Li Jing

Ph.D. candidate at MIT; Co-founder of Lightelligence Inc

Contact: ljing [at] mit.edu; li [at] lightelligence.ai

About

I am a senior Ph.D. student in MIT physics department. I work in Marin soljačić's physics-AI group.
My research interests include Deep Learning and Applied Physics.
I received my B.S. in Physics and B.A. in Economics (Dual Major) from Peking University in 2014.
I won 2010 International Physics Olympiad (IPhO) Gold Medal representing China.

I am a co-founder of Lightelligence Inc.

Academic Projects

Deep Learning

Rotational Unit of Memory

To Appear on Transactions of the Association for Computational Linguistics

PDF Poster Webpage Code-Tensorflow

Gated Orthogonal Recurrent Units: On Learning to Forget

To appear on Neural Computation

PDF Poster Webpage Code-Tensorflow

Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs

ICML 2017

PDF Poster Slides Webpage Code-Tensorflow Code-Theano

AI for Physics

Nanophotonic Particle Simulation and Inverse Design Using Artificial Neural Networks

Science Advance 2018

PDF Poster Code News Coverage

Major Award

41th International Physics Olympiad (IPhO) Gold Medal (2010)

Publications

Submitted

  • Migrating Knowledge between Physical Scenarios based on Artificial Neural Networks

    Yurui Qu*, Li Jing*, Yichen Shen, Min Qiu, Marin Soljačić
    arXiv:1809.00972

Published

  • Rotational Unit of Memory

    Rumen Dangovski*, Li Jing*, Marin Soljačić
    To Appear on Transactions of the Association for Computational Linguistics

  • Gated Orthogonal Recurrent Units: On Learning to Forget

    Li Jing*, Çağlar Gülçehre*, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljačić, Yoshua Bengio
    To Appear on Neural Computation

  • Nanophotonic Particle Simulation and Inverse Design Using Artificial Neural Networks

    John Peurifoy, Yichen Shen, Li Jing, Yi Yang, Fidel Cano-Renteria, Brendan Delacy, John D. Joannopoulos, Max Tegmark, Marin Soljačić
    Science Advance. Vol. 4, no. 6, eaar4206 (2018).

  • Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs

    Li Jing*, Yichen Shen*, Tena Dubček, John Peurifoy, Scott Skirlo, Yann LeCun, Max Tegmark, Marin Soljačić
    Proceedings of the 34th International Conference on Machine Learning (ICML) (2017)

  • Quantum cloning machines and the applications

    • Heng Fan, Yi-Nan Wang, Li Jing, Jie-Dong Yue, Han-Duo Shi, Yong-Liang Zhang, Liang-Zhu Mu
    Physics Reports 544 (3), 241-322 (2014)

  • Fitting magnetic field gradient with Heisenberg-scaling accuracy

    • Yong-Liang Zhang, Huan Wang, Li Jing, Liang-Zhu Mu, Heng Fan
    Scientific Reports 4, 7390 (2014)

  • Quantum network teleportation for quantum information distribution and concentration

    • Yong-Liang Zhang, Yi-Nan Wang, Xiang-Ru Xiao, Li Jing, Liang-Zhu Mu, VE Korepin, Heng Fan
    Physical Review A 87 (2), 022302 (2013)

  • Minimal input sets determining phase-covariant and universal quantum cloning

    • Li Jing, Yi-Nan Wang, Han-Duo Shi, Liang-Zhu Mu, Heng Fan
    Physical Review A 86 (6), 062315 (2012)

  • General quantum key distribution in higher dimension

    • Zhao-Xi Xiong, Han-Duo Shi, Yi-Nan Wang, Li Jing, Jin Lei, Liang-Zhu Mu, Heng Fan
    Physical Review A 85 (1), 012334 (2012)

  • Non-compression of quantum phase information

    • Yi-Nan Wang, Han-Duo Shi, Li Jing, Zhao-Xi Xiong, Jin Lei, Liang-Zhu Mu, Heng Fan
    Journal of Physics A: Mathematical and Theoretical 45 (2), 025304 (2012)

  • Unified universal quantum cloning machine and fidelities

    • Yi-Nan Wang, Han-Duo Shi, Zhao-Xi Xiong, Li Jing, Xi-Jun Ren, Liang-Zhu Mu, Heng Fan
    Physical Review A 84 (3), 034302 (2011)