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Workshop
MATH-AI: Toward Human-Level Mathematical Reasoning
Pan Lu · Swaroop Mishra · Sean Welleck · Yuhuai Wu · Hannaneh Hajishirzi · Percy Liang

Sat Dec 03 06:55 AM -- 03:00 PM (PST) @ Room 293 - 294
Event URL: https://mathai2022.github.io/ »

Mathematical reasoning is a unique aspect of human intelligence and a fundamental building block for scientific and intellectual pursuits. However, learning mathematics is often a challenging human endeavor that relies on expert instructors to create, teach and evaluate mathematical material. From an educational perspective, AI systems that aid in this process offer increased inclusion and accessibility, efficiency, and understanding of mathematics. Moreover, building systems capable of understanding, creating, and using mathematics offers a unique setting for studying reasoning in AI. This workshop will investigate the intersection of mathematics education and AI.

Author Information

Pan Lu (UCLA; AI2)
Swaroop Mishra (Arizona State University)
Sean Welleck (University of Washington)
Yuhuai Wu (Google)
Hannaneh Hajishirzi (University of Washington)
Percy Liang (Stanford University)
Percy Liang

Percy Liang is an Assistant Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011). His research spans machine learning and natural language processing, with the goal of developing trustworthy agents that can communicate effectively with people and improve over time through interaction. Specific topics include question answering, dialogue, program induction, interactive learning, and reliable machine learning. His awards include the IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014).

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