Accepted Papers
Research Track
1. KANICE: Kolmogorov-Arnold Networks with Interactive Convolutional Elements
Authors: 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)
2. Federated On-Device Learning of Integer-Based Convolutional Neural Networks
Authors: Luca Colombo (Politecnico di Milano)*
3. ILAEDA: An Imitation Learning Based Approach for Automatic Exploratory Data Analysis
Authors: Abhijit Manatkar (IBM Research)*; Devarsh Patel (IISER Pune); Hima Patel (IBM Research); Naresh Manwani (International Institute of Information Technology, Hyderabad)
4. Sparse Reservoir Topologies for Physical Implementations of Random Oscillators Networks
Authors: Andrea Cossu (University of Pisa)*; Andrea Ceni (University of Pisa); Davide Bacciu (Univeristy of Pisa); Claudio Gallicchio (University of Pisa)
5. Inversion of Satellite Measurements of CO2 Concentrations using Deep Learning
Authors: Garvit Agarwal (TCS Research)*; Shailesh S Deshpande (TRDDC)
6. Selective Graph Convolutional Network for Efficient Routing
Authors: Nikita Karthikeyan (Indiana University, Bloomington); Hayagreev Jeyandran (Vidyashilp Academy); Rohit Verma (Intel Labs)*; Rajeev Shorey (IIIT Surat)
7. Towards Forecasting Bus Arrival Thorough A Model Based On GNN+LSTM Using GTFS and Real-time Data
Authors: Pedro P Lopes (PUC Minas); Gerlando Gramaglia (Università di Pisa); Davide Bacciu (Univeristy of Pisa); Humberto T Marques-Neto (PUC Minas)*
8. Quantifying Cryptocurrency Unpredictability: A Comprehensive Study of Complexity and Forecasting
Authors: Francesco Puoti (Politecnico di Milano)*; Fabrizio Pittorino (Politecnico di Milano); Manuel Roveri (Politecnico di Milano)
9. GPU Acceleration for Markov Chain Monte Carlo sampling
Authors: Jiarui Li (Tulane University); Ramgopal R Mettu (Tulane University)*
10. TinySV: Speaker Verification in TinyML with On-device Learning
Authors: Massimo Pavan (POLITECNICO DI MILANO)*; Gioele Mombelli (Politecnico di Milano); Francesco Sinacori (Infineon Technologies Italia s.r.l); Manuel Roveri (Politecnico di Milano)
11. VETT: VectorDB-Enabled Transfer-Learning for Time-Series Forecasting
Authors: Alessandro Falcetta (Politecnico di Milano)*; Giulio Cristofaro (Dhiria S.r.l.); Lorenzo Epifani (Politecnico di Milano); Manuel Roveri (Politecnico di Milano)
12. ERFC: Happy Customers with Emotion Recognition and Forecasting in Conversation in Call Centers
Authors: 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)
13. Self Supervised LLM Customizer(SSLC): Customizing LLMs on Unlabeled Data to Enhance Contextual Question Answering
Authors: Raveendra R Hegde (Amazon)*; Saurabh Sharma (Amazon India)
14. ORCHID – Offline RL for Control of HVAC in Buildings using Historical and Low-Fidelity Simulation Data
Authors: Richa Verma (TCS Research)*; Srikar Babu Gadipudi (Indian Institute of Technology, Madras); Srinarayana Nagarathinam (Tata Consultancy Services Ltd); Harshad Khadilkar (Tata Consultancy Services Ltd.)
15. TinyML-Powered Gesture Wizardry: Low-Cost, Low-Power Two-Stage CNN for Static Hand Gesture Classification on MCU in Appliance Control
Authors: 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)
16. Trans-ARG: Predicting Antibiotic Resistance Genes with a Transformer-Based Model and Pretrained Protein Language Model
Authors: Mohd Manzar Abbas (Louisiana State University)*; Amit Ranjan (Louisiana State University); Aixin Hou (Louisiana State University); Supratik Mukhopadhyay (Louisiana State University)
17. KG-DTA: A knowledge graph-based meta-path learning framework to predict drug-target binding affinity
Authors: 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)
18. Tab2Graph: Transforming Heterogeneous Tables as Graphs
Authors: Rajat Singh (IIT Delhi)*; Raajita Bhamidipaty (IIT Delhi); Anjali Sharma (indian institute of technology Delhi); Srikanta Bedathur (IIT Delhi)
19. Visual Perception Transformer: Robust image understanding on unseen transformations across wide-ranging dataset sizes
Authors: 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)
20. BudgetMLAgent: A Cost-Effective LLM Multi-Agent system for Automating Machine Learning Tasks
Authors: Shubham Gandhi (TCS Research); Manasi Patwardhan (TCS Research)*; Lovekesh Vig (TCS Research); Gautam Shroff (IIIT Delhi)
Industry Track
1. Efficient and verifiable responses using Retrieval Augmented Generation (RAG)
2. Assessing the Impact of Upselling in Online Fantasy Sports
Authors: Aayush Chaudhary
3. Weighted Retriever Ensembles for Video-to-Product Ads Curation
Authors: Faizan Ahemad (Amazon India)*; Abdulla Mohammed (Amazon); Sachin Farfade (Amazon)
4. AI Enhanced Ticket Management System for optimized Support
Authors: Shubham Jain (Hughes Systique)*; Amit Gupta (Hughes Systique); Kumari Neha (Hughes Systique)
5. CultureVo: The Serious Game of Utilizing Gen AI for Enhancing Cultural Intelligence
Authors: Ajita Agarwala (CultureVo)*; Anupam Purwar (Independent); Viswanadhasai Nissankarao (SRM UNIVERSITY)
6. Aggregated Knowledge Model: Enhancing Domain-Specific QA with Fine-Tuned and Retrieval-Augmented Generation Models
Authors: 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)
7. Remote Attestation and Secure AI in Systems-on-Chip/Systems-in-Package
Authors: Giridhar Mandyam (Mediatek)
8. VidyaRANG: Conversational Learning Based Platform powered by Large Language Model
Authors: Chitranshu Harbola (Indian Institute of Technology, Madras)*; Anupam Purwar (Independent)
Demo Track
1. TASCA++ : A multi-agentic tool to scalably accelerate ML pipelines
Authors: Bibek Paul (Chennai Mathematical Institute); ARCHISMAN BHOWMICK (TATA CONSULTANCY SERVICES)*; Mayank Mishra (TCS); Sarthak Gupta (IIIT Nagpur); Rekha Singhal (TCS)
2. LeafSense: A Portable, Low-Cost, Low-Power Plant Disease Diagnostic Device Using TinyML
Authors: Riya Samanta (Indian Institute of Technology, Kharagpur)*; Bidyut Saha (Indian Institute of Technology Kharagpur); Soumya Kanti Ghosh (Indian Institute of Technology Kharagpur, India)
Workshop-GenAI
1. Methodology for Quality Assurance Testing of LLM-based Multi-Agent Systems
Isha Shamim (Tata Consultancy Services Limited)*; Rekha Singhal (TCS)
2. Bridging the Gap: Synthetic Data Augmentation through Inversion and Distribution Matching for Few-shot Learning
Yunsung Chung (Tulane University)*; Janet Wang (Tulane University); Jihun Hamm (Tulane University)
3. Question-Answering System in Computer Science
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)
4. Introducing a new hyper-parameter for RAG: Context Window Utilization
Kush Juvekar (Independant)*; Anupam Purwar (Independent)