is an Assistant Professor at the Ohio State University. His research interests are in machine learning and its applications to computer vision and autonomous driving. He was a postdoc at Cornell University. He holds a Ph.D. in CS from the University of Southern California. He was a co-organizer of ICML 2019 Workshop on Autonomous Driving.

is a postdoctoral researcher at UC Berkeley working on motion planning for autonomous vehicles at the Berkeley Deep Drive group. He previously worked with Uber's autonomous vehicle forecasting team, completed his PhD at the University of Cambridge on Bayesian reinforcement learning, and a masters in motion planning at the Australian Center for Field Robotics. Rowan was the primary organizer of the NeurIPS 2019 workshop on Machine Learning for Autonomous Driving.

is the Head of Machine Learning Research at the Toyota Research Institute (TRI) in Los Altos, CA, USA, focusing on going beyond supervised learning for Automated Driving. He received his PhD from Microsoft Research - Inria Paris in 2012, co-organized the ECCV/ACMM 2016 workshop on Virtual/Augmented Reality for Visual AI, and the ICML 2019 workshop on AI for Automated Driving. He was also guest editor for IJCV.

is a senior applied scientist at Alexa AI, Amazon and an adjunct professor at Columbia University. His current research interests are machine learning (3D deep learning, generative models, multimodal learning with images and text, dialog systems, deep reinforcement learning). Previously, he was with Scale AI, Pony.ai, Uber ATG and Uber Prime, Bell Labs. He co-taught tutorials at ICML'17 and ICCV’19, and co-organized several workshops at NeurIPS, ICML, CVPR, ICCV on machine learning for autonomous driving. He has a PhD in CS, Cornell. He is an ACM Fellow and IEEE Fellow.

is a senior research scientist and manager at NVIDIA with a strong background in perception for autonomous driving. He has been involved in the organization of 20+ workshops mainly at CVPR and ECCV/ICCV, including the Workshop in Autonomous Driving, Deep Vision, Computer Vision for Road Scene Understanding or Color and Photometry in Computer Vision. He has also served as Area Chair for major conferences and is an associate editor for the IEEE Trans. on Intelligent Transportation Systems.

is President of North-C Technologies, where he consults in machine learning, robotics, and autonomous vehicles. From 2003-2007 he was a DARPA Program Manager in the IPTO and TTO offices. He conceived and managed programs in autonomous ground robot navigation and locomotion. For most of his scientific career Jackel was a manager and researcher in Bell Labs and then AT\&T Labs. He has created and managed research groups in microscience and microfabrication, in machine learning and pattern recognition, and in carrier-scale telecom services. Jackel holds a PhD in experimental physics from Cornell University with a thesis in superconducting electronics. He is a Fellow of the American Physical Society and the IEEE.

is the Head of Research at Lyft Level 5 self-driving division. He received his Ph.D. from Oxford and in 2016 co-founded and served as CEO of Blue Vision Labs, working on a city-scale localization and mapping system for collaborative augmented reality and robotics. In 2018 the company was acquired by Lyft to use the technology to build self-driving cars where he now leads Lyft’s research team focused on ML approaches for self-driving perception and planning. Peter co-organized tutorials at CVPR and NeurIPS in 2019, and worked on releasing Level 5 self-driving dataset.