Workshop
Machine Learning for Autonomous Driving
Rowan McAllister · Nicholas Rhinehart · Fisher Yu · Li Erran Li · Anca Dragan

Sat Dec 14th 08:00 AM -- 06:00 PM @ East Meeting Rooms 1 - 3
Event URL: https://ml4ad.github.io/ »

Autonomous vehicles (AVs) provide a rich source of high-impact research problems for the machine learning (ML) community at NeurIPS in diverse fields including computer vision, probabilistic modeling, gesture recognition, pedestrian and vehicle forecasting, human-machine interaction, and multi-agent planning. The common goal of autonomous driving can catalyze discussion between these subfields, generating a cross-pollination of research ideas. Beyond the benefits to the research community, AV research can improve society by reducing road accidents; giving independence to those unable to drive; and inspiring younger generations towards ML with tangible examples of ML-based technology clearly visible on local streets.

As many NeurIPS attendees are key drivers behind AV-applied ML, the proposed NeurIPS 2019 Workshop on Autonomous Driving intends to bring researchers together from both academia and industries to discuss machine learning applications in autonomous driving. Our proposal includes regular paper presentations, invited speakers, and technical benchmark challenges to present the current state of the art, as well as the limitations and future directions for autonomous driving.

08:45 AM Welcome <span> <a href="#"></a> </span> Rowan McAllister, Nick Rhinehart, Anca Dragan
09:00 AM Invited Talk <span> <a href="#"></a> </span> Raquel Urtasun
09:30 AM Contributed Talks <span> <a href="#"></a> </span>
09:45 AM Coffee + Posters (Break)
Changhao Chen, Nils Gählert, Edouard Leurent, Johannes Lehner, Apratim Bhattacharyya, Harkirat S Behl, TeckYian Lim, Shiho Kim, Jelena Novosel, Błażej Osiński, Arindam Das, Robin Shen, Jeff Hawke, Joachim Sicking, Babak Shahian Jahromi, Theja Tulabandhula, Claudio Michaelis, Evgenia Rusak, WENHANG BAO, Hazem Rashed, JP Chen, Amin Ansari, Jaekwang Cha, Mohamed Zahran, Daniele Reda, Jinhyuk Kim, Kim Dohyun, Ho Suk, Junekyo Jhung, Alexander Kister, Matthias Fahrland, Adam Jakubowski, Piotr Miłoś, Jean Mercat, Bruno Arsenali, Silviu Homoceanu, Xiao-Yang Liu, Philip Torr, Ahmad El Sallab, Ibrahim Sobh, Anurag Arnab, Christopher Galias
10:30 AM Invited Talk <span> <a href="#"></a> </span> Daniela Rus
11:00 AM Invited Talk <span> <a href="#"></a> </span> Andrej Karpathy
11:30 AM Invited Talk <span> <a href="#"></a> </span> Vladlen Koltun
12:00 PM Lunch + Posters (Break)
01:30 PM Invited Talk <span> <a href="#"></a> </span> Eric Wolff
02:00 PM Invited Talk <span> <a href="#"></a> </span> Cathy Wu
02:30 PM Invited Talk <span> <a href="#"></a> </span> Jaime Fernández Fisac
03:00 PM Contributed Talks <span> <a href="#"></a> </span>
03:30 PM Coffee + Posters (Break)
Ben Caine, Ren Wang, Nazmus Sakib, Nana Otawara, Meha Kaushik, elmira amirloo, Nemanja Djuric, Johanna Rock, Tanmay Agarwal, Angelos Filos, Panagiotis Tigkas, Donsuk Lee, Wootae Jeon, Nikita Jaipuria, Pin Wang, Jinxin Zhao, Liangjun Zhang, Ashutosh Singh, Ershad Banijamali, Mohsen Rohani, Aman Sinha, Ameya Joshi, Ching-Yao Chan, Mohammed Abdou Abdou, Changhao Chen, Jong-Chan Kim, eslam mohamed, Matt OKelly, Nirvan Singhania, Hiroshi Tsukahara, Atsushi Keyaki, Praveen Palanisamy, Justin Norden, Micol Marchetti-Bowick, Yiming Gu, Hitesh Arora, Shuby Deshpande, Jeff Schneider, Shangling Jui, Vaneet Aggarwal, Tryambak Gangopadhyay, Qiaojing Yan
04:30 PM Invited Talk <span> <a href="#"></a> </span> Igor Gilitschenski
05:00 PM Invited Talk <span> <a href="#"></a> </span> Chris Baker
05:30 PM Competition <span> <a href="#"></a> </span> Ming-Fang (Allie) Chang, Jagjeet Singh, Andrew Hartnett, Nicolas Cebron

Author Information

Rowan McAllister (UC Berkeley)
Nick Rhinehart (Carnegie Mellon University)
Fisher Yu (Princeton University)
Li Erran Li (Scale AI)

Li Erran Li is the head of machine learning at Scale and an adjunct professor at Columbia University. Previously, he was chief scientist at Pony.ai. Before that, he was with the perception team at Uber ATG and machine learning platform team at Uber where he worked on deep learning for autonomous driving, led the machine learning platform team technically, and drove strategy for company-wide artificial intelligence initiatives. He started his career at Bell Labs. Li’s current research interests are machine learning, computer vision, learning-based robotics, and their application to autonomous driving. He has a PhD from the computer science department at Cornell University. He’s an ACM Fellow and IEEE Fellow.

Anca Dragan (UC Berkeley)

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