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 research interests focus on developing highly efficient algorithms for processing massive datasets. I am passionate about designing novel algorithmic techniques that can handle the unprecedented scale of modern data while using significantly fewer computational resources than traditional approaches. This includes creating sophisticated data compression and summarization methods, developing sublinear algorithms that use less space/time/communication than the input size, and establishing new theoretical frameworks that enable breaking through previous efficiency barriers.

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 wife 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)

  • Near-optimal Linear Sketches and Fully-Dynamic Algorithms for Hypergraph Spectral Sparsification.

    • Sanjeev Khanna, Huan Li, and Aaron (Louie) Putterma.

    STOC 2025. (arXiv)

  • 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