Invited Speakers

Distinguished Scientist/VP, Amazon Web Services

I studied physics in Munich at the University of Technology, Munich, at the Universita degli Studi di Pavia and at AT&T Research in Holmdel. During this time I was at the Maximilianeum München and the Collegio Ghislieri in Pavia. In 1996 I received the Master degree at the University of Technology, Munich and in 1998 the Doctoral Degree in computer science at the University of Technology Berlin. Until 1999 I was a researcher at the IDA Group of the GMD Institute for Software Engineering and Computer Architecture in Berlin (now part of the Fraunhofer Geselschaft). After that, I worked as a Researcher and Group Leader at the Research School for Information Sciences and Engineering of the Australian National University. From 2004 onwards I worked as a Senior Principal Researcher and Program Leader at the Statistical Machine Learning Program at NICTA. From 2008 to 2012 I worked at Yahoo Research. In spring of 2012 I moved to Google Research to spend a wonderful year in Mountain View and I continued working there until the end of 2014. From 2013-2017 I was professor at Carnegie Mellon University. I co-founded Marianas Labs in early 2015. In July 2016 I moved to Amazon Web Services to help build AI and Machine Learning tools for everyone.

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)

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.