{"id":237,"date":"2023-05-23T01:19:45","date_gmt":"2023-05-22T19:49:45","guid":{"rendered":"https:\/\/aiml.3it.in\/?page_id=237"},"modified":"2026-03-29T19:51:12","modified_gmt":"2026-03-29T14:21:12","slug":"callresearch","status":"publish","type":"page","link":"https:\/\/www.aimlsystems.org\/2026\/callresearch\/","title":{"rendered":"Call for Research Papers"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; 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;||24px|||&#8221; disabled=&#8221;on&#8221; collapsed=&#8221;on&#8221; 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global_colors_info=&#8221;{}&#8221;]<\/p>\n<h2>Call for Research Papers<\/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] -->\"AI INDIA 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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_image src=&#8221;https:\/\/www.aimlsystems.org\/2023\/wp-content\/uploads\/2023\/05\/ai-icon-01.png&#8221; title_text=&#8221;ai-icon-01&#8243; align=&#8221;center&#8221; disabled_on=&#8221;on|on|off&#8221; _builder_version=&#8221;4.21.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;-3px|||||&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_image][\/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 Research Papers<\/h1>\n<p><!-- [et_pb_line_break_holder] --><pee class=\"subtitle\">Exploring the interplay between AI\/ML and System Engineering<\/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 Research 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>We welcome submissions presenting original research that explores the interplay between AI\/ML and system engineering. Our focus includes (but is not limited to) the following pivotal topics:<\/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>Scalable &#038; Efficient AI-ML<\/h3>\n<p><!-- [et_pb_line_break_holder] --><pee>Focuses on agentic AI systems, AIOps efficiency, and distributed, federated, or decentralized learning. Topics include high-performance, robust, secure, and energy-efficient systems, as well as root-cause analysis and auto-scaling for deployments on-premise, in the cloud, or at the edge.<\/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>System Architectures<\/h3>\n<p><!-- [et_pb_line_break_holder] --><pee>Advanced hardware platforms (CPU, GPU, accelerators, edge devices) enabling improved cost, performance, and power efficiency; high-performance computing for AI workloads; custom hardware co-design; and data-intensive infrastructures.<\/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>Socio-Economic &#038; Decision Systems<\/h3>\n<p><!-- [et_pb_line_break_holder] --><pee>Vertical and domain-adapted foundation models, agentic workflows, and emerging AI techniques with significant system-level implications for decision making and socio-economic modeling.<\/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>Domain-Specific Solutions<\/h3>\n<p><!-- [et_pb_line_break_holder] --><pee>Advanced AI-ML methods for real-world systems including healthcare, education, governance, finance, communication, security, and computer vision. Emphasis is placed on scalability, robustness, and meeting strict operational constraints.<\/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>Safe &#038; Responsible AI<\/h3>\n<p><!-- [et_pb_line_break_holder] --><pee>Safe system design, detection of out-of-distribution data and hallucinations, and rigorous verification and testing of AI systems. Includes the analysis of risks and opportunities arising from real-world deployment.<\/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 content) + unlimited 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>Review:<\/strong> Double-blind review process.<\/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 TPC Co-Chairs<\/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>Filippo Maria Bianchi<\/h4>\n<p><!-- [et_pb_line_break_holder] --><pee>UiT, Norway<\/pee><!-- [et_pb_line_break_holder] --><a href=\"https:\/\/en.uit.no\/ansatte\/filippo.m.bianchi\" target=\"_blank\" class=\"link-btn\">Profile<\/a><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"glass-card text-chair\"><!-- [et_pb_line_break_holder] --><\/p>\n<h4>Fazel Keshtkar<\/h4>\n<p><!-- [et_pb_line_break_holder] --><pee>St John\u2019s University, USA<\/pee><!-- [et_pb_line_break_holder] --><a href=\"https:\/\/www.stjohns.edu\/academics\/faculty\/fazel-keshtkar\" target=\"_blank\" class=\"link-btn\">Profile<\/a><!-- [et_pb_line_break_holder] --><\/div>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"glass-card text-chair\"><!-- [et_pb_line_break_holder] --><\/p>\n<h4>Kalika Bali<\/h4>\n<p><!-- [et_pb_line_break_holder] --><pee>Microsoft, India<\/pee><!-- [et_pb_line_break_holder] --><a href=\"https:\/\/www.linkedin.com\/in\/kalika-bali-b72bab9\/?originalSubdomain=in\" 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 === *\/<!-- [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) 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Through this conference we plan to bring out and highlight the natural connections between these two fields and their application to socio-economic systems. Specifically we explore how immense strides in AI\/ML techniques are made possible through computational systems research (e.g., improvements in CPU\/GPU architectures, data-intensive infrastructure, and communications ), how the use of AI\/ML can help in the continuous and workload-driven design space exploration of computational systems (e.g., self-tuning databases, learning compiler optimisers, and learnable network systems ), and the use of AI\/ML in the design of socio-economic systems such as public healthcare, and security. The goal is to bring together these diverse communities and elicit connections between them.<\/span><\/p>\n<p class=\"text-justify pe-4\"><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; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; custom_button=&#8221;on&#8221; button_text_size=&#8221;15px&#8221; button_text_color=&#8221;gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68&#8243; 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; global_colors_info=&#8221;{%22gcid-5fa2e3a6-d98c-4022-811a-b5fb6fa40d68%22:%91%22button_text_color%22%93}&#8221; button_bg_color__hover_enabled=&#8221;on|hover&#8221; button_bg_color__hover=&#8221;&#8221; 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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_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; inactive_tab_background_color=&#8221;#0b91c6&#8243; _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,%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<div class=\"text-attention\">\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\"><span style=\"font-weight: 400;\">Paper submissions due: July 15, 2025, 11:59 pm AoE.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Author notifications: <span style=\"text-decoration: line-through;\">Aug 10, 2025<\/span>, Aug 20, 2025, 11:59 pm AoE.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Camera ready deadline: Aug 31, 2025, 11:59 pm AoE.<\/span><\/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<\/div>\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; custom_margin=&#8221;4px|||||&#8221; border_radii=&#8221;on|11px|11px|11px|11px&#8221; locked=&#8221;off&#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 style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.tcs.com\/insights\/authors\/rekha-singhal\" target=\"_blank\" rel=\"noopener\"><span style=\"text-decoration: underline;\">Rekha Singhal<\/span><\/a>, TCS Research, USA<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/docenti.unisi.it\/it\/melacci\" target=\"_blank\" rel=\"noopener\"><span style=\"text-decoration: underline;\">Stefano Melacci<\/span><\/a>, University of Siena, Italy<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.neeldhara.com\/\" target=\"_blank\" rel=\"noopener\"><span style=\"text-decoration: underline;\">Neeldhara Misra<\/span><\/a>, IIT Gandhinagar, India<\/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_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_color=&#8221;#ffffff&#8221; background_image=&#8221;https:\/\/www.aimlsystems.org\/2023\/wp-content\/uploads\/2023\/05\/grid-bg-1.png&#8221; background_size=&#8221;custom&#8221; background_image_width=&#8221;50%&#8221; background_image_height=&#8221;50%&#8221; background_repeat=&#8221;repeat&#8221; background_blend=&#8221;darken&#8221; background_last_edited=&#8221;on|phone&#8221; background_enable_image_phone=&#8221;off&#8221; disabled=&#8221;on&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row disabled_on=&#8221;off|off|off&#8221; _builder_version=&#8221;4.23.4&#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;4.21.0&#8243; _module_preset=&#8221;default&#8221; text_text_color=&#8221;#000000&#8243; header_4_text_color=&#8221;#000000&#8243; custom_margin=&#8221;||14px|||&#8221; header_4_font_size_tablet=&#8221;&#8221; header_4_font_size_phone=&#8221;20px&#8221; header_4_font_size_last_edited=&#8221;on|phone&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h4 id=\"topics-of-interest\">Topics of Interest<\/h4>\n<p>The areas of interest are broadly categorized into the following three streams: (<span>including but not limited to)<\/span><\/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;Systems for 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 style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">CPU\/GPU architectures for AI\/ML<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Specialized\/Embedded hardware for AI\/ML workloads<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Data intensive systems for efficient and distributed training<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Challenges in production deployment of AI\/ML systems<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI\/ML programming models, languages, and abstractions<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI\/ML compilers and runtime<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Efficient systems for data preparation and processing<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Systems for visualization of data, models, and predictions<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Testing, debugging, and monitoring of AI\/ML applications<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Cloud-computing for machine and deep learning<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Machine and deep learning \u201cas-a-service\u201d<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Tiny Machine Learning<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Embedded and Edge AI<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Pervasive AI<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Federated, distributed and parallel learning algorithms<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">MLOps (data collection, monitoring and re-training)<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Efficient inference for deep learning models<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Logging mechanisms for deep learning models<\/span><\/li>\n<\/ul>\n<\/div>\n<p>[\/et_pb_tab][et_pb_tab title=&#8221;AI\/ML for Systems&#8221; _builder_version=&#8221;4.23.4&#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;\">AI\/ML for VLSI and architecture design<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI\/ML in compiler optimization<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI\/ML in data management \u2013 including database optimizations, virtualization, etc.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI\/ML for networks \u2013 design of networks, load modeling, etc.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI\/ML for power management \u2013 green computing, power models, etc.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI\/ML for Cloud Computing<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI\/ML for IOT networks<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI\/ML for HPC<\/span><\/li>\n<\/ul>\n<p>[\/et_pb_tab][et_pb_tab title=&#8221;AI\/ML for Socio-Economic Systems Design&#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 style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Deep Learning Architecture and applications<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Computer Vision and Image processing<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Natural language processing and understanding<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Speech signal processing and Socio-Economic Systems<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI\/ML in cyber-physical systems<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Privacy, Security, and Robustness in AI\/ML systems<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Ethics in AI\/ML systems<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Fairness, Transparency, Interpretability and Explainability in AI\/ML\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Sustainable AI\/ML<\/span><\/li>\n<\/ul>\n<\/div>\n<p>[\/et_pb_tab][et_pb_tab title=&#8221;Domain-Specific AI\/ML&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<ul>\n<li>AI for Healthcare<\/li>\n<li>AI for Resource Allocation, Econometrics, and Finance<\/li>\n<li>AI for Energy<\/li>\n<li>AI for Transportation and Built Environment<\/li>\n<li>AI for Climate Change &amp; Sustainability<\/li>\n<li>AI for Education<\/li>\n<li>AI for Art, Music, and Sound<\/li>\n<\/ul>\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;4.21.0&#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_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; 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_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; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Style and Author Instructions&#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<ul>\n<li><span style=\"font-weight: 400;\">Research papers must not exceed 8 pages, excluding appendix, acknowledgment and bibliography. <\/span><span style=\"font-weight: 400;\">Only electronic submissions in PDF format using the ACM sigconf template (see <a href=\"https:\/\/www.overleaf.com\/gallery\/tagged\/acm-official\">https:\/\/www.overleaf.com\/gallery\/tagged\/acm-official<\/a>) will be considered for authors using Latex. For authors writing in Microsoft Word, MS Word submissions should use the official Interim Template provided by ACM <a href=\"https:\/\/www.acm.org\/binaries\/content\/assets\/publications\/word_style\/interim-template-style\/interim-layout.docx\">here<\/a>. Submissions will be handled through <\/span><a href=\"https:\/\/cmt3.research.microsoft.com\/AIMLSystems2024\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">https:\/\/cmt3.research.microsoft.com\/AIMLSystems2025\/<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><span style=\"font-weight: 400;\">Papers can be submitted under any of the three main topics listed above. Authors are required to make a primary topic selection, with optional secondary topics for each paper. Number of papers accepted under each topic is not capped. We will accept all papers that meet the high quality and innovation levels required by the AI-ML Systems conference. All papers that are accepted will appear in the proceedings.<\/span><span style=\"font-weight: 400;\">All accepted papers will be presented as posters at AI-ML Systems 2025, but a selected subset of them will be given a \u201cconventional\u201d (oral) presentation slot during the conference. However, all accepted papers will be treated equally in the conference proceedings, which are the persistent, archival record of the conference.<\/span><\/li>\n<\/ul>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][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; body_text_color=&#8221;#000000&#8243; background_color=&#8221;rgba(0,0,0,0)&#8221; custom_margin=&#8221;31px|||||&#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;Ethics&#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><span style=\"font-weight: 400;\"><strong>Plagiarism Policy<\/strong>: Submission of papers to AIMLSystems 2025 carries with it the implied agreement that the paper represents original work. We will follow the ACM Policy on Plagiarism, Misrepresentation, and Falsification \u2013 see <\/span><a href=\"https:\/\/www.acm.org\/publications\/policies\/plagiarism-overview\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">https:\/\/www.acm.org\/publications\/policies\/plagiarism-overview<\/span><\/a><span style=\"font-weight: 400;\">. All submitted papers will be subjected to a \u201csimilarity test\u201d. Papers achieving a high similarity score will be examined and those that are deemed unacceptable will be rejected without a formal review. We also expect to report such unacceptable submissions to the superiors of each of the authors.<\/span>\n<p><span style=\"font-weight: 400;\">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. Therefore, authors are strongly encouraged to plan accordingly before deciding to submit a paper.<\/span><\/p>\n<\/li>\n<\/ul>\n<\/div>\n<p>[\/et_pb_tab][et_pb_tab title=&#8221;Conflicts of Interest&#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><span style=\"font-weight: 400;\">During submission of a research paper, the submission site will request information about Conflicts of Interest (COI) of the paper\u2019s authors with program committee (PC) members. It is the full responsibility of all authors of a paper to identify all (and only) PC members with potential COIs as per the definition provided on the submission site. Papers with incorrect or incomplete COI information as of the submission closing time are subject to immediate rejection.<\/span>\n<p><span style=\"font-weight: 400;\">Definition of Conflict of Interest (COI): A paper author has a COI with a PC member when and only when one or more of the following conditions hold:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The PC member is a co-author of the paper, or has been a co-author of a paper in the last 3 years or 4 (or more) papers in the last 10 years.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The PC member has been a co-worker in the same company or university within the past two years.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The PC member has been a collaborator within the past two years.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The PC member is or was the author\u2019s primary thesis advisor, no matter how long ago.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The author is or was the PC member\u2019s primary thesis advisor, no matter how long ago.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The PC member is a relative or close personal friend of the author.<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/div>\n<p>[\/et_pb_tab][et_pb_tab title=&#8221;Review Process&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Paper Format:<\/b><span style=\"font-weight: 400;\"> Please prepare your submission using a double-column format. This format allows for optimal readability and consistency throughout the proceedings.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Double-Blind Review:<\/b><span style=\"font-weight: 400;\"> 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.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Paper Upload:<\/b><span style=\"font-weight: 400;\"> Kindly upload the PDF file of your paper. The maximum file size allowed for submission is 20MB.<\/span><\/li>\n<\/ul>\n<p>[\/et_pb_tab][et_pb_tab title=&#8221;Dual Submission Policy&#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><span style=\"font-weight: 400;\">A paper submitted to AI-ML Systems can not be under review at any other conference or journal during the entire time it is considered for review at AI-ML Systems, and it must be substantially different from any previously published work or any work under review. After submission and during the review period, submissions to AI-ML Systems must not be submitted to other conferences \/ journals for consideration. However, authors may publish at non-archival venues, such as workshops without proceedings, or as technical reports (including arXiv).<\/span><\/li>\n<\/ul>\n<\/div>\n<p>[\/et_pb_tab][et_pb_tab title=&#8221;Mode of Conference&#8221; _builder_version=&#8221;4.23.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p>The conference is planned to be an in-person event. At least one author of each accepted paper is expected to attend and present at the conference in person.<\/p>\n<p>[\/et_pb_tab][\/et_pb_tabs][\/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%||||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 Research 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.\tLiBERTy: A Novel Model for Natural Language Understanding &#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> Onkar Susladkar (IIT Roorkee); Gayatri s Deshmukh (Vishwakarma Institute of Information Technology); Sparsh Mittal (IIT Roorkee)*; Sai Chandra Teja R (Independent Researcher); Rekha Singhal (TCS)<\/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.\tDesign-Space Exploration of Systolic Array for Edge Inferencing Applications&#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> Prashanth H C (International Institute of Information Technology Bangalore)*; Yash Dharmesh Mogal (International Institute of Information Technology Bangalore); Madhav Rao (International Institute of information Technology, Bangalore)<\/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.\tTinyML-Driven On-Device Personalized Human Activity Recognition and Auto-Deployment to Smart Bands&#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> Bidyut Saha (Indian Institute of Technology Kharagpur)*; Riya Samanta (Indian Institute of Technology, Kharagpur); Soumya Kanti Ghosh (Indian Institute of Technology Kharagpur, India); Ram Babu Roy (Indian Institute of Technology Kharagpur )<\/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.\tManaged Bidirectional Charging of Electric Fleets with Arbitrage&#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> Kshitij Garg (TCS Research); Prasant Misra (TCS Research)*; Yogesh Bichpuriya (Industry Researcher); Arunchandar Vasan (TCS Research)<\/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.\tSoil Moisture Prediction Using Deep Learning on Hyperspectral Data&#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> Sourav Seal (Delhi Technological University)*; Divyashikha Sethia (Delhi Technological 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;6.\tInvestigating the changes in BOLD responses during viewing of images with varied complexity: An fMRI time-series based analysis on human vision&#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> Naveen Kanigiri (International Institute of Information Technology Bangalore); Manohar Suggula (International Institute of Information Technology Bangalore); Debanjali Bhattacharya (International Institute of Information Technology Bangalore)*; Neelam Sinha (International Institute of Information Technology)<\/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.\tPredicting Depth of Anesthesia using EEG Signals and Deep Convolution Network&#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> NEERAJ KUMAR SHARMA (Ram Lal Anand College, University of Delhi)*; Sakeena Shahid (Sri Guru Tegh Bahadur Khalsa College, University of Delhi); Subodh Kumar (Department of Computer Science, University of Delhi); Sanjeev Sharma (Department of Anesthesia, A.B.V.I.M.S &amp; R.M.L Hospital); Rakesh Kumar Gupta (Ram Lal Anand College, University of Delhi); Naveen Kumar (University of Delhi)<\/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.\tSecureFrameNet:A rich computing capable secure framework for deploying neural network models on edge protected system.&#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> Renju C Nair (International Institute of information Technology, Bangalore)*; Madhav Rao (International Institute of information Technology, Bangalore); Muralidhara V N (IIIT Bangalore)<\/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.\tUnveiling User Influence: An Adaptive Algorithm for Socialness Estimation through User-Reply Semantics&#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> Vikram Singh (Computer Engineering Dept.,National Institute of Technology, Kurukshetra, Haryana-136119, India)*; Devanand Gamboir (Computer Engineering Dept.,National Institute of Technology, Kurukshetra, Haryana-136119, India )<\/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;10. CAMOT: Content Aware Multi Object Tracking&#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> Ratul Kishore Saha (Tata Consultancy Services)*; Rekha Singhal (TCS); Manoj Nambiar (TCS)<\/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;11.\tTIFeD: a Tiny Integer-based Federated learning algorithm with Direct feedback alignment&#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> Luca Colombo (Politecnico di Milano)*; Alessandro Falcetta (Politecnico di Milano); Manuel Roveri (Politecnico di Milano)<\/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;12.\tYOLOv7-DocInstSeg: Efficient Instance Segmentation Framework for Document Analysis and Recognition&#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> Vamshi Krishna Kancharla (IIIT Bangalore college)*; Neelam Sinha (International Institute of Information Technology)<\/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;13.\tPerceptually-Inspired Local Source Normalization for Adversarial Robustness&#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> Archana Ramachandran (Indian Institute of Technology Hyderabad)*; Sumohana S. Channappayya (IIT Hyderabad)<\/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;14.\tLeveraging Uncertainty for Credit Risk Estimation and Reliable Predictions in lending decision making&#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> Akash Mondal (American Express)*; Saradindu Kar (American Express); Akash Mondal (American Express)<\/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;15.\tExploring Causality Aware Data Synthesis&#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)*; Sudeshna Sarkar (IIT Kharagpur)<\/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;16.\tImproved Sequence Predictions using Knowledge Graph Embedding for Large Language 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> Rabina Khatun (Dr. B.C.Roy Engineering College); Nilanjan Sinhababu (Indian Institute of Technology Kharagpur)*<\/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;17.\tSplitEE: Early Exit in Deep Neural Networks  with Split Computing&#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> Divya Jyoti Bajpai (Indian Institute of Technology Bombay); Vivek Kumar Trivedi (Indian Institute of Technology Bombay ); Sohan L Yadav (Indian Institute of Technology, Bombay); Manjesh Kumar Hanawal (IIT Bombay)*<\/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;18.\tBinary Convolutional Neural Network for Efficient Gesture Recognition at Edge&#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> Jayeeta Mondal (TCS Research); Swarnava Dey (TCS Research, Tata Consultancy Services Ltd.); Arijit Mukherjee (TCS Research)*<\/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;19.\tDesigning a Bare Minimum Face Recognition Architecture for Bare Metal Edge Devices: An Experience Report&#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> Swarnava Dey (TCS Research, Tata Consultancy Services Ltd.)*<\/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;20.\tMobileASR: A resource-aware on-device learning framework for user voice personalization applications on mobile phones&#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> Zitha Sasindran (Indian Institute of Science)*; Harsha Yelchuri (Information Science Engineering RV College of Engineering Bengaluru, India); Prabhakar Venkata Tamma (Electronics Systems Engg); Pooja Rao (IISc)<\/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;21.\tModel Uncertainty based Active Learning on Tabular Data using Boosted Trees&#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> Sharath M Shankaranarayana (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;22.\tHetero-Rec++: Modelling-based Robust and Optimal Deployment of Embeddings Recommendations&#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> Ashwin Krishnan (TCS Research)*; Manoj Nambiar (TCS); Rekha Singhal (TCS)<\/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 Research Papers<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"<!-- wp:paragraph -->\n<p>This is an example page. It's different from a blog post because it will stay in one place and will show up in your site navigation (in most themes). Most people start with an About page that introduces them to potential site visitors. It might say something like this:<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:quote -->\n<blockquote class=\"wp-block-quote\"><!-- wp:paragraph -->\n<p>Hi there! I'm a bike messenger by day, aspiring actor by night, and this is my website. I live in Los Angeles, have a great dog named Jack, and I like pi\u00f1a coladas. (And gettin' caught in the rain.)<\/p>\n<!-- \/wp:paragraph --><\/blockquote>\n<!-- \/wp:quote -->\n\n<!-- wp:paragraph -->\n<p>...or something like this:<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:quote -->\n<blockquote class=\"wp-block-quote\"><!-- wp:paragraph -->\n<p>The XYZ Doohickey Company was founded in 1971, and has been providing quality doohickeys to the public ever since. Located in Gotham City, XYZ employs over 2,000 people and does all kinds of awesome things for the Gotham community.<\/p>\n<!-- \/wp:paragraph --><\/blockquote>\n<!-- \/wp:quote -->\n\n<!-- wp:paragraph -->\n<p>As a new WordPress user, you should go to <a href=\"https:\/\/www.aimlsystems.org\/2023\/wp-admin\/\">your dashboard<\/a> to delete this page and create new pages for your content. Have fun!<\/p>\n<!-- \/wp:paragraph -->","_et_gb_content_width":"","footnotes":""},"class_list":["post-237","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.aimlsystems.org\/2026\/wp-json\/wp\/v2\/pages\/237","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.aimlsystems.org\/2026\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.aimlsystems.org\/2026\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.aimlsystems.org\/2026\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.aimlsystems.org\/2026\/wp-json\/wp\/v2\/comments?post=237"}],"version-history":[{"count":129,"href":"https:\/\/www.aimlsystems.org\/2026\/wp-json\/wp\/v2\/pages\/237\/revisions"}],"predecessor-version":[{"id":8030,"href":"https:\/\/www.aimlsystems.org\/2026\/wp-json\/wp\/v2\/pages\/237\/revisions\/8030"}],"wp:attachment":[{"href":"https:\/\/www.aimlsystems.org\/2026\/wp-json\/wp\/v2\/media?parent=237"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}