The schedule is tentative and subject to change. All times are IST.
| Day 1 | January 5, 2023 |
| 10:30-10:40 | Welcome |
| 10:40-12:00 | Session 1: AI in Healthcare: Challenges and Applications |
| Strategies to Engender Trust in Clinical Decision Support among Clinicians Ravi Parikh (Penn) | |
| Retain Trust by Delivering Eventually Correct Decisions: Case Studies, Opportunities, and Challenges Soma Dhavala (Wadhwani AI) | |
| Computational Social Listening During COVID-19 Using Social Media Sharath Chandra (Penn) | |
| Integrating Context into AI for Clinical and Public Health Tavpritesh Sethi (IIIT Delhi) | |
| 12:00-01:00 | Session 2: Safety, Reliability, and Robustness |
| Neurosymbolic Methods for Robust AI Sriram Rajamani (MSR India) | |
| Calibrating Deep Neural Network Models Chetan Arora (IIT Delhi) | |
| Applications of Quantiles in Quantifying Uncertainty and Improving Robustness Aditya Challa (BITS-Pilani Goa) | |
| Specification-Guided Reinforcement Learning Rajeev Alur (Penn) | |
| 01:00-02:00 | Lunch |
| 02:00-03:00 | Session 3: Industry Panel |
| Moderator: Sameep Mehta (IBM Research) Panelists from Wadhwani, Bosch, Amazon, Samsung, and GE | |
| 03:00-03:20 | Coffee break |
| 03:20-05:00 | Session 4: ML: From Theory to Practice |
| Building Safe Autonomous Systems -- what we can learn from Autonomous Racing Rahul Mangharam (Penn) | |
| PyTorch Plugins for Uncertainty Quantification and Out-of-Distribution Detection Yash Khandelwal, Nevil Vekaria, Yugam Tiwari, Rishabh Sharma (Wadhwani AI) | |
| Voice AI for Ubiquitous Smart Home Experience Girdhar Jakki (Samsung R&D) | |
| Learning Cautious and Scrupulous Robot Behaviors Dinesh Jayaraman (Penn) | |
| Performance and Risk Tradeoffs of Responsible AI at Scale Sunayana Sitaram (MSR India) | |
| Protect your raison d'etre – Artificial Intelligence Yuvaraj Govindarajulu (Bosch AIShield) | |
| 05:00-06:00 | Session 5: Student Posters |
| 07:00-11:00 | Dinner at The Chancery Pavilion (135 Residency Rd) |
| Day 2 | January 6, 2023 |
| 9:00-10:40 | Session 6: Privacy, Fairness, and Explainability |
| Moving from Post-hoc to Ante-hoc Explainability in Deep Learning Models Vineeth Balasubramanian (IIT Hyderabad) | |
| Scallop: A Neurosymbolic Programming Language Mayur Naik (Penn) | |
| Group-Fairness and Individual-Fairness Amit Deshpande (MSR India) | |
| Pipeline Interventions Sampath Kannan (Penn) | |
| Private Collaboration made EzPC Rahul Sharma (MSR India) | |
| 10:40-11:00 | Coffee break |
| 11:00-12:00 | Session 7: Group Discussions |
| Moderator: Usha Rengaraju (Exa Protocol) | |
| 12:00-01:15 | Wrapup and Lunch |