Huan Li (李寰)

 

Ph.D. student
Department of Computer and Information Science
University of Pennsylvania

Email:  huanli<at>cis<dot>upenn<dot>edu

I am a PhD student in Computer Science at University of Pennsylvania, co-advised by Profs. Anindya De and Sanjeev Khanna. My current research interests lie in the design and analysis of sublinear algorithms for processing massive datasets, especially those with graph structures. I am particularly interested in designing algorithms using spectral graph theory as a tool. More broadly, I am also interested in other topics related to algorithm design including continuous/combinatorial optimization, numerical linear algebra, unsupervised learning, and network science. Before coming to Penn, I obtained my bachelor's and master's degrees in Computer Science from Fudan University, where I was advised by Prof. Zhongzhi Zhang.

Personal: My partner Fangqian Wu is a PhD student studying Economics at Drexel University.

Selected Publications

(See my Google Scholar page for a full list)

(Authors are ordered alphabetically)

  • Detecting Low-Degree Truncation.

    • Anindya De, Huan Li, Shivam Nadimpalli, and Rocco Servedio.

    STOC 2024. (arXiv)

  • Parallel Approximate Maximum Flows in Near-Linear Work and Polylogarithmic Depth.

    • Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil, Chen Wang, Nathan White, and Peilin Zhong.

    SODA 2024. (arXiv)

  • On Regularity Lemma and Barriers in Streaming and Dynamic Matching.

    • Sepehr Assadi, Soheil Behnezhad, Sanjeev Khanna, and Huan Li.

    STOC 2023. (arXiv).

  • Sublinear Algorithms for Hierarchical Clustering.

    • Arpit Agarwal, Sanjeev Khanna, Huan Li, and Prathamesh Patil.

    NeurIPS 2022. (arXiv).

  • On Weighted Graph Sparsification by Linear Sketching.

    • Yu Chen, Sanjeev Khanna, and Huan Li.

    FOCS 2022. (arXiv).

  • Nearly Tight Bounds for Discrete Search under Outlier Noise.

    • Anindya De, Sanjeev Khanna, Huan Li, and Hesam Nikpey.

    SOSA 2022. (conf).

  • Approximate optimization of convex functions with outlier noise.

    • Anindya De, Sanjeev Khanna, Huan Li, and Hesam Nikpey.

    NeurIPS 2021. (conf).

  • An Efficient PTAS for Stochastic Load Balancing with Poisson Jobs.

    • Anindya De, Sanjeev Khanna, Huan Li, and Hesam Nikpey.

    ICALP 2020. (arXiv).

  • Hermitian matrices for clustering directed graphs: insights and applications.

    • Mihai Cucuringu, Huan Li, He Sun, and Luca Zanetti.

    AISTATS 2020. (arXiv).

  • Maximizing the Number of Spanning Trees in a Connected Graph.

    • Huan Li, Stacy Patterson, Yuhao Yi, and Zhongzhi Zhang.

    IEEE Transactions on Information Theory 66(2): 1248-1260 (2020). (arXiv).

  • Hermitian Laplacians and a Cheeger inequality for the Max-2-Lin problem.

    • Huan Li, He Sun, and Luca Zanetti.

    ESA 2019. (arXiv).

  • Current Flow Group Closeness Centrality for Complex Networks.

    • Huan Li, Richard Peng, Liren Shan, Yuhao Yi, and Zhongzhi Zhang.

    WWW 2019. (arXiv | Julia code).

  • Spectral Subspace Sparsification.

    • Huan Li and Aaron Schild.

    FOCS 2018. (arXiv).

  • Kirchhoff Index As a Measure of Edge Centrality in Weighted Networks: Nearly Linear Time Algorithms.

    • Huan Li and Zhongzhi Zhang.

    SODA 2018. (arXiv).

  • Maximum matchings in scale-free networks with identical degree distribution.

    • Huan Li and Zhongzhi Zhang.

    Theoretical Computer Science 675 (2017): 64-81. (arXiv).

    Talks

  • Parallel Approximate Maximum Flows in Near-Linear Work and Polylogarithmic Depth
  • On Regularity Lemma and Barriers in Streaming and Dynamic Matching
  • On Weighted Graph Sparsification by Linear Sketching
  • Nearly Tight Bounds for Discrete Search under Outlier Noise
  • Approximate optimization of convex functions with outlier noise
  • An Efficient PTAS for Stochastic Load Balancing with Poisson Jobs
  • Spectral Subspace Sparsification
  • Kirchhoff Index As a Measure of Edge Centrality in Weighted Networks: Nearly Linear Time Algorithms