{"id":5412,"date":"2024-08-20T11:57:30","date_gmt":"2024-08-20T06:27:30","guid":{"rendered":"https:\/\/www.aimlsystems.org\/2024\/?page_id=5412"},"modified":"2024-10-16T21:30:27","modified_gmt":"2024-10-16T16:00:27","slug":"accepted-papers","status":"publish","type":"page","link":"https:\/\/www.aimlsystems.org\/2024\/accepted-papers\/","title":{"rendered":"Accepted Papers"},"content":{"rendered":"

[et_pb_section fb_built=”1″ admin_label=”Header” _builder_version=”4.19.5″ _module_preset=”default” background_color=”gcid-1bcf785a-50e1-437b-b09f-65567babc1de” background_image=”https:\/\/www.aimlsystems.org\/2023\/wp-content\/uploads\/2023\/05\/grid-bg-2.png” background_size=”initial” background_position=”bottom_center” background_repeat=”repeat” custom_padding=”||0px|||” collapsed=”on” global_colors_info=”{%22gcid-1bcf785a-50e1-437b-b09f-65567babc1de%22:%91%22background_color%22%93}”][et_pb_row _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.25.1″ _module_preset=”7f63b212-a10a-4d30-afa2-e478a747ca88″ custom_margin=”||10px||false|false” header_2_font_size_phone=”33px” global_colors_info=”{}”]<\/p>\n

Accepted Papers<\/span><\/h2>\n

[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Features” module_id=”about” _builder_version=”4.21.0″ _module_preset=”default” background_color=”#dbdbdb” background_image=”https:\/\/www.aimlsystems.org\/2023\/wp-content\/uploads\/2023\/05\/rm380-10.jpg” background_blend=”overlay” custom_padding=”3.9%||||false|false” use_background_color_gradient_phone=”on” background_color_gradient_stops_phone=”#001528 0%|rgba(255, 255, 255, 0) 10%|rgba(255,255,255,0) 70%|#0f0122 100%” collapsed=”on” global_colors_info=”{}”][et_pb_row _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_heading title=”Research Track” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_heading][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.21.0″ _module_preset=”default” custom_padding=”27px||29px|||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”1. KANICE: Kolmogorov-Arnold Networks with Interactive Convolutional Elements” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Md Meftahul Ferdaus (University of New Orleans)*; Mahdi Abdelguerfi (University of New Orleans); Elias Ioup (Center for Geospatial Sciences, Naval Research Laboratory, Stennis Space Center); David Dobson (Center for Geospatial Sciences, Naval Research Laboratory, Stennis Space Center); Kendall N. Niles (US Army Corps of Engineers, Engineer Research and Development Center); Ken Pathak (US Army Corps of Engineers, Engineer Research and Development Center); Steven Sloan (US Army Corps of Engineers, Engineer Research and Development Center)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”2.\tFederated On-Device Learning of Integer-Based Convolutional Neural Networks” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Luca Colombo (Politecnico di Milano)*<\/p>\n

 <\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”3.\tILAEDA: An Imitation Learning Based Approach for Automatic Exploratory Data Analysis” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Abhijit Manatkar (IBM Research)*; Devarsh Patel (IISER Pune); Hima Patel (IBM Research); Naresh Manwani (International Institute of Information Technology, Hyderabad)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”\t4.\tSparse Reservoir Topologies for Physical Implementations of Random Oscillators Networks” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Andrea Cossu (University of Pisa)*; Andrea Ceni (University of Pisa); Davide Bacciu (Univeristy of Pisa); Claudio Gallicchio (University of Pisa)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”5.\tInversion of Satellite Measurements of CO2 Concentrations using Deep Learning” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Garvit Agarwal (TCS Research)*; Shailesh S Deshpande (TRDDC)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”6.\tSelective Graph Convolutional Network for Efficient Routing” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Nikita Karthikeyan (Indiana University, Bloomington); Hayagreev Jeyandran (Vidyashilp Academy); Rohit Verma (Intel Labs)*; Rajeev Shorey (IIIT Surat)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”7.\tTowards Forecasting Bus Arrival Thorough A Model Based On GNN+LSTM Using GTFS and Real-time Data” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Pedro P Lopes (PUC Minas); Gerlando Gramaglia (Universit\u00e0 di Pisa); Davide Bacciu (Univeristy of Pisa); Humberto T Marques-Neto (PUC Minas)*<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”8.\tQuantifying Cryptocurrency Unpredictability: A Comprehensive Study of Complexity and Forecasting” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Francesco Puoti (Politecnico di Milano)*; Fabrizio Pittorino (Politecnico di Milano); Manuel Roveri (Politecnico di Milano)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”9.\tGPU Acceleration for Markov Chain Monte Carlo sampling” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Jiarui Li (Tulane University); Ramgopal R Mettu (Tulane University)*<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”10. TinySV: Speaker Verification in TinyML with On-device Learning” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Massimo Pavan (POLITECNICO DI MILANO)*; Gioele Mombelli (Politecnico di Milano); Francesco Sinacori (Infineon Technologies Italia s.r.l); Manuel Roveri (Politecnico di Milano)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”11.\tVETT: VectorDB-Enabled Transfer-Learning for Time-Series Forecasting” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Alessandro Falcetta (Politecnico di Milano)*; Giulio Cristofaro (Dhiria S.r.l.); Lorenzo Epifani (Politecnico di Milano); Manuel Roveri (Politecnico di Milano)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”12.\tERFC: Happy Customers with Emotion Recognition and Forecasting in Conversation in Call Centers” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors: <\/strong>Aditi Debsharma (Accenture)*; Bhushan Jagyasi (Accenture); Surajit Sen (Accenture); Priyanka Pandey (Accenture); Devicharith Dovari (Accenture); Yuvaraj V. C (Accenture); Rosalin Parida (Accenture); Gopali Contractor (Accenture)

<\/strong><\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”13.\tSelf Supervised LLM Customizer(SSLC): Customizing LLMs on Unlabeled Data to Enhance Contextual Question Answering” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors: <\/strong>Raveendra R Hegde (Amazon)*; Saurabh Sharma (Amazon India)<\/p>\n<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”14.\tORCHID \u2013 Offline RL for Control of HVAC in Buildings using Historical and Low-Fidelity Simulation Data” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Richa Verma (TCS Research)*; Srikar Babu Gadipudi (Indian Institute of Technology, Madras); Srinarayana Nagarathinam (Tata Consultancy Services Ltd); Harshad Khadilkar (Tata Consultancy Services Ltd.)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”15.\tTinyML-Powered Gesture Wizardry: Low-Cost, Low-Power Two-Stage CNN for Static Hand Gesture Classification on MCU in Appliance Control” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

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, India)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”16.\tTrans-ARG: Predicting Antibiotic Resistance Genes with a Transformer-Based Model and Pretrained Protein Language Model” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Mohd Manzar Abbas (Louisiana State University)*; Amit Ranjan (Louisiana State University); Aixin Hou (Louisiana State University); Supratik Mukhopadhyay (Louisiana State University)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”17.\tKG-DTA: A knowledge graph-based meta-path learning framework to predict drug-target binding affinity” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Amit Ranjan (Louisiana State University)*; Adam Bess (Louisiana State University); Md Saiful Islam Sajol (Louisiana State University); Magesh Rajasekaran (Louisiana State University); Chris Alvin (Louisiana State University); Supratik Mukhopadhyay (Louisiana State University)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”18.\tTab2Graph: Transforming Heterogeneous Tables as Graphs” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Rajat Singh (IIT Delhi)*; Raajita Bhamidipaty (IIT Delhi); Anjali Sharma (indian institute of technology Delhi); Srikanta Bedathur (IIT Delhi)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”19.\tVisual Perception Transformer: Robust image understanding on unseen transformations across wide-ranging dataset sizes” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Renju C Nair (International Institute of information Technology, Bangalore)*; Ashish Gatreddi (International Institute of Information Technology, Bangalore); Madhav Rao (International Institute of information Technology, Bangalore); Muralidhara V N (IIIT Bangalore)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”20.\tBudgetMLAgent: A Cost-Effective LLM Multi-Agent system for Automating Machine Learning Tasks” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Shubham Gandhi (TCS Research); Manasi Patwardhan (TCS Research)*; Lovekesh Vig (TCS Research); Gautam Shroff (IIIT Delhi)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_heading title=”Industry Track” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_heading][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.21.0″ _module_preset=”default” custom_padding=”27px||29px|||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”1.\tEfficient and verifiable responses using Retrieval Augmented Generation (RAG)” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]Authors:\u00a0<\/strong>Henry Liang (Vail Systems), Yu Zhou (Vail Systems), Vijay K. Gurbani (Vail Systems).[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”2.\tAssessing the Impact of Upselling in Online Fantasy Sports” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Aayush Chaudhary<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”\t4.\tAI Enhanced Ticket Management System for optimized Support” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:<\/strong> Shubham Jain (Hughes Systique)*; Amit Gupta (Hughes Systique); Kumari Neha (Hughes Systique)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” hover_enabled=”0″ border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}” sticky_enabled=”0″][et_pb_accordion_item title=”5.\tAggregated Knowledge Model: Enhancing Domain-Specific QA with Fine-Tuned and Retrieval-Augmented Generation Models” open=”on” _builder_version=”4.25.1″ _module_preset=”default” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n

Authors:<\/strong> Fengchen Liu (Lawrence Berkeley National Laboratory)*; Fengchen Liu (University of California, Berkeley); Jordan Jung (Lawrence Berkeley National Laboratory); Wei Feinstein (Lawrence Berkeley National Laboratory); Jeff D’Ambrogia (Lawrence Berkeley National Laboratory); Gary Jung (Lawrence Berkeley National Laboratory)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” hover_enabled=”0″ border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}” sticky_enabled=”0″][et_pb_accordion_item title=”6.\tRemote Attestation and Secure AI in Systems-on-Chip\/Systems-in-Package” open=”on” _builder_version=”4.25.1″ _module_preset=”default” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n

Authors:<\/strong> Giridhar Mandyam (Mediatek)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_heading title=”Demo Track” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_heading][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.21.0″ _module_preset=”default” custom_padding=”27px||29px|||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”1.\tTASCA++ : A multi-agentic tool to scalably accelerate ML pipelines” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:\u00a0<\/strong>Bibek Paul (Chennai Mathematical Institute); ARCHISMAN BHOWMICK (TATA CONSULTANCY SERVICES)*; Mayank Mishra (TCS); Sarthak Gupta (IIIT Nagpur); Rekha Singhal (TCS) <\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”2.\tLeafSense: A Portable, Low-Cost, Low-Power Plant Disease Diagnostic Device Using TinyML” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Authors:\u00a0<\/strong>Riya Samanta (Indian Institute of Technology, Kharagpur)*; Bidyut Saha (Indian Institute of Technology Kharagpur); Soumya Kanti Ghosh (Indian Institute of Technology Kharagpur, India) <\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Workshop-GenAI<\/h2>\n

[\/et_pb_text][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”1. Methodology for Quality Assurance Testing of LLM-based Multi-Agent Systems” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Isha Shamim (Tata Consultancy Services Limited)*; Rekha Singhal (TCS)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”2. Bridging the Gap: Synthetic Data Augmentation through Inversion and Distribution Matching for Few-shot Learning” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Yunsung Chung (Tulane University)*; Janet Wang (Tulane University); Jihun Hamm (Tulane University)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_accordion open_toggle_background_color=”#f7f7f7″ icon_color=”#0C71C3″ use_icon_font_size=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||14px|||” animation_style=”slide” animation_direction=”bottom” animation_intensity_slide=”18%” border_radii=”on|30px|30px|30px|30px” global_colors_info=”{}”][et_pb_accordion_item title=”3. Question-Answering System in Computer Science” open=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

Harshit Verma (BITS Pilani Hyderabad); M Bhargav (BITS Pilani Hyderabad); Ritvik – (BITS Pilani Hyderabad); Chetana Dr Gavankar (BITS Pilani)*; Prajna Devi Upadhyay (BITS Pilani Hyderabad)<\/p>\n

[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"

Accepted PapersAuthors: Md Meftahul Ferdaus (University of New Orleans)*; Mahdi Abdelguerfi (University of New Orleans); Elias Ioup (Center for Geospatial Sciences, Naval Research Laboratory, Stennis Space Center); David Dobson (Center for Geospatial Sciences, Naval Research Laboratory, Stennis Space Center); Kendall N. Niles (US Army Corps of Engineers, Engineer Research and Development Center); Ken Pathak (US […]<\/p>\n","protected":false},"author":7,"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":"\n

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\n\n\n

\n

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<\/blockquote>\n\n\n\n

...or something like this:<\/p>\n\n\n\n

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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<\/blockquote>\n\n\n\n

As a new WordPress user, you should go to your dashboard<\/a> to delete this page and create new pages for your content. Have fun!<\/p>\n","_et_gb_content_width":"","footnotes":""},"class_list":["post-5412","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.aimlsystems.org\/2024\/wp-json\/wp\/v2\/pages\/5412","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.aimlsystems.org\/2024\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.aimlsystems.org\/2024\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.aimlsystems.org\/2024\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/www.aimlsystems.org\/2024\/wp-json\/wp\/v2\/comments?post=5412"}],"version-history":[{"count":26,"href":"https:\/\/www.aimlsystems.org\/2024\/wp-json\/wp\/v2\/pages\/5412\/revisions"}],"predecessor-version":[{"id":5918,"href":"https:\/\/www.aimlsystems.org\/2024\/wp-json\/wp\/v2\/pages\/5412\/revisions\/5918"}],"wp:attachment":[{"href":"https:\/\/www.aimlsystems.org\/2024\/wp-json\/wp\/v2\/media?parent=5412"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}