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We are delighted to announce exSPLORe 2026, a five-day workshop from January 13–17, 2026, traversing the exciting areas of quantitative research in Data Science, Machine Learning, and Artificial Intelligence.
- Jan 13–14: Tutorials on Generative AI, LLMs, and Sequential Learning Theory.
- Jan 15: Industry interactions and panel discussions with Data Science Practitioners.
- Jan 16–17: Research workshop, featuring talks by luminaries, Young Researcher Best Paper Award, and Hackathon Winners.
Venue
Takshila Hall ( AC-02 | LR-007), Ashoka University
To Participate
Graduates, advanced undergraduates, post-docs, and faculty interested in related fields are encouraged to apply.
Limited accommodation is available for outstation participants.
Click here to Register
Last date for registration: November 30, 2025
Confirmed Speakers
| Sarah Cen, Carnegie Mellon University |
Dheeraj Nagaraj, Google DeepMind |
| Peter W. Glynn, Stanford University |
Venkat Padmanabhan, Microsoft Research |
| Ashish Goel, Stanford University |
Alexandre Proutiere, KTH Royal Institute of Technology |
| Aditya Gopalan, IISc |
Arun Sai Suggala, Google DeepMind |
| Vineet Goyal, Columbia University |
Himanshu Tyagi, IISc |
| Andrew Ilyas, Carnegie Mellon University |
Dootika Vats, IIT Kanpur |
| Prateek Jain, Google DeepMind |
Nishith Vishnoi, Yale University |
| Karthyek Murthy, USC Los Angeles |
Assaf Zeevi, Columbia University |
Click here to downlaod the event poster
Steering committee: V Borkar (IIT Bombay), P Glynn (Stanford), G Iyengar (Columbia), S Juneja (Ashoka University), P Netrapalli (Google DeepMind), A Ramdas (CMU)
Organising committee: V Borkar (IIT Bombay), S Juneja (Ashoka), P Netrapalli (Google DeepMind), Sumegh P (Ashoka), KS Mallikarjuna Rao (IIT Bombay), D Shah (MIT), A Thakkar (Ashoka)
[post_title] => Explorations in Statistics, Probability, Learning and Optimization Research 2026
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[post_content] => Abstract: Extracting actionable insights from unstructured text remains a fundamental goal of NLP, yet conventional approaches often fall short in temporal and causal reasoning and integrating domain-specific insights. This talk introduces innovative research directions to address these challenges across clinical and social science domains. First, I will introduce GraphTREx, a model that enhances clinical temporal relation extraction by integrating context-aware representations with graph neural networks. This integration enables improved timeline extraction from clinical notes, overcoming challenges posed by long documents and specialized jargon, thereby supporting more accurate patient representations. I will then turn to social data, illustrating how contextualized representations help quantify between-group polarization and use causal inference to examine when intergroup interactions mitigate it. Finally, I will present a comprehensive framework to investigate gender bias in generative-AI-driven recruitment and highlight how behavioral alignment affects fairness.
About the Speaker: Rochana Chaturvedi is a Postdoctoral Research Fellow at Argonne National Laboratory, where she develops large language model (LLM) frameworks for scientific reasoning. Her research lies at the intersection of natural language processing, graph-based modeling, and causal machine learning, with applications spanning healthcare, computational social science, AI ethics, and climate science communication. She received her Ph.D. in Computer Science from the University of Illinois Chicago and previously served as an Assistant Professor at the University of Delhi. Her research has been published in venues such as ACL, the Web Conference (WWW), Political Analysis, and IEEE BIBM, and has been covered by major media outlets.
We look forward to you your active participation.
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We are delighted to announce exSPLORe 2026, a five-day workshop from January 13–17, 2026, traversing the exciting areas of quantitative research in Data Science, Machine Learning, and Artificial Intelligence.
- Jan 13–14: Tutorials on Generative AI, LLMs, and Sequential Learning Theory.
- Jan 15: Industry interactions and panel discussions with Data Science Practitioners.
- Jan 16–17: Research workshop, featuring talks by luminaries, Young Researcher Best Paper Award, and Hackathon Winners.
Venue
Takshila Hall ( AC-02 | LR-007), Ashoka University
To Participate
Graduates, advanced undergraduates, post-docs, and faculty interested in related fields are encouraged to apply.
Limited accommodation is available for outstation participants.
Click here to Register
Last date for registration: November 30, 2025
Confirmed Speakers
| Sarah Cen, Carnegie Mellon University |
Dheeraj Nagaraj, Google DeepMind |
| Peter W. Glynn, Stanford University |
Venkat Padmanabhan, Microsoft Research |
| Ashish Goel, Stanford University |
Alexandre Proutiere, KTH Royal Institute of Technology |
| Aditya Gopalan, IISc |
Arun Sai Suggala, Google DeepMind |
| Vineet Goyal, Columbia University |
Himanshu Tyagi, IISc |
| Andrew Ilyas, Carnegie Mellon University |
Dootika Vats, IIT Kanpur |
| Prateek Jain, Google DeepMind |
Nishith Vishnoi, Yale University |
| Karthyek Murthy, USC Los Angeles |
Assaf Zeevi, Columbia University |
Click here to downlaod the event poster
Steering committee: V Borkar (IIT Bombay), P Glynn (Stanford), G Iyengar (Columbia), S Juneja (Ashoka University), P Netrapalli (Google DeepMind), A Ramdas (CMU)
Organising committee: V Borkar (IIT Bombay), S Juneja (Ashoka), P Netrapalli (Google DeepMind), Sumegh P (Ashoka), KS Mallikarjuna Rao (IIT Bombay), D Shah (MIT), A Thakkar (Ashoka)
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