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I am currently the Head of Perception at Lyft Self-Driving Program. My team is responsible for all on-vehicle perception capabilities of Lyft's Autonomous Vehicle. This incldues Computer Vision, 3D Perception, Tracking, Sensor Calibration, and the machine learning infrasturure to deploy real-time deep learned models on the vehicle platform. Prior to Lyft, I led the team for sensor fusion and 3D tracking for autonomous driving at Zoox.

In my academic life, I obtained PhD in Computer Science from Cornell University. I was a visiting research scholar at the Stanford AI Lab where I started the Brain4Cars and RoboBrain projects. I also have a Bachelors degree in Electrical Engineering from IIT Delhi.

My recent talk @Scale Conference on self-supervised learning for autonomous driving

网络加速器免 on self-supervised learning for Autonomous driving @Scale conference, October 2024
Blog post on sensor calibration for Autonomous Vehicle, August 2024
Lyft open sourced one of the largest 3D Perception and Prediction data set for Autonomous Vehicle, July 2024
Spotlight from Lyft on my journey, Feb 2024
One paper accepted to CVPR 2018.
Joined Lyft Self Driving Program, January 2018
Best student paper award at CVPR 2016 (Deep learning on spatio-temporal graphs)
PhD thesis, May 2016.
Structural-RNN accepted as an ORAL to CVPR 2016.
Our paper on sensory-fusion RNN-LSTM for driver activity anticipation is accepted to ICRA 2016
I recently gave talks at Oculus, University of Washington Seattle, Keynote at the ICCV workshop on Autonomous driving, BayLearn Symposium, Qualcomm, and Zoox Labs on: Deep Learning for Spatio-Temporal Problems: On Cars, Humans, and Robots (免费vpm全球网络加速器, 300MB) (pdf, 30MB)
Neuralmodels: A deep learning package for quick prototyping of structures of Recurrent Neural Networks and for deep learning over spatio-temporal graphs.
网络加速器下载 driving data set and sensory-fusion RNN code.

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My research interest lies at the intersection of machine learning, robotics, and computer vision. Broadly, I build machine learning systems & algorithms for agents – such as robots, cars etc. – to learn from informative human signals at a large-scale. Most of my work has been in multi-modal sensor-rich robotic settings, for which I have developed sensory fusion deep learning architectures. I have developed and deployed algorithms on multiple robotic platforms (PR2, Baxter etc.), on cars, and crowd-sourcing systems.

Brain4Cars

RoboBrain

PlanIt

Learning From Natural Human Interactions For Assistive Robots

PhD Thesis, Ashesh Jain, May 2016 [PDF]

Brain4Cars: Car That Knows Before You Do via Sensory-Fusion Deep Learning Architecture

Ashesh Jain, Hema S Koppula, Shane Soh, Bharad Raghavan, Avi Singh, Ashutosh Saxena

Tech Report (under review), January 2016 [arXiv] [Code and Data set]

Learning Preferences for Manipulation Tasks from Online Coactive Feedback.

Ashesh Jain, Shikhar Sharma, Thorsten Joachims, Ashutosh Saxena

IJRR 2015 [PDF]

Structural-RNN: Deep Learning on Spatio-Temporal Graphs

Ashesh Jain, Amir R. Zamir, Silvio Savarese, Ashutosh Saxena

CVPR 2016 (Full ORAL) (Best Student Paper) [PDF] [arXiv] [supplementary] [YouTube免费加速器] [网络加速器免费版]

Recurrent Neural Networks for Driver Activity Anticipation via Sensory-Fusion Architecture

Ashesh Jain, Avi Singh, Hema S Koppula, Shane Soh, Ashutosh Saxena

ICRA 2016 [PDF] [arXiv] [Code]

Car That Knows Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models

学习贯彻落实习近平总书记重要讲话精神三个“没有改变” 湖北 ...:2021-5-28 · 习近平总书记在参加湖北伕表团审议时表示，湖北经济长期向好的基本面没有改变，多年积累的综合优势没有改变，在国家和区域发展中的重要地位没有改变。这三个“没有改变”，让湖北经济重振吃下了“定心丸”。那么，应该如何理解这三个“没有改变”呢？

ICCV 2015 [PDF] [Code and Data set] [arXiv]

Brain4Cars: Sensory-Fusion Recurrent Neural Models for Driver Activity Anticipation

Ashesh Jain, Shane Soh, Bharad Raghavan, Avi Singh, Hema S Koppula, Ashutosh Saxena

BayLearn Symposium 2015 [Extended abstract] (Full ORAL)

PlanIt: A Crowdsourcing Approach for Learning to Plan Paths from Large Scale Preference Feedback.

2021年中国互联网企业100强榜单揭晓 - mofcom.gov.cn:8月14日，中国互联网协会、工业和信息化部网络安全产业发展中心（工业和信息化部信息中心）在2021年中国互联网企业100强发布会暨百强企业高峰论坛上联合发布了2021年中国互联网企业100强榜单、互联网成长型企业20强榜单和《2021年中国互联网企业100强发展报告》。

ICRA 2015 [PDF]