Pang Wei Koh 2024 Early Career Fellow
Affiliation Assistant Professor, University of Washington Hard Problem Solved AI’s continually evolving safety and security, robustness, performance, output challenges and other shortcomings that may cause harm or erode public trust of AI systems, especially in safety-critical applications and uses where societal stakes and potential for societal harm are high.

Pang Wei Koh is an assistant professor in the Allen School of Computer Science and Engineering at the University of Washington, a visiting research scientist at the Allen Institute for AI, and a Singapore AI Visiting Professor. His research interests are in the theory and practice of building reliable machine learning systems. His research has been published in Nature and Cell, featured in media outlets such as The New York Times and The Washington Post, and recognized by the MIT Technology Review Innovators Under 35 Asia Pacific award and best paper awards at ICML and KDD. He received his PhD and BS in Computer Science from Stanford University. Prior to his PhD, he was the 3rd employee and Director of Partnerships at Coursera.

AI2050 Project

Pang Wei Koh’s AI2050 project aims to develop more trustworthy models by reducing their reliance on the often-inscrutable internal workings of their parameters and instead enabling them to find and reason directly with relevant data sources. He will develop new methods for building models that when asked, for example, a medical question, would first retrieve relevant sources such as peer-reviewed medical papers in credible journals, integrate their information, and then generate an answer with clear attribution to these sources.