Jingling Li

(Li 李 [family name] Jingling 京玲 [given name])

I am a Ph.D. student in Computer Science at the University of Maryland, College Park, where I am fortunate to be advised by Prof. John Dickerson. Before that, I obtained my Bachelor’s degree in Computer Science and Mathematics from Bryn Mawr College. My research focuses on understanding and enriching the reasoning capabilities of current deep learning models. I believe having the ability to reason is an important and necessary step to achieving general intelligence.

I am currently interning at DeepMind under the supervision of Dr. Petar Veličković. We are investigating how to re-use the learned knowledge and skills in reinforcement learning. During my Ph.D., I have also worked closely with Prof. Jimmy Ba and Prof. Taiji Suziki when doing research internships at Vector Institute and RIKEN AIP. During my research, I also received great guidance from Prof. Don Perlis, Prof. Furong Huang, and Prof. Justin Brody.

I am looking for internship opportunities for summer 2022. Here is my CV. Let me know if you think I can be a good fit.

news

Sep 28, 2021 Our work on How Does a Neural Network’s Architecture Impact its Robustness to Noisy Labels has been accepted to NeurIPS 2021. :tada:
Sep 28, 2021 Our work on VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization has been accepted to NeurIPS 2021. :tada:
May 24, 2021 Started internship at DeepMind. :sparkles:

selected publications

  1. Neurips
    How Does a Neural Network’s Architecture Impact Its Robustness to Noisy Labels?
    Li, Jingling, Zhang, Mozhi, Xu, Keyulu, Dickerson, John, and Ba, Jimmy
    In Advances in Neural Information Processing Systems, 2021
  2. ICLR
    How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
    Xu, Keyulu, Zhang, Mozhi, Li, Jingling, Du, Simon S., Kawarabayashi, Ken-ichi, and Jegelka, Stefanie
    In International Conference on Learning Representations (Oral) 2021
  3. ICLR
    What Can Neural Networks Reason About?
    Xu, Keyulu, Li, Jingling, Zhang, Mozhi, Du, Simon S., Kawarabayashi, Ken-ichi, and Jegelka, Stefanie
    In International Conference on Learning Representations (Spotlight) 2020
  4. AISTATS
    Understanding Generalization in Deep Learning via Tensor Methods
    Li, Jingling, Sun, Yanchao, Su, Jiahao, Suzuki, Taiji, and Huang, Furong
    In International Conference on Artificial Intelligence and Statistics 2020