Yuke Zhu received his master’s and Ph.D. degrees from Stanford. His Ph.D. thesis centers around closing the perception-action loop to make robot intelligence more generalized and applicable to less-controlled environments. His research lies at the intersection of robotics, machine learning, and computer vision. He develops computational methods of perception and control that give rise to intelligent robot behaviors. Through his work, he aspires to teach robots to understand and interact with the visual world around them.

Haggai Maron joined Nvidia Research in October 2019 as a Research Scientist. His main fields of interest are machine learning and shape analysis. In particular, he studies how to apply deep learning to irregular domains (e.g., sets, graphs, point clouds, and surfaces) by leveraging their symmetry structure. 

Haggai completed his MSc and Ph.D. at the Department of Computer Science and Applied Mathematics at the Weizmann Institute of Science, and his BSc in Mathematics and Computer Science from the Hebrew University of Jerusalem.

Ting-Chun Wang is a senior research scientist at NVIDIA in Santa Clara, USA. He obtained his Ph.D. in EECS from UC Berkeley, advised by Professor Ravi Ramamoorthi and Alexei A. Efros. He is a recipient of the Berkeley Fellowship. He won the 1st place in the Domain Adaptation for Semantic Segmentation Competition in CVPR, 2018. His semantic image synthesis paper was in the best paper finalist in CVPR, 2019. He served as an area chair in WACV, 2020.