Organizers

Katja Hofmann
General Chair
Alexander Rush
Deputy General Chair
Yan Liu
Senior Program Chair
Chelsea Finn
Program Chair
Marc Deisenroth
Program Chair
Yejin Choi
Program Chair

Yejin Choi is a Brett Helsel associate professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington and also a senior research manager at AI2 overseeing the project Mosaic. Her research interests include language grounding with vision, physical and social commonsense knowledge, language generation with long-term coherence, conversational AI, and AI for social good. She is a co-recipient of the AAAI Outstanding Paper Award in 2020, a recipient of Borg Early Career Award (BECA) in 2018, among the IEEE’s AI Top 10 to Watch in 2015, a co-recipient of the Marr Prize at ICCV 2013, and a faculty advisor for the Sounding Board team that won the inaugural Alexa Prize Challenge in 2017. Her work on detecting deceptive reviews, predicting the literary success, and interpreting bias and connotation has been featured by numerous media outlets including NBC News for New York, NPR Radio, New York Times, and Bloomberg Business Week. She received her Ph.D. in Computer Science from Cornell University.

Feryal Behbahani
Workshop Chair
Vukosi Marivate
Workshop Chair
Krystal Maughan
Diversity & Inclusion Chairs

Current PhD student at the University of Vermont

Rosanne Liu
Diversity & Inclusion Chairs
Archana David
Virtual and Volunteer Chair

Archana David BEng, is a Data scientist with 13 yrs of IT experience, Infosys Ltd. Her ability to handle crisis has enabled her to work for 6 consecutive years in Europe and UK. She earned her Bachelor of Engineering(BEng) from Karunya University. Her IT experience in brief Developer => Automation Architect => Data Scientist

Jumanah Alshehri
Virtual and Volunteer Chair

Ph.D. Student@Temple University

Ayanna Howard
Ethics Review Committee
Miguel Luengo-Oroz
Ethics Review Committee
Patrick Lin
Ethics Review Committee

Patrick Lin, PhD, is the director of the Ethics + Emerging Sciences Group, based at California Polytechnic State University, San Luis Obispo, where he is a philosophy professor. Current affiliations include Stanford Law School, 100-Year Study on AI, World Economic Forum, Czech Academy of Sciences, and the Center for a New American Security. Previous affiliations include Stanford Engineering, US Naval Academy, Dartmouth College, Notre Dame, University of Iceland (Fulbright specialist), New America Foundation, and UNIDIR. He is well published in technology ethics, esp. in AI and robotics, with five books that include Robot Ethics (MIT Press, 2012) and Robot Ethics 2.0 (Oxford University Press, 2017), as well as several funded policy reports on military robotics, cyberwarfare, and enhanced warfighters. Dr. Lin regularly gives invited briefings to industry, media, and governments worldwide; and he teaches courses in ethics, technology, and law. He earned his BA at UC Berkeley and PhD at UC Santa Barbara.

Robert Sparrow
Ethics Review Committee
Shannon Vallor
Ethics Review Committee
Thomas Dietterich
Ethics Review Committee

Researcher in machine learning since 1977. Past roles: Executive Editor, Machine Learning Journal. Founding President, International Machine Learning Society. Program Chair AAAI 1990; NIPS 2000. President, Association for the Advancement of Artificial Intelligence (2014-2016). Current roles: ArXiv moderator for cs.LG, Advisory Board, NIPS Foundation

Charlie Gauthier
Blog Track Chairs
Claire Vernade
Blog Track Chairs
David Dobre
Blog Track Chairs
Gauthier Gidel
Blog Track Chairs

I am a Ph.D student supervised by Simon Lacoste-Julien, I graduated from ENS Ulm and Université Paris-Saclay. I was a visiting PhD student at Sierra. I also worked for 6 months as a freelance Data Scientist for Monsieur Drive (Acquired by Criteo) and I recently co-founded a startup called Krypto. I'm currently pursuing my PhD at Mila. My work focuses on optimization applied to machine learning. More details can be found in my resume.

My research is to develop new optimization algorithms and understand the role of optimization in the learning procedure, in short, learn faster and better. I identify to the field of machine learning (NIPS, ICML, AISTATS and ICLR) and optimization (SIAM OP)

Sebastien Bubeck
Blog Track Chairs
YaGuang Li
Workflow Chairs

YaGuang Li a senior research engineer in the Google Research, Brain team working on neural sequence and graph modeling research for task-oriented dialogue, and grounded large language model, such as LaMDA. Prior to joining Google, YaGuang received his Ph.D. degree in Computer Science at the University of Southern California and his Master degree in Computer Science from Institute of Software in University of Chinese Academy of Sciences in 2014. His primary research interest lies in machine learning, spatiotemporal prediction and recommendation, deep learning on graphs with applications in transportation.

Zhenyu Xue
Workflow Chairs
Ehi Nosakhare
Engagements Chairs
William Agnew
Engagements Chairs
Andrea Brown
Executive Director