Invited Speakers

Assistant Professor, McGill University

Siamak Ravanbhakhsh is an Assistant Professor at McGill University's School of Computer Science. He is broadly interested in inference within structured, complex and combinatorial domains using graphical and structured deep models. In addition to its potential role in artificial intelligence, ability to draw inference in structured domains, is essential in a data-driven approach to science. He is one of the pioneers of the field of deep learning on sets with the ``DeepSets'' paper in NeurIPS 2017.

Visiting Professor, Carnegie Mellon University

Eunsu Kang is an artist, a researcher, and an educator who explores the intersection of art and machine learning. Through over 100 art exhibitions, her works have transformed from video installations into interactive and interdisciplinary art projects that currently focus on the new area of AI art. She was a tenured art professor and now is teaching Art and Machine Learning and Creative AI courses at Carnegie Mellon University's School of Computer Science.

Research Scientist, Autonomous Energy Materials Discovery, Dutch Institute for Fundamental Energy Research (DIFFER)

Research Scientist, Google Research

Amr Ahmed is a Senior Staff Research Scientist at Google. His research interests include large-scale machine learning, data/web mining, user modeling, personalization, social networks and content analysis. He received the best paper award at KDD 2014 , the best Paper Award at WSDM 2014, the 2012 ACM SIGKDD Doctoral Dissertation Award, and a best paper award (runner-up) at WSDM 2012.

Associate Professor, Massachusetts Institute of Technology

Stefanie Jegelka is an X-Consortium Career Development Associate Professor at MIT EECS, and a member of CSAIL, IDSS, the Center for Statistics and Machine Learning at MIT. She is also affiliated with the ORC. Before that, she was a postdoc in the AMPlab and computer vision group at UC Berkeley, and a PhD student at the Max Planck Institutes in Tuebingen and at ETH Zurich.