Invited Speakers

Michael Bronstein is a professor at Imperial College London, where he holds the Chair in Machine Learning and Pattern Recognition, and Head of Graph Learning Research at Twitter. His main research expertise is in theoretical and computational methods for geometric data analysis, a field in which he has published extensively in the leading journals and conferences. He is credited as one of the pioneers of geometric deep learning, generalizing machine learning methods to graph-structured data. Michael received his PhD from the Technion (Israel Institute of Technology) in 2007. He has held visiting appointments at Stanford, MIT, Harvard, and Tel Aviv University, and has also been affiliated with three Institutes for Advanced Study (at TU Munich as Rudolf Diesel Fellow (2017-), at Harvard as Radcliffe fellow (2017-2018), and at Princeton (2020)). Michael is the recipient of four ERC grants, Fellow of IEEE and IAPR, ACM Distinguished Speaker, and World Economic Forum Young Scientist. In addition to his academic career, Michael is a serial entrepreneur and founder of multiple startup companies, including Novafora, Invision (acquired by Intel in 2012), Videocites, and Fabula AI (acquired by Twitter in 2019). He has previously served as Principal Engineer at Intel Perceptual Computing and was responsible for the development of RealSense 3D sensing technology.

Siddhartha Chaudhuri is Senior Research Scientist in the Creative Intelligence Lab at Adobe Research, and Assistant Professor (on leave) of Computer Science and Engineering at IIT Bombay. He obtained his Ph.D. from Stanford University, and his undergraduate degree from IIT Kanpur. He subsequently did postdoctoral research at Stanford and Princeton, and taught at Cornell. Siddhartha's work combines geometric analysis, machine learning, and UI innovation to make sophisticated 3D geometric modeling accessible even to non-expert users. He also studies foundational problems in geometry processing (retrieval, segmentation, correspondences) that arise from this pursuit. His research themes include assembly-based modeling, semantic attributes for design, generative neural networks for shape structures, and other applications of deep learning to 3D geometry processing. He is the original author of the commercial 3D character modeling tool Adobe Fuse, and the author of the open-source Thea toolkit for geometric computing.

Andreas Geiger is a full professor at the University of Tübingen and a group leader at the Max Planck Institute for Intelligent Systems. Prior to this, he was a visiting professor at ETH Zürich and a research scientist at MPI-IS. He studied at KIT, EPFL and MIT and received his PhD degree in 2013 from the Karlsruhe Institute of Technology. His research interests are at the intersection of 3D reconstruction, motion estimation, scene understanding and sensory-motor control. He maintains the KITTI vision benchmark.

Shenzhen University

Ruizhen Hu is an Assistant Professor at Shenzhen University, China. She received her Ph.D. from the Department of Mathematics, Zhejiang University. Before that, she spent two years visiting Simon Fraser University, Canada. Ruizhen’s research interests are in shape analysis, geometry processing and fabrication. She has received several research awards including the Asia Graphics “Young Researcher Award” in 2019, among others.

Qixing Huang is an assistant professor of Computer Science at the University of Texas at Austin. He obtained his PhD in Computer Science from Stanford University. He was a research assistant professor at Toyota Technological Institute at Chicago before joining UT Austin. Dr. Huang's research spans the fields of computer vision, computer graphics, and machine learning, and publishes extensively in venues such as SIGGRAPH, CVPR, ICCV, ECCV, NeuriPS, ICML, and etc. In particular, his recent focus is on developing machine learning algorithms (particularly deep learning) that leverage Big Data to solve core problems in computer vision, computer graphics and computational biology. He is also interested in statistical data analysis, compressive sensing, low-rank matrix recovery, and large-scale optimization, which provides theoretical foundation for his research.

Isaak Lim is a Researcher at the Visual Computing Institute of the RWTH Aachen University under the supervision of Prof. Leif Kobbelt. His main research interest is Geometric Deep Learning.

Yaron Lipman is an associate professor at the Department of Computer Science and Applied Mathematics at the Weizmann Institute of Science, Israel. He did his PhD at Tel Aviv University and postdoc at Princeton University. His research interests are in geometric and irregular learning, geometry processing, shape comparison and analysis, discrete differential geometry, and optimization. Yaron has received multiple awards for his work, including the Eurographics Young Researcher Award (2009), the Blavatnik Award for Young Scientists from the New-York Academy of Sciences (2010), the ERC Starting Grant (2012), and the ERC Consolidator Grant (2018).

Sainan Liu is Ph.D. student at the University of California, San Diego working with Professor Zhuowen Tu. Her main research interest is recognition in both 2D and 3D domains.