Home Original page

Lei Chen 陈磊

Research

My previous research interests included

  • Understanding Transformer-based LLMs

  • Deep Learning Theory

  • Representation Learning on Graphs

Education

  • Ph.D., Computer Science, New York University, Sep. 2020 - May 2025

  • M.S., Computer Science, New York University, Aug. 2018 - May 2020

  • B.Eng., Civil Engineering, Tsinghua University, Aug. 2012 - July 2016

Publications

(* indicates joint authorship)

  • Distributional Associations vs In-Context Reasoning: A Study of Feed-forward and Attention Layers
    Lei Chen, Joan Bruna, Alberto Bietti
    ICLR 2025 arxiv

  • Beyond the Edge of Stability via Two-step Gradient Updates
    Lei Chen, Joan Bruna
    ICML 2023 arxiv poster

  • On Graph Neural Networks versus Graph-Augmented MLPs
    Lei Chen*, Zhengdao Chen*, Joan Bruna
    ICLR 2021 code arxiv

  • Learning the Relevant Substructures for Tasks on Graph Data
    Lei Chen, Zhengdao Chen, Joan Bruna
    ICASSP 2021

  • Can Graph Neural Networks Count Substructures?
    Zhengdao Chen, Lei Chen, Soledad Villar, Joan Bruna
    NeurIPS 2020 code arxiv

  • Attributed Random Walk as Matrix Factorization
    Lei Chen, Shunwang Gong, Joan Bruna, Michael Bronstein
    Graph Representation Learning Workshop NeurIPS 2019 code paper

  • SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator
    Shunwang Gong, Lei Chen, Michael Bronstein, Stefanos Zafeiriou
    Geometry Meets Deep Learning Workshop ICCV 2019 code paper

  • On the Equivalence between Graph Isomorphism Testing and Function Approximation with GNNs
    Zhengdao Chen, Soledad Villar, Lei Chen, Joan Bruna
    NeurIPS 2019 code arxiv

Professional Service

  • Journal reviewer: JMLR, TMLR, IEEE TPAMI

  • Conference reviewer: NeurIPS 2021-2023, ICLR 2022-2023, ICML 2022-2024