Lulu (Luke) Gong

Email: lulu.gong@yale.edu

Address: 1121A, 100 College St, New Haven, CT, USA

I am a Swartz Postdoc Fellow of Theoretical and Computational Neuroscience working with Dr. Shreya Saxena at Wu Tsai Institute, Yale University. From 2022.02 to 2024.08, I was a Postdoc Research Associate working with Dr. ShiNung Ching at the Department of Electrical and Systems Engineering, Washington University in St. Louis. I received my PhD degree in System and Control in 2022 from the University of Groningen, the Netherlands, advised by Prof. Ming Cao. Before that, I obtained Bachelor’s and Master’s degrees in Mechanical and Electrical Engineering respectively in China.

My research interests lie in the emerging field of Neuro-AI, specifically the intersection of Modeling and Learning of Neural Dynamics, by using tools from Neural Networks Theory, Dynamical Systems Theory and Analysis, and Game/Decision Theory & Complex Network Science. I am particularly interested in the applications in Cognitive Science (such as learning, memory, and decision-making) and Nature/Machine Intelligence.

news

Jan 26, 2026	Our paper “Learning Mixtures of Linear Dynamical Systems via Hybrid Tensor-EM Method” was accepted to ICLR 2026.
Jan 11, 2026	Co-authored paper “Multitimescale Computation by Astrocytes” was submitted for review. Check out the preprint.
Nov 16, 2025	I attended the Society of Neuroscience Conference in San Diego, Nov 15-19, and presented our work “Towards Inference and Learning of Neural Dynamics at Multiple Timescales”.
Oct 25, 2025	I submitted a paper on “Learning Mixtures of Linear Dynamical Systems (MoLDS) via Hybrid Tensor-EM Method” for neural data analysis.
Jun 11, 2025	I attended The 11th Workshop on Statistical Analysis of Neural Data (SAND) at the Simons Flatiron Institute and presented our work “Towards Inference and Learning of Neural Dynamics at Multiple Timescales”.
Jan 23, 2025	I attended NSF Workship on Reinforcement Learning at Harvard University and presented our co-authored poster “Multi-agent reinforcement learning for modeling animal social behaviors in cooperative tasks”.
Jan 08, 2025	Happy New Year, 2025! Our paper “Strong anti-Hebbian plasticity alters the convexity of network attractor landscapes” is accepted for publication in IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
Oct 10, 2024	I attended the Society of Neuroscience Conference 2024 (10.05-10.09) in Chicago and presented our work on the feedback modulation of Hebbian plasticity enabling efficient learning in Hopfield networks. This travel was supported partially by the Travel Award from the Wu Tsai Institute at Yale.

selected publications

ICLR

Learning Mixtures of Linear Dynamical Systems (MoLDS) via Hybrid Tensor-EM Method

Lulu Gong, and Shreya Saxena

The Fourteenth International Conference on Learning Representations, 2026

Bib

@article{gong2025molds,
  title = {Learning Mixtures of Linear Dynamical Systems (MoLDS) via Hybrid Tensor-EM Method},
  author = {Gong, Lulu and Saxena, Shreya},
  year = {2026},
  publisher = {The Fourteenth International Conference on Learning Representations},
  url = {https://openreview.net/forum?id=1GkzDABbME},
  journal = {The Fourteenth International Conference on Learning Representations}
}

PLoS-CB

Astrocytes as a mechanism for contextually-guided network dynamics and function

Lulu Gong, Fabio Pasqualetti, Thomas Papouin, and 1 more author

PLOS Computational Biology, 2024

Bib PDF

@article{gong2024astrocytes,
  title = {Astrocytes as a mechanism for contextually-guided network dynamics and function},
  author = {Gong, Lulu and Pasqualetti, Fabio and Papouin, Thomas and Ching, ShiNung},
  journal = {PLOS Computational Biology},
  volume = {20},
  number = {5},
  pages = {e1012186},
  year = {2024},
  publisher = {Public Library of Science San Francisco, CA USA},
  doi = {10.1371/journal.pcbi.1012186},
  url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1012186},
}

Automatica

Limit cycles analysis and control of evolutionary game dynamics with environmental feedback

Lulu Gong, Weijia Yao, Jian Gao, and 1 more author

Automatica, 2022

Bib PDF

@article{gong2022limit,
  title = {Limit cycles analysis and control of evolutionary game dynamics with environmental feedback},
  author = {Gong, Lulu and Yao, Weijia and Gao, Jian and Cao, Ming},
  journal = {Automatica},
  volume = {145},
  pages = {110536},
  year = {2022},
  publisher = {Elsevier},
  doi = {doi.org/10.1016/j.automatica.2022.110536},
  url = {https://www.sciencedirect.com/science/article/pii/S0005109822003971},
}

IEEE-TNNLS

Strong anti-Hebbian plasticity alters the convexity of network attractor landscapes

Lulu Gong, Xudong Chen, and ShiNung Ching

IEEE Transactions on Neural Networks and Learning Systems, 2025

Bib

@article{gong2025strong,
  title = {Strong anti-Hebbian plasticity alters the convexity of network attractor landscapes},
  author = {Gong, Lulu and Chen, Xudong and Ching, ShiNung},
  year = {2025},
  journal = {IEEE Transactions on Neural Networks and Learning Systems},
  url = {https://ieeexplore.ieee.org/document/10981480}
}