Speakers and Panelists

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Speaker Details:

Danqi Chen is an Associate Professor of Computer Science at Princeton University, where she co-leads the Princeton NLP Group and serves as Associate Director of Princeton Language and Intelligence (PLI). Her research focuses on natural language processing, machine learning, and the development of intelligent systems that can acquire and reason over knowledge from large-scale text data. Her contributions have been recognized through numerous prestigious honors, including the NSF CAREER Award, and the Samsung AI Researcher of the Year. 

Title: TBD

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Speaker Details:

Tatsunori Hashimoto is an Assistant Professor of Computer Science at Stanford University. His research focuses on developing statistical and machine learning methods that improve the robustness, safety, and reliability of large-scale AI systems. He is a recipient of the NSF CAREER Award, the Alfred P. Sloan Research Fellowship, and the Samsung AI Researcher of the Year, and has received best paper awards at ICML, ICLR, and CHI. He received his Ph.D. from Massachusetts Institute of Technology. 

Title: TBD

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Speaker Details:

Andrew Ilyas is an Assistant Professor at Carnegie Mellon University. His research seeks to make ML more predictable & reliable by pursuing a precise empiricalunderstanding of the entire ML pipeline. Prior to joining CMU, he was a Stein Fellow at Stanford University and received his Ph.D. from Massachusetts Institute of Technology. His work has been recognized through honors including the George M. Sprowls Ph.D. Thesis Award and the Open Philanthropy AI Fellowship. 

Title: TBD

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Speaker Details:

Omar Khattab is an Assistant Professor of Electrical Engineering and Computer Science at Massachusetts Institute of Technology. He studies how to program and optimize systems specified in natural language, as well as how to use the knowledge encoded in language models to build more effective and sample-efficient learning algorithms. He is the creator of the ColBERT retrieval model and the DSPy framework, which have become widely used foundations for retrieval-augmented generation and language model programming. 

Title: TBD

Abstract: TBD

Speaker Details:

Dimitris Papailiopoulos is the Jay and Cynthia Ihlenfeld Associate Professor of Electrical and Computer Engineering at University of Wisconsin–Madison. His research focuses on machine learning, optimization, coding theory, and the foundations of large-scale AI systems. He is a recipient of the NSF CAREER Award and the IEEE Joint Communications Society/Information Theory Society Best Paper Award, and is a co-founder of the Conference on Machine Learning and Systems (MLSys). 

Title: TBD

Abstract: TBD

Speaker Details:

Songlin Yang is a Member of Technical Staff at Thinking Machines Lab. Her research focuses on efficient language model architectures, sequence modeling, and hardware-aware algorithm design, with an emphasis on linear attention methods and scalable alternatives to Transformers. She received her Ph.D. from Massachusetts Institute of Technology, where she was advised by Yoon Kim.