{"id":287,"date":"2023-05-23T01:57:01","date_gmt":"2023-05-22T20:27:01","guid":{"rendered":"https:\/\/aiml.3it.in\/?page_id=287"},"modified":"2026-03-29T19:50:46","modified_gmt":"2026-03-29T14:20:46","slug":"callindustry","status":"publish","type":"page","link":"https:\/\/www.aimlsystems.org\/2026\/callindustry\/","title":{"rendered":"Call for Papers Industry Track"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; custom_padding_last_edited=&#8221;on|phone&#8221; disabled_on=&#8221;on|on|on&#8221; admin_label=&#8221;Header&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;gcid-1bcf785a-50e1-437b-b09f-65567babc1de&#8221; background_image=&#8221;https:\/\/www.aimlsystems.org\/2023\/wp-content\/uploads\/2023\/05\/grid-bg-2.png&#8221; background_size=&#8221;initial&#8221; background_position=&#8221;bottom_center&#8221; background_repeat=&#8221;repeat&#8221; custom_padding=&#8221;||22px||false|false&#8221; 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custom_css_free_form=&#8221;selector h2{color:white}&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h2>Call for Papers Industry Track\u00a0<\/h2>\n<p>[\/et_pb_text][et_pb_code disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; disabled=&#8221;on&#8221; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;]<!-- [et_pb_line_break_holder] --><!DOCTYPE html><!-- [et_pb_line_break_holder] --><html><!-- [et_pb_line_break_holder] --><script><!-- [et_pb_line_break_holder] -->window.onload = (event) =>{<!-- [et_pb_line_break_holder] -->document.getElementById('search').style.width = '350px';<!-- [et_pb_line_break_holder] -->}<!-- [et_pb_line_break_holder] -->window.onclick = (event) =>{<!-- [et_pb_line_break_holder] -->document.getElementById('options').innerHTML = '';<!-- [et_pb_line_break_holder] -->}<!-- [et_pb_line_break_holder] -->    <!-- [et_pb_line_break_holder] -->var search_list = {<!-- [et_pb_line_break_holder] 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[et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] -->[\/et_pb_code][\/et_pb_column][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;4.19.2&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; fullwidth=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;-90px||-140px||false|false&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_fullwidth_code _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<div id=\"call-track-page\"><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"dark-overlay\"><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"circuit-lines\"><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"track-content\"><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"hero-section\"><!-- [et_pb_line_break_holder] --><\/p>\n<h1 class=\"glow-text\">Call for Industry Papers<\/h1>\n<p><!-- [et_pb_line_break_holder] --><pee class=\"subtitle\">Solving practical, real-world problems in large-scale environments<\/pee><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"accent-line scanner-animation\"><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"button-row\"><!-- [et_pb_line_break_holder] --><a href=\"#\" class=\"cta-button disabled-btn\">Submit Industry Paper<\/a><!-- [et_pb_line_break_holder] --><a href=\"https:\/\/www.aimlsystems.org\/2026\/wp-content\/uploads\/2026\/03\/AIMLSystems-2026-Call-for-Papers-Version-8.0.pdf\" target=\"_blank\" class=\"cta-button outline-btn\">Download CFP (PDF)<\/a><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"intro-box\"><!-- [et_pb_line_break_holder] --><pee>The Industry Track solicits submissions describing AI-ML systems and solutions addressing practical, real-world problems in industry, broadly defined to include manufacturing, finance, government, and large-scale operational environments.<\/pee><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"split-layout\"><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"topics-column\"><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"glass-card horizontal-card\"><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"icon-side\">01<\/div>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"content-side\"><!-- [et_pb_line_break_holder] --><\/p>\n<h3>Industrial Systems Design<\/h3>\n<p><!-- [et_pb_line_break_holder] --><pee>Focusing on the design and implementation of AI-ML\u2013based systems that solve real industrial or societal problems.<\/pee><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"glass-card horizontal-card\"><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"icon-side\">02<\/div>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"content-side\"><!-- [et_pb_line_break_holder] --><\/p>\n<h3>Real-World Constraints<\/h3>\n<p><!-- [et_pb_line_break_holder] --><pee>Solutions, optimizations, and lessons learned from deploying learning systems under practical constraints such as scale, latency, reliability, cost, safety, and regulation.<\/pee><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"glass-card horizontal-card\"><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"icon-side\">03<\/div>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"content-side\"><!-- [et_pb_line_break_holder] --><\/p>\n<h3>System Implementation<\/h3>\n<p><!-- [et_pb_line_break_holder] --><pee>Describing how existing or previously published AI-ML methods can be adapted, engineered, and integrated into production-level systems.<\/pee><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"glass-card horizontal-card\"><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"icon-side\">04<\/div>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"content-side\"><!-- [et_pb_line_break_holder] --><\/p>\n<h3>System Impact<\/h3>\n<p><!-- [et_pb_line_break_holder] --><pee>Demonstrations of significant and verifiable business, operational, or societal impact resulting from real deployments.<\/pee><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"glass-card horizontal-card highlight-topic\"><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"icon-side\">05<\/div>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"content-side\"><!-- [et_pb_line_break_holder] --><\/p>\n<h3>Dare to Try<\/h3>\n<p><!-- [et_pb_line_break_holder] --><pee>Featuring AI-ML systems under development, ambitious real-world attempts, and well-documented negative results or failures that provide valuable insights.<\/pee><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"timeline-column\"><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"glass-card vertical-timeline-card\"><!-- [et_pb_line_break_holder] --><\/p>\n<h3 class=\"timeline-header\">Important Dates<\/h3>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"timeline-accent\"><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"timeline-body\"><!-- [et_pb_line_break_holder] -->    <\/p>\n<div class=\"timeline-list\"><!-- [et_pb_line_break_holder] -->        <\/p>\n<div class=\"timeline-item\"><!-- [et_pb_line_break_holder] -->            <span class=\"date-highlight\">June 8, 2026<\/span><!-- [et_pb_line_break_holder] -->            <span class=\"date-label\">Abstract Deadline<\/span><!-- [et_pb_line_break_holder] -->        <\/div>\n<p><!-- [et_pb_line_break_holder] -->        <\/p>\n<div class=\"timeline-item\"><!-- [et_pb_line_break_holder] -->            <span class=\"date-highlight\">June 15, 2026<\/span><!-- [et_pb_line_break_holder] -->            <span class=\"date-label\">Paper Submissions Due<\/span><!-- [et_pb_line_break_holder] -->        <\/div>\n<p><!-- [et_pb_line_break_holder] -->        <\/p>\n<div class=\"timeline-item\"><!-- [et_pb_line_break_holder] -->            <span class=\"date-highlight\">July 30, 2026<\/span><!-- [et_pb_line_break_holder] -->            <span class=\"date-label\">Author Notifications<\/span><!-- [et_pb_line_break_holder] -->        <\/div>\n<p><!-- [et_pb_line_break_holder] -->        <\/p>\n<div class=\"timeline-item\"><!-- [et_pb_line_break_holder] -->            <span class=\"date-highlight\">Aug 31, 2026<\/span><!-- [et_pb_line_break_holder] -->            <span class=\"date-label\">Camera Ready Deadline<\/span><!-- [et_pb_line_break_holder] -->        <\/div>\n<p><!-- [et_pb_line_break_holder] -->        <\/p>\n<div class=\"timeline-item conference-date\"><!-- [et_pb_line_break_holder] -->            <span class=\"date-highlight\">Oct 6-9, 2026<\/span><!-- [et_pb_line_break_holder] -->            <span class=\"date-label\">Conference Dates<\/span><!-- [et_pb_line_break_holder] -->        <\/div>\n<p><!-- [et_pb_line_break_holder] -->    <\/div>\n<p><!-- [et_pb_line_break_holder] -->    <pee class=\"small-note aoe-note\">All deadlines are 11:59 pm AoE.<\/pee><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"glass-card vertical-info-card\"><!-- [et_pb_line_break_holder] --><\/p>\n<h3 class=\"timeline-header\">Submission Guidelines<\/h3>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"timeline-accent\"><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"info-body\"><!-- [et_pb_line_break_holder] --><\/p>\n<ul><!-- [et_pb_line_break_holder] --><\/p>\n<li><strong>Page Limit:<\/strong> 6 pages (main) + references.<\/li>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<li><strong>Format:<\/strong> Double-column IEEE Format.<\/li>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<li><strong>Content:<\/strong> Must report real-world deployment or prototype results.<\/li>\n<p><!-- [et_pb_line_break_holder] --><\/ul>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"chairs-section\"><!-- [et_pb_line_break_holder] --><\/p>\n<h2 class=\"cyan-text\">For queries, contact the Industry Chair<\/h2>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"text-chairs-row\"><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"glass-card text-chair\"><!-- [et_pb_line_break_holder] --><\/p>\n<h4>Marco Tarabini<\/h4>\n<p><!-- [et_pb_line_break_holder] --><pee>Politecnico di Milano<\/pee><!-- [et_pb_line_break_holder] --><a href=\"https:\/\/www.mecc.polimi.it\/en\/staff\/marco.tarabini\" target=\"_blank\" class=\"link-btn\">Profile<\/a><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] --><\/p>\n<style><!-- [et_pb_line_break_holder] -->\/* === SHARED CSS (Research & Industry - Same Colors) === *\/<!-- [et_pb_line_break_holder] -->#call-track-page {<!-- [et_pb_line_break_holder] -->--purple: #bc13fe; --cyan: #00e5ff; --bg: #0b0d17;<!-- [et_pb_line_break_holder] -->background: var(--bg) url('https:\/\/www.aimlsystems.org\/2026\/wp-content\/uploads\/2026\/01\/circuit-board-bg.jpg') fixed center\/cover;<!-- [et_pb_line_break_holder] -->padding: 220px 5% 100px; font-family: 'Poppins', sans-serif; color: #fff; position: relative;<!-- 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[et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] -->@keyframes scanLine { 0% { left: -100%; } 100% { left: 100%; } }<!-- [et_pb_line_break_holder] --><!-- [et_pb_line_break_holder] -->@media (max-width: 980px) {<!-- [et_pb_line_break_holder] -->.split-layout { flex-direction: column; }<!-- [et_pb_line_break_holder] -->.timeline-column { width: 100%; position: static; }<!-- [et_pb_line_break_holder] -->.hero-section h1 { font-size: 40px; }<!-- [et_pb_line_break_holder] -->#call-track-page { padding-top: 150px; }<!-- [et_pb_line_break_holder] -->}<!-- [et_pb_line_break_holder] --><\/style>\n<p>[\/et_pb_fullwidth_code][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; disabled_on=&#8221;on|on|on&#8221; admin_label=&#8221;Features&#8221; module_id=&#8221;about&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;#c1c1c1&#8243; background_image=&#8221;https:\/\/www.aimlsystems.org\/2023\/wp-content\/uploads\/2023\/05\/rm380-10.jpg&#8221; background_blend=&#8221;overlay&#8221; custom_padding=&#8221;0%||||false|false&#8221; use_background_color_gradient_phone=&#8221;on&#8221; background_color_gradient_stops_phone=&#8221;#001528 0%|rgba(255, 255, 255, 0) 10%|rgba(255,255,255,0) 70%|#0f0122 100%&#8221; disabled=&#8221;on&#8221; collapsed=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row column_structure=&#8221;3_5,2_5&#8243; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; min_height=&#8221;428.7px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;3_5&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_code _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<html><!-- [et_pb_line_break_holder] --><\/p>\n<style><!-- [et_pb_line_break_holder] -->  #submit_button{color:black;border-style:solid}<!-- [et_pb_line_break_holder] -->  <\/style>\n<p><\/html>[\/et_pb_code][et_pb_text disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; text_font=&#8221;|700|||||||&#8221; text_text_color=&#8221;#E02B20&#8243; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p>Notification of acceptance: 31st August 2025, 11:59 pm AoE<\/p>\n<p>Final submission: 10th September 2025,11:59 pm AoE<\/p>\n<p>[\/et_pb_text][et_pb_button button_url=&#8221;https:\/\/cmt3.research.microsoft.com\/AIMLSys2025\/&#8221; url_new_window=&#8221;on&#8221; button_text=&#8221;Submit Papers&#8221; button_alignment=&#8221;left&#8221; disabled_on=&#8221;off|off|off&#8221; admin_label=&#8221;Submit Button&#8221; module_id=&#8221;submit_button&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;_initial&#8221; custom_button=&#8221;on&#8221; button_text_size=&#8221;15px&#8221; button_border_width=&#8221;1px&#8221; button_border_radius=&#8221;78px&#8221; button_font=&#8221;Poppins|500||on|||||&#8221; button_icon=&#8221;&#x24;||divi||400&#8243; animation_style=&#8221;fade&#8221; custom_css_main_element=&#8221;  &#8221; global_colors_info=&#8221;{}&#8221; button_bg_color__hover_enabled=&#8221;on|hover&#8221; button_bg_color__hover=&#8221;&#8221; button_bg_enable_color__hover=&#8221;off&#8221; button_bg_color_gradient_stops__hover=&#8221;#2b87da 0%|#0d1c63 100%&#8221; button_bg_use_color_gradient__hover=&#8221;on&#8221;][\/et_pb_button][et_pb_text _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span style=\"font-weight: 400;\">With the rapid growth of industrial and real-life adoption of artificial intelligence (AI) and<br \/>machine learning (ML), a new research area is emerging at their intersection with<br \/>systems design. This area is seeded by the continued growth in data volume, rapid<br \/>increase in size and complexity of predictive models and scale-up supported through<br \/>development of large-scale AI\/ML hardware. We solicit submissions of papers<br \/>describing designs and implementations of solutions and systems for practical tasks at<br \/>the intersection of AI\/ML and computer systems. The primary emphasis is on papers<br \/>that \u200beither solve or advance the understanding of \u200bissues related to deploying learning<br \/>systems in the real world. We also aim to elicit new connections among these diverse<br \/>fields, and identify tools, best practices, and design principles. Papers demonstrating<br \/>\u200bsignificant, verifiable\u200b business and\/or real-world impact as a result of such deployments<br \/>are encouraged.<\/span><\/p>\n<p><span style=\"font-weight: 400;\"><span>The use of artificial intelligence (AI)\u2013generated text in an article shall be disclosed in the acknowledgments section of any paper submitted to an IEEE Conference or Periodical. The sections of the paper that use AI-generated text shall have a citation to the AI system used to generate the text<\/span><\/span><\/p>\n<p>[\/et_pb_text][et_pb_button button_url=&#8221;https:\/\/www.ieee.org\/conferences\/publishing\/templates&#8221; url_new_window=&#8221;on&#8221; button_text=&#8221;IEEE TEMPLATE&#8221; button_alignment=&#8221;left&#8221; disabled_on=&#8221;off|off|off&#8221; admin_label=&#8221;Submit Button&#8221; module_id=&#8221;submit_button&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;_initial&#8221; custom_button=&#8221;on&#8221; button_text_size=&#8221;15px&#8221; button_border_width=&#8221;1px&#8221; button_border_radius=&#8221;78px&#8221; button_font=&#8221;Poppins|500||on|||||&#8221; button_icon=&#8221;&#x24;||divi||400&#8243; animation_style=&#8221;fade&#8221; custom_css_main_element=&#8221;  &#8221; global_colors_info=&#8221;{}&#8221; button_bg_color__hover_enabled=&#8221;on|hover&#8221; button_bg_color__hover=&#8221;&#8221; button_bg_enable_color__hover=&#8221;off&#8221; button_bg_color_gradient_stops__hover=&#8221;#2b87da 0%|#0d1c63 100%&#8221; button_bg_use_color_gradient__hover=&#8221;on&#8221;][\/et_pb_button][et_pb_button button_url=&#8221;https:\/\/www.aimlsystems.org\/2025\/wp-content\/uploads\/2025\/09\/POSTER-Template-AI-ML-Systems.pptx&#8221; url_new_window=&#8221;on&#8221; button_text=&#8221;POSTER TEMPLATE&#8221; button_alignment=&#8221;left&#8221; disabled_on=&#8221;off|off|off&#8221; admin_label=&#8221;Submit Button&#8221; module_id=&#8221;submit_button&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;_initial&#8221; custom_button=&#8221;on&#8221; button_text_size=&#8221;15px&#8221; button_border_width=&#8221;1px&#8221; button_border_radius=&#8221;78px&#8221; button_font=&#8221;Poppins|500||on|||||&#8221; button_icon=&#8221;&#x24;||divi||400&#8243; animation_style=&#8221;fade&#8221; custom_css_main_element=&#8221;  &#8221; global_colors_info=&#8221;{}&#8221; button_bg_color__hover_enabled=&#8221;on|hover&#8221; button_bg_color__hover=&#8221;&#8221; button_bg_enable_color__hover=&#8221;off&#8221; button_bg_color_gradient_stops__hover=&#8221;#2b87da 0%|#0d1c63 100%&#8221; button_bg_use_color_gradient__hover=&#8221;on&#8221;][\/et_pb_button][et_pb_text disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; text_text_color=&#8221;#2d2d2d&#8221; disabled=&#8221;on&#8221; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h3><b data-ogsc=\"\">Camera Ready Submission<\/b><\/h3>\n<ul>\n<li>Authors of accepted papers will<span class=\"x_apple-converted-space\" data-ogsc=\"\">\u00a0<\/span>be allocated 8 pages (including references, appendix, acknowledgements) in<span class=\"x_apple-converted-space\" data-ogsc=\"\">\u00a0<\/span>the conference proceedings. Information regarding formatting and submission of final paper can be found at: <a href=\"https:\/\/www.overleaf.com\/gallery\/tagged\/acm-official\" target=\"_blank\" rel=\"noopener noreferrer\" data-auth=\"NotApplicable\" title=\"https:\/\/www.overleaf.com\/gallery\/tagged\/acm-official\" data-ogsc=\"\" data-linkindex=\"0\">https:\/\/www.overleaf.com\/gallery\/tagged\/acm-official<\/a>.<\/li>\n<li class=\"text-justify pe-4\">The deadline for camera-ready paper submission and copyright form is Sep 29, 2023. The camera ready submission will be through <a href=\"https:\/\/cmt3.research.microsoft.com\/AIMLSystems2023\/\" target=\"_blank\" rel=\"noopener noreferrer\" data-auth=\"NotApplicable\" title=\"https:\/\/cmt3.research.microsoft.com\/AIMLSystems2023\/\" data-ogsc=\"\" data-linkindex=\"1\">https:\/\/cmt3.research.microsoft.com\/AIMLSystems2023\/.<\/a><\/li>\n<li class=\"x_MsoNormal\" data-ogsb=\"white\">At least one author of accepted paper must also complete conference registration by Sep 29, 2023 at full rate (not student\/workshop rate) in order for the paper to be included in the proceedings and program. Registration details are available at: <a href=\"https:\/\/www.aimlsystems.org\/2023\/registration\" target=\"_blank\" rel=\"noopener noreferrer\" data-auth=\"NotApplicable\" title=\"https:\/\/www.aimlsystems.org\/2023\/registration\" data-ogsc=\"\" data-linkindex=\"2\">https:\/\/www.aimlsystems.org\/2023\/registration<\/a>.<span class=\"x_apple-converted-space\" data-ogsc=\"\">\u00a0<\/span><\/li>\n<\/ul>\n<p>[\/et_pb_text][et_pb_text disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; text_text_color=&#8221;#FFFFFF&#8221; header_3_font=&#8221;|700|||||||&#8221; custom_margin=&#8221;||8px|||&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h3><strong>DEPLOYED Systems<\/strong><\/h3>\n<p>[\/et_pb_text][et_pb_text disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span style=\"font-weight: 400;\">We specially encourage implementation of a system that solves a real-world problem and is (or was or is planned) in production use for an extended period. The paper should present the problem, its significance to the application domain, the decisions and tradeoffs made when making design choices for the solution, the deployment challenges, and the lessons learned from successes and failures (when applicable). Papers that describe enabling infrastructure for large-scale deployment of applied machine learning also fall in this category. The work may particularly focus on how to overcome real challenges in the pipelines which may include data collection, low-resource processing, and usability, and it is perfectly fine that the underlying machine learning algorithms are not fundamentally groundbreaking.<\/span><\/p>\n<p>[\/et_pb_text][\/et_pb_column][et_pb_column type=&#8221;2_5&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_tabs active_tab_background_color=&#8221;#1c1b3a&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; tab_text_color=&#8221;#FFFFFF&#8221; background_color=&#8221;rgba(0,0,0,0)&#8221; width=&#8221;100%&#8221; border_radii=&#8221;on|11px|11px|11px|11px&#8221; global_colors_info=&#8221;{%22gcid-f1f9244b-c8ab-43e1-95c3-c0bdf69ac7b5%22:%91%22active_tab_background_color%22%93}&#8221;][et_pb_tab title=&#8221;Important Dates&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Abstract deadline: July 11, 2025, 11:59 pm AoE.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Notification of acceptance: 31st August 2025, <span style=\"font-weight: 400;\">11:59 pm <\/span>AoE<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Final (Camera Ready) submission: 10th September 2025,<span style=\"font-weight: 400;\">11:59 pm <\/span>AoE<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Conference dates: Oct 08-11, 2025<\/span><\/li>\n<\/ul>\n<p>[\/et_pb_tab][\/et_pb_tabs][et_pb_tabs active_tab_background_color=&#8221;#1c1b3a&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; tab_text_color=&#8221;#FFFFFF&#8221; background_color=&#8221;rgba(0,0,0,0)&#8221; border_radii=&#8221;on|11px|11px|11px|11px&#8221; global_colors_info=&#8221;{%22gcid-f1f9244b-c8ab-43e1-95c3-c0bdf69ac7b5%22:%91%22active_tab_background_color%22%93}&#8221;][et_pb_tab title=&#8221;Chairs&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<ul>\n<li><a href=\"https:\/\/www.linkedin.com\/in\/anupamisb\/\" target=\"_blank\" rel=\"noopener\"><span style=\"text-decoration: underline;\">Anupam Purwar<\/span><\/a><span style=\"text-decoration: underline;\">,<\/span> Sprinklr, India<\/li>\n<li><a href=\"http:\/\/www.cs.iit.edu\/~vgurbani\/\" target=\"_blank\" rel=\"noopener\"><span style=\"text-decoration: underline;\">Vijay Gurbani<\/span><\/a>, <span>Illinois Institute of Technology, USA<\/span><\/li>\n<\/ul>\n<p>[\/et_pb_tab][\/et_pb_tabs][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><em>The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.<\/em><\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h3>Panel Discussion<\/h3>\n<p><b>\u00a0(GenAI for everyday customer)<\/b><\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;27px||43px|||&#8221; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Title&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><b>GenAI for everyday customer<\/b><\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Moderator&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><b><a href=\"https:\/\/anupam-purwar.github.io\/page\/\" target=\"_blank\" rel=\"noopener\">Anupam Purwar<\/a>, Sprinklr<\/b><\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Questions&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<ol>\n<li><span style=\"font-weight: 400;\">How is Generative Changimg the consumer behaviour in IT industry?<\/span><\/li>\n<li><span style=\"font-weight: 400;\">How is Gen AI security becoming important and what are some security\u00a0 implications of using LLms?<\/span><\/li>\n<li><span style=\"font-weight: 400;\">What are some top Frontier LLms which are finding place in consumer products being developed by consulting firms these days?<\/span><\/li>\n<\/ol>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=&#8221;1_4,3_4&#8243; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;27px||43px|||&#8221; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;1_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_image src=&#8221;https:\/\/www.aimlsystems.org\/2025\/wp-content\/uploads\/2025\/10\/Naveen.png&#8221; title_text=&#8221;Naveen&#8221; align=&#8221;center&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; max_width=&#8221;200px&#8221; custom_margin=&#8221;||15px|||&#8221; filter_saturate=&#8221;0%&#8221; animation_style=&#8221;slide&#8221; border_radii=&#8221;on|115px|115px|115px|115px&#8221; border_color_all=&#8221;#FFFFFF&#8221; box_shadow_style=&#8221;preset2&#8243; global_colors_info=&#8221;{}&#8221; transform_styles__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover_enabled=&#8221;on|hover&#8221; transform_translate__hover_enabled=&#8221;on|hover&#8221; transform_rotate__hover_enabled=&#8221;on|hover&#8221; transform_skew__hover_enabled=&#8221;on|hover&#8221; transform_origin__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover=&#8221;104%|104%&#8221; filter_saturate__hover_enabled=&#8221;on|hover&#8221; filter_saturate__hover=&#8221;100%&#8221; border_width_all__hover_enabled=&#8221;on|hover&#8221; border_width_all__hover=&#8221;1px&#8221; border_radii__hover_enabled=&#8221;on|hover&#8221; border_radii__hover=&#8221;on|115px|115px|115px|115px&#8221;][\/et_pb_image][\/et_pb_column][et_pb_column type=&#8221;3_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;25d2b0d8-2373-4ae8-9188-0ef4b1bb77f4&#8243; text_text_color=&#8221;#212A4F&#8221; header_4_text_color=&#8221;gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68&#8243; header_4_font_size=&#8221;20px&#8221; custom_margin=&#8221;||15px|||&#8221; global_colors_info=&#8221;{%22gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68%22:%91%22header_4_text_color%22%93}&#8221;]<\/p>\n<h4><a href=\"https:\/\/www.liquidmind.ai\/company\/founder-profile\" target=\"_blank\" rel=\"noopener\"><strong>Naveen Athresh<\/strong><\/a><\/h4>\n<p>Founder, Liquidmins.ai<\/p>\n<p>[\/et_pb_text][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Bio&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span style=\"font-weight: 400;\">Naveen runs liquidmind.ai in the mixed reality, digital commerce\/Fintech space. A TEDx speaker, Forbes India 2020 top 100 leader (the only leader selected from Rakuten), he has consistently built 200+ member led high performance teams from scratch, led cross geo Product Engineering and Data sciences teams. He has been regularly featured as a thought leader across leading business dailies. Most recently, Naveen was featured on the January 2024 featured section with an elite list of business people globally (mostly USA) on a Global business magazine<\/span><a href=\"https:\/\/businesstodaymag.com\/business\/thought-leaders-making-an-impact-in-the-world\/\"><span style=\"font-weight: 400;\"> (Business Today) and USAwire<\/span><\/a><span style=\"font-weight: 400;\"> in an article called \u201cThought leaders making an impact in the world\u201d<\/span><\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=&#8221;1_4,3_4&#8243; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;27px||43px|||&#8221; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;1_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_image src=&#8221;https:\/\/www.aimlsystems.org\/2025\/wp-content\/uploads\/2025\/10\/Gaurav.png&#8221; title_text=&#8221;Gaurav&#8221; align=&#8221;center&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; max_width=&#8221;200px&#8221; custom_margin=&#8221;||15px|||&#8221; filter_saturate=&#8221;0%&#8221; animation_style=&#8221;slide&#8221; border_radii=&#8221;on|115px|115px|115px|115px&#8221; border_color_all=&#8221;#FFFFFF&#8221; box_shadow_style=&#8221;preset2&#8243; global_colors_info=&#8221;{}&#8221; transform_styles__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover_enabled=&#8221;on|hover&#8221; transform_translate__hover_enabled=&#8221;on|hover&#8221; transform_rotate__hover_enabled=&#8221;on|hover&#8221; transform_skew__hover_enabled=&#8221;on|hover&#8221; transform_origin__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover=&#8221;104%|104%&#8221; filter_saturate__hover_enabled=&#8221;on|hover&#8221; filter_saturate__hover=&#8221;100%&#8221; border_width_all__hover_enabled=&#8221;on|hover&#8221; border_width_all__hover=&#8221;1px&#8221; border_radii__hover_enabled=&#8221;on|hover&#8221; border_radii__hover=&#8221;on|115px|115px|115px|115px&#8221;][\/et_pb_image][\/et_pb_column][et_pb_column type=&#8221;3_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;25d2b0d8-2373-4ae8-9188-0ef4b1bb77f4&#8243; text_text_color=&#8221;#212A4F&#8221; header_4_text_color=&#8221;gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68&#8243; header_4_font_size=&#8221;20px&#8221; custom_margin=&#8221;||15px|||&#8221; global_colors_info=&#8221;{%22gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68%22:%91%22header_4_text_color%22%93}&#8221;]<\/p>\n<h4><a href=\"https:\/\/www.linkedin.com\/in\/gauravsecurity?utm_source=share&amp;utm_campaign=share_via&amp;utm_content=profile&amp;utm_medium=ios_app\" target=\"_blank\" rel=\"noopener\"><strong>Gaurav Rai <\/strong><\/a><\/h4>\n<p><span style=\"font-weight: 400;\">AI security at Microsoft Seattle<\/span><\/p>\n<p>[\/et_pb_text][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Bio&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span style=\"font-weight: 400;\">Gaurav Rai is a seasoned AI Security leader with over two decades of experience driving innovation and excellence in cybersecurity and artificial intelligence security. Currently serving at Microsoft USA, Gaurav leads critical initiatives in AI security, including\u00a0 spearheading security design and requirements for the AI organization. Gaurav has presented at major industry conferences, co-authored research on explainable AI for mental health, and played a pivotal role in securing Microsoft Copilot and Bing services. With a proven track record at leading organizations such as PayPal, AT&amp;T, and Teradata, Gaurav combines deep technical expertise with strategic leadership, mentoring teams and advancing enterprise security standards. Gaurav holds a Master\u2019s degree from Birla Institute of Technology and Science, is a CISSP-certified professional, and is recognized for building cross-functional partnerships and driving impactful security solutions in cloud and AI.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=&#8221;1_4,3_4&#8243; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;27px||43px|||&#8221; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;1_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_image src=&#8221;https:\/\/www.aimlsystems.org\/2025\/wp-content\/uploads\/2025\/10\/Mohit.jpg&#8221; title_text=&#8221;Mohit&#8221; align=&#8221;center&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; max_width=&#8221;200px&#8221; custom_margin=&#8221;||15px|||&#8221; filter_saturate=&#8221;0%&#8221; animation_style=&#8221;slide&#8221; border_radii=&#8221;on|115px|115px|115px|115px&#8221; border_color_all=&#8221;#FFFFFF&#8221; box_shadow_style=&#8221;preset2&#8243; global_colors_info=&#8221;{}&#8221; transform_styles__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover_enabled=&#8221;on|hover&#8221; transform_translate__hover_enabled=&#8221;on|hover&#8221; transform_rotate__hover_enabled=&#8221;on|hover&#8221; transform_skew__hover_enabled=&#8221;on|hover&#8221; transform_origin__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover=&#8221;104%|104%&#8221; filter_saturate__hover_enabled=&#8221;on|hover&#8221; filter_saturate__hover=&#8221;100%&#8221; border_width_all__hover_enabled=&#8221;on|hover&#8221; border_width_all__hover=&#8221;1px&#8221; border_radii__hover_enabled=&#8221;on|hover&#8221; border_radii__hover=&#8221;on|115px|115px|115px|115px&#8221;][\/et_pb_image][\/et_pb_column][et_pb_column type=&#8221;3_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;25d2b0d8-2373-4ae8-9188-0ef4b1bb77f4&#8243; text_text_color=&#8221;#212A4F&#8221; header_4_text_color=&#8221;gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68&#8243; header_4_font_size=&#8221;20px&#8221; custom_margin=&#8221;||15px|||&#8221; global_colors_info=&#8221;{%22gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68%22:%91%22header_4_text_color%22%93}&#8221;]<\/p>\n<h4>MOHIT SRIVASTAVA<\/h4>\n<p><span style=\"font-weight: 400;\">Head of Engineering at OneByZero (OBZ) Analytics<\/span>[\/et_pb_text][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Bio&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span style=\"font-weight: 400;\">Mohit Srivastava is the Head of Engineering at OneByZero (OBZ) Analytics, a next-generation Data and AI consulting firm headquartered in Singapore and serving enterprises across the Asia-Pacific region. With over 12 years of experience in enterprise technology, he leads the design and delivery of secure, scalable, and production-ready Generative AI solutions that empower organizations to transform operations and customer experiences.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Mohit has partnered with several leading banks and telecommunications companies across ASEAN, helping them adopt AI responsibly \u2014 from large-scale data modernization to Generative AI-driven automation and decision intelligence. His deep expertise spans cloud-native architectures, multi-agent AI systems, and enterprise AI governance, ensuring that innovation aligns with security, compliance, and measurable business outcomes.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">An active advocate of the open-source and AI research community, Mohit champions collaborative innovation and responsible AI adoption within regulated industries. His work reflects a strong belief that the true promise of Generative AI lies in enabling enterprises to deliver tangible value to everyday customers \u2014 responsibly and at scale.<\/span><\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; header_4_font_size_tablet=&#8221;&#8221; header_4_font_size_phone=&#8221;22px&#8221; header_4_font_size_last_edited=&#8221;on|desktop&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h3 id=\"topics-of-interest\">Invited Speakers<\/h3>\n<p>&nbsp;<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=&#8221;1_4,3_4&#8243; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;45px|||||&#8221; border_width_top=&#8221;1px&#8221; border_color_top=&#8221;#878787&#8243; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;1_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_image src=&#8221;https:\/\/www.aimlsystems.org\/2025\/wp-content\/uploads\/2025\/09\/AjitaMishra.jpg&#8221; title_text=&#8221;AjitaMishra&#8221; align=&#8221;center&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; max_width=&#8221;200px&#8221; custom_margin=&#8221;||15px|||&#8221; filter_saturate=&#8221;0%&#8221; animation_style=&#8221;slide&#8221; border_radii=&#8221;on|115px|115px|115px|115px&#8221; border_color_all=&#8221;#FFFFFF&#8221; box_shadow_style=&#8221;preset2&#8243; global_colors_info=&#8221;{}&#8221; transform_styles__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover_enabled=&#8221;on|hover&#8221; transform_translate__hover_enabled=&#8221;on|hover&#8221; transform_rotate__hover_enabled=&#8221;on|hover&#8221; transform_skew__hover_enabled=&#8221;on|hover&#8221; transform_origin__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover=&#8221;104%|104%&#8221; filter_saturate__hover_enabled=&#8221;on|hover&#8221; filter_saturate__hover=&#8221;100%&#8221; border_width_all__hover_enabled=&#8221;on|hover&#8221; border_width_all__hover=&#8221;1px&#8221; border_radii__hover_enabled=&#8221;on|hover&#8221; border_radii__hover=&#8221;on|115px|115px|115px|115px&#8221;][\/et_pb_image][\/et_pb_column][et_pb_column type=&#8221;3_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;25d2b0d8-2373-4ae8-9188-0ef4b1bb77f4&#8243; text_text_color=&#8221;gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68&#8243; header_4_text_color=&#8221;gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68&#8243; header_4_font_size=&#8221;20px&#8221; custom_margin=&#8221;||15px|||&#8221; global_colors_info=&#8221;{%22gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68%22:%91%22text_text_color%22,%22header_4_text_color%22%93}&#8221;]<\/p>\n<h4><a href=\"https:\/\/www.linkedin.com\/in\/ajita-agarwala-67a154121\/?originalSubdomain=in\" target=\"_blank\" rel=\"noopener\">Ajita Agarwala<\/a><\/h4>\n<p><span>Founder, CultureVo<\/span><\/p>\n<p>[\/et_pb_text][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Title&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span>Inside Novi: Building the Bumble of AI Companions<\/span><\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Abstract&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p>At CultureVo, we\u2019re building Novi\u2014AI companions designed to be as diverse, engaging, and trustworthy as the people you\u2019d meet on a global journey. Unlike generic chatbots, Novi is powered by agentic architectures and multimodal models that allow for stable personas, long-term memory, and proactive interaction\u2014making them feel more like friends, not tools.<\/p>\n<p>In this talk, we\u2019ll peel back the layers of the Novi stack and walk through the technical foundations behind key features:<\/p>\n<ul>\n<li>\n<p dir=\"auto\">Bumble of AI Companions: Multi-agent orchestration that lets users \u201cmatch\u201d with different Novi personalities, each backed by distinct prompt architectures,\u00a0<span>cultural corpora, and bias-aware training pipelines to ensure diverse, context-aware voices.<\/span><\/p>\n<\/li>\n<li>\n<p dir=\"auto\">Stable Bot Personas: Techniques for consistent long-term identity + structured retrieval ensuring Novi doesn\u2019t \u201cdrift\u201d over time.<\/p>\n<\/li>\n<li>\n<p dir=\"auto\">Voice Calls: Real-time speech synthesis + low-latency pipelines enabling fluid human-like conversation.<\/p>\n<\/li>\n<li>\n<p dir=\"auto\">Games: Lightweight agentic sandboxes where companions can co-create stories, memories, or roleplay with users.<\/p>\n<\/li>\n<li>\n<p>Memory: Hierarchical memory architecture (short-term context windows + long-term vector stores) to maintain continuity.<\/p>\n<\/li>\n<li>\n<p>Proactive Messages: Event-driven triggers and scheduling agents that let Novi reach out first, not just respond.<\/p>\n<\/li>\n<li>\n<p>Categoriser: On-device classifiers that auto-organize chats, insights, and emotional states into structured categories.<\/p>\n<\/li>\n<li>\n<p>Journal: Agent-chained summarization that transforms daily conversations into a reflective log.<\/p>\n<\/li>\n<li>\n<p dir=\"auto\">Selfie Reader &amp; Generator: Multimodal vision pipelines\u00a0to let Novi \u201csee\u201d you and generate creative outputs.<\/p>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p>By walking through these features, we\u2019ll discuss how agent frameworks, multimodality, and cultural intelligence combine to create AI companions that feel humanly complex yet technically robust.<\/p>\n<p>The session is a deep dive into not just what Novi does\u2014but how emerging AI infrastructures are evolving to support a new class of persistent, emotionally resonant agents.<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Bio&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<div class=\"row\">\n<div class=\"col-9 col-12-medium\">\n<div class=\"text-justify\">\n<p><span>Ajita Agarwala, founder of CultureVo, is a firm believer in AI as a leveler in a world of inequalities. Through CultureVo, she seeks to bridge the cultural intelligence gap and offer the richness of the world to its citizens on a platter. Novi AI, developed by CultureVo, embodies this vision by providing culturally diverse and emotionally intelligent, affective AI partners. Ajita herself has witnessed the power of this intelligence in her own journey- as an Indian Civil Servant and diplomat to the G20, World Bank, and the United Nations, and as a graduate of Princeton University.<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=&#8221;1_4,3_4&#8243; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;45px|||||&#8221; border_width_top=&#8221;1px&#8221; border_color_top=&#8221;#878787&#8243; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;1_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_image src=&#8221;https:\/\/www.aimlsystems.org\/2025\/wp-content\/uploads\/2025\/09\/Gopinath.jpg&#8221; title_text=&#8221;Gopinath&#8221; align=&#8221;center&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; max_width=&#8221;200px&#8221; custom_margin=&#8221;||15px|||&#8221; filter_saturate=&#8221;0%&#8221; animation_style=&#8221;slide&#8221; border_radii=&#8221;on|115px|115px|115px|115px&#8221; border_color_all=&#8221;#FFFFFF&#8221; box_shadow_style=&#8221;preset2&#8243; global_colors_info=&#8221;{}&#8221; transform_styles__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover_enabled=&#8221;on|hover&#8221; transform_translate__hover_enabled=&#8221;on|hover&#8221; transform_rotate__hover_enabled=&#8221;on|hover&#8221; transform_skew__hover_enabled=&#8221;on|hover&#8221; transform_origin__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover=&#8221;104%|104%&#8221; filter_saturate__hover_enabled=&#8221;on|hover&#8221; filter_saturate__hover=&#8221;100%&#8221; border_width_all__hover_enabled=&#8221;on|hover&#8221; border_width_all__hover=&#8221;1px&#8221; border_radii__hover_enabled=&#8221;on|hover&#8221; border_radii__hover=&#8221;on|115px|115px|115px|115px&#8221;][\/et_pb_image][\/et_pb_column][et_pb_column type=&#8221;3_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;25d2b0d8-2373-4ae8-9188-0ef4b1bb77f4&#8243; text_text_color=&#8221;gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68&#8243; header_4_text_color=&#8221;gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68&#8243; header_4_font_size=&#8221;20px&#8221; custom_margin=&#8221;||15px|||&#8221; global_colors_info=&#8221;{%22gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68%22:%91%22text_text_color%22,%22header_4_text_color%22%93}&#8221;]<\/p>\n<h4><a href=\"https:\/\/www.csa.iisc.ac.in\/~gopi\/\" target=\"_blank\" rel=\"noopener\">K. Gopinath<span>\u00a0<\/span><\/a><\/h4>\n<p><span>Indian Institute of Science, <\/span><span>Bangalore<\/span><\/p>\n<p>[\/et_pb_text][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Title&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p>Demystifying AI thru some History and some Philosophy<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Abstract&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p>At CultureVo, we\u2019re building Novi\u2014AI companions designed to be as diverse, engaging, and trustworthy as the people you\u2019d meet on a global journey. Unlike generic chatbots, Novi is powered by agentic architectures and multimodal models that allow for stable personas, long-term memory, and proactive interaction\u2014making them feel more like friends, not tools.<\/p>\n<p>In this talk, we\u2019ll peel back the layers of the Novi stack and walk through the technical foundations behind key features:<\/p>\n<ul>\n<li>\n<p dir=\"auto\">Bumble of AI Companions: Multi-agent orchestration that lets users \u201cmatch\u201d with different Novi personalities, each backed by distinct prompt architectures,\u00a0<span>cultural corpora, and bias-aware training pipelines to ensure diverse, context-aware voices.<\/span><\/p>\n<\/li>\n<li>\n<p dir=\"auto\">Stable Bot Personas: Techniques for consistent long-term identity + structured retrieval ensuring Novi doesn\u2019t \u201cdrift\u201d over time.<\/p>\n<\/li>\n<li>\n<p dir=\"auto\">Voice Calls: Real-time speech synthesis + low-latency pipelines enabling fluid human-like conversation.<\/p>\n<\/li>\n<li>\n<p dir=\"auto\">Games: Lightweight agentic sandboxes where companions can co-create stories, memories, or roleplay with users.<\/p>\n<\/li>\n<li>\n<p>Memory: Hierarchical memory architecture (short-term context windows + long-term vector stores) to maintain continuity.<\/p>\n<\/li>\n<li>\n<p>Proactive Messages: Event-driven triggers and scheduling agents that let Novi reach out first, not just respond.<\/p>\n<\/li>\n<li>\n<p>Categoriser: On-device classifiers that auto-organize chats, insights, and emotional states into structured categories.<\/p>\n<\/li>\n<li>\n<p>Journal: Agent-chained summarization that transforms daily conversations into a reflective log.<\/p>\n<\/li>\n<li>\n<p dir=\"auto\">Selfie Reader &amp; Generator: Multimodal vision pipelines\u00a0to let Novi \u201csee\u201d you and generate creative outputs.<\/p>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p>By walking through these features, we\u2019ll discuss how agent frameworks, multimodality, and cultural intelligence combine to create AI companions that feel humanly complex yet technically robust.<\/p>\n<p>The session is a deep dive into not just what Novi does\u2014but how emerging AI infrastructures are evolving to support a new class of persistent, emotionally resonant agents.<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Bio&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<div class=\"row\">\n<div class=\"col-9 col-12-medium\">\n<div class=\"text-justify\">\n<p><span>Prof. K. Gopinath, after superannuating from IISc, Bangalore in 2021 <\/span><span>as a professor of Computer Science, is now a senior professor at <\/span><span>Rishihood Univ. He also headed the CSAI program at Plaksha Univ (betw <\/span><span>2021-24). His research interests are (in the &#8220;AI&#8221; area) in sysML (ML <\/span><span>applied to computer systems design) and (in the &#8220;computer systems&#8221; <\/span><span>area) primarily in OS, systems security\/privacy and systems <\/span><span>verification. He is the co-author of 2 books: Suparna Bhattacharya, <\/span><span>Kanchi Gopinath, Doug Voigt, &#8220;Resource Proportional Software Design <\/span><span>for Emerging Systems,&#8221; Chapman and Hall\/CRC, 2020 and Kanchi Gopinath, <\/span><span>Shailaja DSharma, &#8220;The Computation Meme: Computational Thinking in <\/span><span>the Indic Tradition&#8221;, IIScPress, 2024.<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=&#8221;1_4,3_4&#8243; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;45px|||||&#8221; border_width_top=&#8221;1px&#8221; border_color_top=&#8221;#878787&#8243; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;1_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_image src=&#8221;https:\/\/www.aimlsystems.org\/2025\/wp-content\/uploads\/2025\/10\/Samarth.jpg&#8221; alt=&#8221;Samarth&#8221; title_text=&#8221;Samarth&#8221; align=&#8221;center&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; max_width=&#8221;200px&#8221; custom_margin=&#8221;||15px|||&#8221; filter_saturate=&#8221;0%&#8221; animation_style=&#8221;slide&#8221; border_radii=&#8221;on|115px|115px|115px|115px&#8221; border_color_all=&#8221;#FFFFFF&#8221; box_shadow_style=&#8221;preset2&#8243; global_colors_info=&#8221;{}&#8221; transform_styles__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover_enabled=&#8221;on|hover&#8221; transform_translate__hover_enabled=&#8221;on|hover&#8221; transform_rotate__hover_enabled=&#8221;on|hover&#8221; transform_skew__hover_enabled=&#8221;on|hover&#8221; transform_origin__hover_enabled=&#8221;on|hover&#8221; transform_scale__hover=&#8221;104%|104%&#8221; filter_saturate__hover_enabled=&#8221;on|hover&#8221; filter_saturate__hover=&#8221;100%&#8221; border_width_all__hover_enabled=&#8221;on|hover&#8221; border_width_all__hover=&#8221;1px&#8221; border_radii__hover_enabled=&#8221;on|hover&#8221; border_radii__hover=&#8221;on|115px|115px|115px|115px&#8221;][\/et_pb_image][\/et_pb_column][et_pb_column type=&#8221;3_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;25d2b0d8-2373-4ae8-9188-0ef4b1bb77f4&#8243; text_text_color=&#8221;gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68&#8243; header_4_text_color=&#8221;gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68&#8243; header_4_font_size=&#8221;20px&#8221; custom_margin=&#8221;||15px|||&#8221; global_colors_info=&#8221;{%22gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68%22:%91%22text_text_color%22,%22header_4_text_color%22%93}&#8221;]<\/p>\n<h4><a href=\"https:\/\/www.spinorlabs.com\/people\" target=\"_blank\" rel=\"noopener\"><span>Samarth Chandra<\/span><\/a><\/h4>\n<p><span>Spinor Research Labs, <\/span><span>India<\/span><\/p>\n<p>[\/et_pb_text][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Title&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p>ML for spying on business rivals and for other applications<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Abstract&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<div>Can you calculate information about the website traffic of your business rival ? For instance, number of visitors, their income distribution, professions, male\/female, geographical distribution, languages they speak, etc. Some foreign webapps already provide this information. The talk will discuss the technology for doing this.<\/div>\n<div>The later half of the talk will discuss automatic design of chemicals (medicines) using generative AI. The approach of Aspuru-Guzik&#8217;s lab will be discussed in detail. Later, you may contact us to join an online Journal Club we are starting on the topic.<\/div>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Bio&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<div class=\"row\">\n<div class=\"col-9 col-12-medium\">\n<div class=\"text-justify\">\n<div>Samarth Chandra is the founder, and Bookworm-in-Chief, of Indian private scientific research company, Spinor Research Labs. He is deeply interested in science. He enjoys reading (and teaching) research papers in widely different sub-fields of AI\/ML. He is also trained in Molecular Biology (lab and course work) as well as in Clinical Research and participated in development of surgically implantable devices at National Institutes of Health, USA. He is also interested in representation of tribal languages in the AI ecosystem.<\/div>\n<div>He received his PhD from TIFR, Mumbai and BTech from IIT Delhi.<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;7px|||||&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; background_enable_color=&#8221;off&#8221; custom_margin=&#8221;||14px|||&#8221; animation_direction=&#8221;bottom&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Important note to authors about the new ACM open access publishing model&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;#f7f7f7&#8243; background_enable_color=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p>ACM has introduced a new open access publishing model for the International Conference Proceedings Series (ICPS). Authors based at institutions that are not yet part of the <a href=\"https:\/\/libraries.acm.org\/acmopen\/open-participants\" target=\"_blank\" data-saferedirecturl=\"https:\/\/www.google.com\/url?q=https:\/\/libraries.acm.org\/acmopen\/open-participants&amp;source=gmail&amp;ust=1721965018718000&amp;usg=AOvVaw08K2raXgm5uGBK4NAjqzgG\" rel=\"noopener\">ACM Open program<\/a> and do not qualify for a waiver will be required to pay an article processing charge (APC) to publish their ICPS article in the ACM Digital Library. To determine whether or not an APC will be applicable to your article, please follow the detailed guidance here: <a href=\"https:\/\/www.acm.org\/publications\/icps\/author-guidance\" target=\"_blank\" data-saferedirecturl=\"https:\/\/www.google.com\/url?q=https:\/\/www.acm.org\/publications\/icps\/author-guidance&amp;source=gmail&amp;ust=1721965018718000&amp;usg=AOvVaw3yW8py6g90M47RyskouKNT\" rel=\"noopener\">https:\/\/www.acm.org\/<wbr \/>publications\/icps\/author-<wbr \/>guidance<\/a>.<\/p>\n<p>Further information may be found on the ACM website, as follows:<\/p>\n<p>Full details of the new ICPS publishing model: <a href=\"https:\/\/www.acm.org\/publications\/icps\/faq\" target=\"_blank\" data-saferedirecturl=\"https:\/\/www.google.com\/url?q=https:\/\/www.acm.org\/publications\/icps\/faq&amp;source=gmail&amp;ust=1721965018718000&amp;usg=AOvVaw1HKKXkd4ki_HfyAVLEGg8c\" rel=\"noopener\">https:\/\/www.acm.org\/<wbr \/>publications\/icps\/faq<\/a><br \/>Full details of the ACM Open program: <a href=\"https:\/\/www.acm.org\/publications\/openaccess\" target=\"_blank\" data-saferedirecturl=\"https:\/\/www.google.com\/url?q=https:\/\/www.acm.org\/publications\/openaccess&amp;source=gmail&amp;ust=1721965018718000&amp;usg=AOvVaw2yL9XalOCin6I5BV91zRH-\" rel=\"noopener\">https:\/\/www.acm.org\/<wbr \/>publications\/openaccess<\/a><\/p>\n<p>Please direct all questions about the new model to <a href=\"mailto:icps-info@acm.org\" target=\"_blank\" rel=\"noopener\">icps-info@acm.org<\/a>.<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_text _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><b>Style and Author Instructions<\/b><\/p>\n<p><span>Regular papers must not exceed 6 pages including bibliography.<br \/>Short papers must not exceed 4 pages including bibliography and will be presented as posters.<br \/>Only electronic submissions in PDF format using the ACM Latex template will be considered. Submissions will be handled through <\/span><a href=\"https:\/\/cmt3.research.microsoft.com\/AIMLSystems2024\/\"><span>https:\/\/cmt3.research.microsoft.com\/AIMLSystems2025\/<\/span><\/a><span>.<\/span><\/p>\n<p><b>\u00a0<\/b>We will accept all papers that meet the high quality and innovation levels required by the AI-ML Systems conference. All accepted papers will appear in the proceedings.<\/p>\n<p><b>\u00a0<\/b>Submission of papers to AI-ML Systems 2025 also carries with it the implied agreement that one or more of the listed authors will register for and attend the conference and present the paper. Papers not presented at the conference will not be included in the final program or in the digital proceedings.<\/p>\n<p>&nbsp;<\/p>\n<p>[\/et_pb_text][et_pb_accordion icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_direction=&#8221;bottom&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Reviewing process&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;#f4f4f4&#8243; background_enable_color=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<ul>\n<li><strong>Paper Format:<\/strong>\u00a0Please prepare your submission using a double-column format. This format allows for optimal readability and consistency throughout the proceedings.<\/li>\n<li><strong>Double-Blind Review:<\/strong> In order to maintain anonymity during the review process, please refrain from including author names and affiliations in the paper. This will help ensure an unbiased evaluation of your work.<\/li>\n<li><strong>Paper Upload:<\/strong> Kindly upload the PDF file of your paper. The maximum file size allowed for submission is 20MB.<\/li>\n<\/ul>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_direction=&#8221;bottom&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Submission format&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;#f4f4f4&#8243; background_enable_color=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span>Research papers must not exceed 6 pages, including any appendix, with an unlimited number of pages containing only bibliography. Only electronic submissions in PDF format using the ACM sigconf template (see\u00a0<\/span><a href=\"https:\/\/www.acm.org\/publications\/proceedings-template\">https:\/\/www.acm.org\/publications\/proceedings-template<\/a><span>) will be considered. The submissions will be through\u00a0<\/span><a href=\"https:\/\/cmt3.research.microsoft.com\/AIMLSystems2023\">https:\/\/cmt3.research.microsoft.com\/AIMLSystems2023<\/a><span>.<\/span><\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; fullwidth=&#8221;on&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; background_enable_color=&#8221;off&#8221; background_enable_image=&#8221;off&#8221; background_size=&#8221;custom&#8221; background_image_width=&#8221;50%&#8221; background_image_height=&#8221;50%&#8221; background_repeat=&#8221;repeat&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; header_4_font_size_tablet=&#8221;&#8221; header_4_font_size_phone=&#8221;22px&#8221; header_4_font_size_last_edited=&#8221;on|desktop&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h4 id=\"topics-of-interest\">Topics of Interest<\/h4>\n<p>The topics of interest include AI\/ML systems machine learning applications in all mature and emerging domains, as well as contributions to enabling algorithmic, infrastructure, and optimization methodologies to improve learning efficiency, scaling, and adoption\/deployment. The topics include, but are not limited to:<\/p>\n<p>&nbsp;<\/p>\n<p>[\/et_pb_text][et_pb_tabs active_tab_background_color=&#8221;#1c1b3a&#8221; inactive_tab_background_color=&#8221;#0b91c6&#8243; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; tab_text_color=&#8221;#FFFFFF&#8221; background_color=&#8221;rgba(0,0,0,0)&#8221; border_radii=&#8221;on|11px|11px|11px|11px&#8221; global_colors_info=&#8221;{%22gcid-f1f9244b-c8ab-43e1-95c3-c0bdf69ac7b5%22:%91%22active_tab_background_color%22%93}&#8221;][et_pb_tab title=&#8221;AI\/ML&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<div class=\"text-attention\">\n<ul>\n<li>Efficient model training, inference, and serving.<\/li>\n<li>Distributed and parallel learning algorithms<\/li>\n<li>Privacy and security for ML applications<\/li>\n<li>Testing, debugging, and monitoring of ML applications.<\/li>\n<li>Fairness, interpretability and explainability for ML applications<\/li>\n<li>Data preparation, feature selection, and feature extraction<\/li>\n<li>ML programming models and abstractions<\/li>\n<li>Programming languages for machine learning<\/li>\n<li>Visualization of data, models, and predictions<\/li>\n<li>Specialized hardware for machine learning<\/li>\n<li>Hardware-efficient ML methods<\/li>\n<li>Machine Learning for Systems<\/li>\n<li>Systems for Machine Learning<\/li>\n<li>Lessons learned from end-to-end production ML pipelines.<\/li>\n<li>Emerging practices such as AI-ML Ops<\/li>\n<li>Systems for Generative AI<\/li>\n<li>Generative AI use-cases<\/li>\n<li>\u00a0Benchmarking and performance studies for Generative AI tools<\/li>\n<\/ul>\n<\/div>\n<p>[\/et_pb_tab][\/et_pb_tabs][\/et_pb_column][\/et_pb_row][et_pb_row disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;7px|||||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><b>Style and Author Instructions<\/b><\/p>\n<p><span>Regular papers must not exceed 6 pages including bibliography.<br \/>Short papers must not exceed 4 pages including bibliography and will be presented as posters.<br \/>Only electronic submissions in PDF format using the ACM Latex template will be considered. Submissions will be handled through <\/span><a href=\"https:\/\/cmt3.research.microsoft.com\/AIMLSystems2024\/\"><span>https:\/\/cmt3.research.microsoft.com\/AIMLSystems2024\/<\/span><\/a><span>.<\/span><\/p>\n<p><b>\u00a0<\/b>We will accept all papers that meet the high quality and innovation levels required by the AI-ML Systems conference. All accepted papers will appear in the proceedings.<\/p>\n<p><b>\u00a0<\/b>Submission of papers to AI-ML Systems 2024 also carries with it the implied agreement that one or more of the listed authors will register for and attend the conference and present the paper. Papers not presented at the conference will not be included in the final program or in the digital proceedings.<\/p>\n<p>&nbsp;<\/p>\n<p>[\/et_pb_text][et_pb_accordion icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_direction=&#8221;bottom&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Reviewing process&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;#f4f4f4&#8243; background_enable_color=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<ul>\n<li><strong>Paper Format:<\/strong>\u00a0Please prepare your submission using a double-column format. This format allows for optimal readability and consistency throughout the proceedings.<\/li>\n<li><strong>Double-Blind Review:<\/strong> In order to maintain anonymity during the review process, please refrain from including author names and affiliations in the paper. This will help ensure an unbiased evaluation of your work.<\/li>\n<li><strong>Paper Upload:<\/strong> Kindly upload the PDF file of your paper. The maximum file size allowed for submission is 20MB.<\/li>\n<\/ul>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_direction=&#8221;bottom&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Submission format&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;#f4f4f4&#8243; background_enable_color=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span>Research papers must not exceed 6 pages, including any appendix, with an unlimited number of pages containing only bibliography. Only electronic submissions in PDF format using the ACM sigconf template (see\u00a0<\/span><a href=\"https:\/\/www.acm.org\/publications\/proceedings-template\">https:\/\/www.acm.org\/publications\/proceedings-template<\/a><span>) will be considered. The submissions will be through\u00a0<\/span><a href=\"https:\/\/cmt3.research.microsoft.com\/AIMLSystems2023\">https:\/\/cmt3.research.microsoft.com\/AIMLSystems2023<\/a><span>.<\/span><\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;7px|||||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; admin_label=&#8221;Features&#8221; module_id=&#8221;about&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;#dbdbdb&#8221; background_image=&#8221;https:\/\/www.aimlsystems.org\/2023\/wp-content\/uploads\/2023\/05\/rm380-10.jpg&#8221; background_blend=&#8221;overlay&#8221; custom_padding=&#8221;3.9%|||2px|false|false&#8221; use_background_color_gradient_phone=&#8221;on&#8221; background_color_gradient_stops_phone=&#8221;#001528 0%|rgba(255, 255, 255, 0) 10%|rgba(255,255,255,0) 70%|#0f0122 100%&#8221; locked=&#8221;off&#8221; collapsed=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;27px||43px|||&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h2>Accepted Industry Papers<\/h2>\n<p>[\/et_pb_text][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;1.\tCONRAD: Cognitive Intent Driven 5G Network Slice Planning and Design&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Ajay Kattepur (Ericsson)*; Swarup Kumar Mohalik (Ericsson); Ian Burdick (Ericsson); Marin Orlic (Ericsson); Leonid Mokrushin (Ericsson)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;2.\tUncovering Critical Products in Retail Baskets: A Predictive Modelling Approach to Increase Order Fulfilment&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Preeti Gopal (Walmart Global Tech)*; Sivaram Prasad Mudunuri (Walmart Global Tech); Sumit Dutta (Walmart Global Tech); Kamiya Motwani (Walmart Global Tech)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;3.\tMaximizing Success Rate of Payment Routing using Non-stationary Bandits&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Aayush Chaudhary (Dream11)*; Abhinav Rai (Dream11); Abhishek Gupta (The Ohio State University)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;\t4.\tt-RELOAD: A REinforcement Learning-based Recommendation for Outcome-driven Application&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Debanjan Sadhukhan (Games24x7 Pvt Ltd)*; Sachin Kumar (Games 24&#215;7 Pvt Ltd); Swarit Sankule (Games 24&#215;7 Pvt Ltd); Tridib Mukherjee (Games24x7)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;5.\tPhysics Guided Generative Learning for Domain Adaptable Data Synthesis : Progressive Fault Synthesization for Predictive Machine Maintenance&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Soma Bandyopadhyay (Tata Consultancy Services)*; Anish Datta (Tata Consultancy Services); Mudassir Ali Sayyed (Fraunhofer Enas); Tapas Chakravarty (Tata Consultancy Services); Arpan Pal (Tata Consultancy Services); Chirabrata Bhaumik (Tata Consultancy Services)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;6.\tSToRM: Smart ticket resolution steps recommendation in facilities management&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Rishav Gupta (Walmart Global Tech)*; Abhijeet Pandey (Walmart Global Tech); Abhishek Mishra (Walmart Global Tech)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;7.\tMetric Learning based Shelf Item Recognition on Images from Autonomous Robots&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Raghava Balusu (Walmart Global Tech); Lingfeng Zhang (Walmart Global Tech); Abhinav Pachauri (Walmart Global Tech); Han Zhang (Walmart Global Tech); Avinash Jade (Walmart Global Tech); Ashlin Ghosh (Walmart Global Tech); Siddhartha Chakraborty (Walmart Global Tech)*; Zhaoliang Duan (Walmart Global Tech)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;8.\tAdapting Open-Source LLMs for Contract Drafting and Analyzing Multi-Role vs. Single-Role Behavior of ChatGPT for Synthetic Data Generation&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Jaykumar Kasundra (Thomson Reuters)*; Shreyans Dhankhar (Thomson Reuters)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;9.\tNoisy Text Data: foible of popular Transformer based NLP models&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Kartikay Bagla (Chaos Genius); Shivam Gupta (Ninja Salary); Ankit Kumar (Clearfeed)*; Anuj Gupta (Clearfeed)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row disabled_on=&#8221;on|on|on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;27px||43px|||&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;1.\tAccelerating Causal Algorithms for Industrial-scale Data: A Distributed Computing Approach with Ray Framework&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Vishal Verma (Dream11)*; Vinod Reddy (Dream11)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;2.\tFENCE: Fairplay Ensuring Network Chain Entity for Real-Time Multiple ID Detection at Scale In Fantasy Sports&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Vishal Verma (Dream11)*; Akriti Upreti (Dream11); Kartavya Kothari (Dream11); Utkarsh Thukral (Dream11)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;3.\tVigil: Effective end-to-end monitoring for large-scale recommender systems at Glance&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Priyansh Saxena (Glance)*; Manisha R (Glance)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=&#8221;#f7f7f7&#8243; icon_color=&#8221;#0C71C3&#8243; use_icon_font_size=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||14px|||&#8221; animation_style=&#8221;slide&#8221; animation_direction=&#8221;bottom&#8221; animation_intensity_slide=&#8221;18%&#8221; border_radii=&#8221;on|30px|30px|30px|30px&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;4.\tMachine Learning Driven Performance Benchmarking for Energy Efficiency &#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Authors:<\/strong> Mandeep Singh (Walmart Global Tech)*; Viraj Patel (Walmart Global Tech); Ritik Kumar (Walmart Global Tech)<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Call for Papers Industry Track\u00a0<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"<!-- wp:paragraph -->\n<p>This is an example page. 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