One paper accepted to NeurIPS 2022: Self-supervised Amodal Video Object Segmentation.
One paper accepted to NeurIPS 2021: GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction. Check it out!
- I am a Senior Applied Scientist at Amazon Web Service Shanghai AI Lab (ASAIL). I play a lot with objects. In this period, I will be focusing on object-centric learning, graph neural network and causal representation learning, exploring and exploiting their usage in applications like Video Analysis, Relational Inference and 3D Vision.
- Before joining Amazon, I was a Staff Machine Learning Scientist at Tesla Autopilot AI/Vision team, working with Dr. Andrej Karpathy. I was one of the major contributors of the Autopilot vision neural network stack and the task owner of Autopilot (Dynamic and Static) Object Detection during 2017 - 2020. My working items have been shipped into hundreds of thousands of Tesla cars worldwide during major Autopilot releases, contributing to Autopilot functionalities like Traffic-Aware Cruise Control, Auto Lane Change, Automatic Emergency Braking, Navigation on Autopilot, Smart Summon, etc.
- Prior to Tesla, I spent 3.25 years at Microsoft. I was a Software Engineer 2 at Microsoft Bing Multimedia team (now under Microsoft AI & Research Org), where I was working on Image-Text Semantic Embedding to contribute to functionalities like Image Annotation and Image Search in Bing Search Engine. And during my graduate years, I interned at Microsoft Research Asia, advised by Prof. Zheng Zhang and Dr. Kuiyuan Yang, where I was working on both training platform and vision applications of deep learning. I was a major contributor of the open-source deep learning training framework Minerva and also contributed to the machine learning library MXNet.
- I received M.S degree in Computer Science from Wangxuan Institute Of Computer Technology, Peking University, advised by Prof. Yuxin Peng. And B.S degree in Computer Science from Nankai University.
- My enthusiasm is to apply machine learning to large-scale, life-changing technologies, currently with a focus on computer vision related applications.