Li Jing is a postdoctoral researcher at Facebook AI Research (FAIR), working with Yann LeCun.
Before joining FAIR, he obtained his PhD in physics from MIT. He received a BS in physics and a BA in economics from Peking University.
He is a co-founder of Lightelligence Inc..
His current research focuses on self-supervised learning. He is also interested in representation learning, multimodal learning, AI for science.
He has been awarded Forbes China 30 under 30. He has won a gold medal in the 2010 International Physics Olympiad (IPhO).
Understanding Dimensional Collapse in Contrastive Self-supervised Learning
Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian
Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations
Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic
Heuristic Recurrent Algorithms for Photonic Ising Machines
Charles Roques-Carmes, Yichen Shen, Cristian Zanoci, Mihika Prabhu, Fadi Atieh, Li Jing, Tena Dubcek, Vladimir Ceperic, John Joannopoulos, Dirk Englund, Marin Soljacic
Nature Communications 2020
Nanophotonic Particle Simulation and Inverse Design Using Artificial Neural Networks
John Peurifoy, Yichen Shen, Li Jing, Yi Yang, Fidel Cano-Renteria, Brendan Delacy, John Joannopoulos, Max Tegmark, Marin Soljacic
Science Advances 2018
[Paper] [News] [Code]
We Can Explain Your Research in Layman’s Terms: Towards Automating Science Journalism at Scale
Rumen Dangovski,Michelle Shen, Dawson Byrd, Li Jing, Desislava Tsvetkova, Preslav Nakov, Marin Soljacic
Vector-Vector-Matrix Architecture: A Novel Hardware-Aware Framework for Low-Latency Inference in NLP Applications
Matthew Khoury, Rumen Dangovski, Longwu Ou, Preslav Nakov, Yichen Shen, Li Jing
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Li Jing*, Yichen Shen*, Tena Dubcek, John Peurifoy, Scott Skirlo, Yann LeCun, Max Tegmark, Marin Soljacic
[Paper] [Code] [Talk]