I'm currently at MIT, working on deep learning for perception and control of autonomous vehicles. Our research focuses on Human-Centered Artificial Intelligence (HCAI) that leverages human knowledge to enhance machine intelligence.
I TAed MIT 6.S094: Deep Learning for Self-driving Cars and MIT 6.S099: Artificial General Intelligence in Jan. & Feb. 2018. If you have questions regarding the course, please email us through deepcars [at] mit.edu / agi [at] mit.edu, respectively.
Prior to joining MIT, I worked on deep learning for human action recognition at University of Rochester (Dept. of Computer Science), after getting a Master degree in Data Science.
I'm from Shanghai, China. On a side of fun, I'm a casual Kaggler interested in playing with various kinds of data. I like photography, electro-funk, all kinds of cuisine, and at the moment, walking and traveling around with Pokémon Go.
Driving Scene Perception
Dynamic Scene and Optical Flow
Weakly Supervised Action Localization
Edge Cases in Image Recognition
Fine-grained Image Classification
MIT Autonomous Vehicle Technology Study: Large-Scale Deep Learning Based Analysis of Driver Behavior and Interaction
Lex Fridman, Daniel E. Brown, Michael Glazer, William Angell, Spencer Dodd, Benedikt Jenik, Jack Terwilliger, Julia Kindelsberger, Li Ding, Sean Seaman, Hillary Abraham, Alea Mehler, Andrew Sipperley, Anthony Pettinato, Bobbie Seppelt, Linda Angell, Bruce Mehler, Bryan Reimer
TricorNet: A Hybrid Temporal Convolutional and Recurrent Network for Video Action Segmentation
Li Ding, Chenliang Xu
MIT 6.S094: Deep Learning for Self-driving Cars
MIT 6.S099: Artificial General Intelligence
IEEE Transactions on Circuits and Systems for Video Technology (2018)
IEEE Access (2018)
Level: Competitions Expert (highest rank: 1169 | current rank)
Statoil/C-CORE Iceberg Classifier Challenge
(Satellite Image Classification)
· 2018 · Top 6%
Data Science Bowl 2017
(Lung Cancer Detection)
· 2017 · Top 6%
Thanks for visiting!