Responsible Machine Learning Summit 2022

Artificial Intelligence and Machine Learning Research at UC Santa Barbara

UC Santa Barbara

October 7, 2022

Location: Henley Hall 1st Floor

This is a free event but we are requiring registration. Please register in advance:



Welcome Mixer



Welcome and Opening Remarks:

Tresa Pollock Interim Dean of Engineering and ALCOA Distinguished Professor, Materials

Pierre Wiltzius Executive Dean of the College of Letters and Science, Susan & Bruce Worster Dean of Science, Professor of Physics

William Wang Director, Center for Responsible Machine Learning and Mellichamp Associate Professor of Artificial Intelligence



Opening Keynote:

Miguel Eckstein Director, Mellichamp Initiative in Mind and Machine Intelligence and Mellichamp Professor of Psychological and Brain Sciences

Session Chair: William Wang



ML Foundations:

Sui Tang Assistant Professor of Mathematics

Ruimeng Hu Assistant Professor of Statistics and Applied Probability  

Igor Mezic Professor of Mechanical Engineering

Yu-Xiang Wang Co-Director of the Center for Responsible Machine Learning and Eugene Aas Assistant Professor of Computer Science

Session Chair: Mahnoosh Alizadeh Associate Professor, Electrical and Computer Engineering



Lunch break



Afternoon Keynote:

B.S. Manjunath Distinguished Professor and Chair, Department of Electrical and Computer Engineering

Session Chair: Yu-Xiang Wang



ML for Science and Engineering:

Lei Li Assistant Professor of Computer Science

Claudio Campagnari Professor and Department Chair, Physics 

Sam Daly Professor of Mechanical Engineering

Stephen Wilson Professor and Associate Chair, Materials 

Session Chair: Timothy Sherwood Professor of Computer Science






ML for Arts, Humanities, and Social Sciences:

Simon Todd Assistant Professor of Linguistics

Paul Leonardi Chair and Duca Family Professor of Technology Management

Sarah Rosalena Brady Assistant Professor of Art

Session Chair: Kyle Lewis Department Chair and Professor, Technology Management



Breakout Session:

Topic 1: Responsible and Safe Use of AI
Topic 2: Getting the Most of AI, Data, and Foundation Models
Topic 3: Interdisciplinary Collaborations in AI and Machine Learning



Summary, closing remarks and adjourn


Sponsored by the Center for Responsible Machine Learning, the Mellichamp Initiative in Mind and Machine Intelligence, and Amazon Alexa AI