Weiming Feng

Assistant Professor

The University of Hong Kong

Biography

I am Weiming Feng (凤维明), an Assistant Professor at the School of Computing and Data Science at The University of Hong Kong. Prior to this, I held postdoctoral positions at the Institute for Theoretical Studies at ETH Zürich, the Simons Institute at UC Berkeley, and the School of Informatics at The University of Edinburgh. I received my Ph.D. from Nanjing University in June 2021, where I was advised by Prof. Yitong Yin. Before that, I obtained my B.Eng. degree in Network Engineering from the University of Electronic Science and Technology of China in June 2016.

My research interest lies in theoretical computer science. Currently, I focus on sampling and counting algorithms. Classic topics include Markov chain Monte Carlo (MCMC) methods, spatial mixing of Gibbs distributions and computational phase transitions. I am also interested in their applications in statistics and learning theory.

Email: wfeng AT hku DOT hk & fwm1994 AT gmail DOT com

Here is my CV

Courses

Mini-Course: Mixing Time Analysis for MCMC Algorithms @ USTC, Jan 2025

Preprints

Weiming Feng, Hongyang Liu, Minji Yang (2025). Approximating the total variation distance between spin systems.

PDF

Xiaoyu Chen, Weiming Feng, Heng Guo, Xinyuan Zhang, Zongrui Zou (2024). Deterministic counting from coupling independence.

PDF

Xiaoyu Chen, Weiming Feng (2024). Rapid mixing via coupling independence for spin systems with unbounded degree.

PDF

Publications

Konrad Anand, Weiming Feng, Graham Freifeld, Heng Guo, Mark Jerrum, Jiaheng Wang (2025). Rapid mixing of the flip chain over non-crossing spanning trees. In SoCG 2025.

PDF

Arnab Bhattacharyya, Weiming Feng, Piyush Srivastava (2025). Approximating the Total Variation Distance between Gaussians. In AISTATS 2025.

Weiming Feng, Ce Jin (2025). Approximately counting knapsack solutions in subquadratic time. In SODA 2025.

PDF Ce's slides

Charlie Carlson, Xiaoyu Chen, Weiming Feng, Eric Vigoda (2025). Optimal mixing for randomly sampling edge colorings on trees down to the max degree. In SODA 2025.

PDF Xiaoyu's slides

Konrad Anand, Weiming Feng, Graham Freifeld, Heng Guo, Jiaheng Wang (2025). Approximate counting for spin systems in sub-quadratic time. TheoretiCS, Volume 4 (2025), Article 3, 1-27 (conference version in ICALP 2024).

PDF Jiaheng's slides

Weiming Feng, Heng Guo (2024). An FPRAS for two terminal reliability in directed acyclic graphs. In ICALP 2024.

PDF Slides@ICALP Slides@ADYN_SummerSchool Heng's slides Heng's talk

Weiming Feng, Liqiang Liu, Tianren Liu (2024). On deterministically approximating total variation distance. In SODA 2024.

PDF Slides@Shonan Tianren's slides

Weiming Feng, Heng Guo, Chunyang Wang, Jiaheng Wang, Yitong Yin (2023). Towards derandomising Markov chain Monte Carlo. In FOCS 2023.

PDF Slides@USTC Poster@MIT Heng's slides Heng's talk Jiaheng's slides Chunyang's slides

Weiming Feng, Heng Guo, Jiaheng Wang (2023). Swendsen-Wang dynamics for the ferromagnetic Ising model with external fields. Information and Computation (IANDC) 294: 105066 (2023).

PDF

Weiming Feng, Heng Guo, Mark Jerrum, Jiaheng Wang (2023). A simple polynomial-time approximation algorithm for the total variation distance between two product distributions. TheoretiCS, Volume 2 (2023), Article 8, 1-7 (conference version in SOSA 2023).

PDF Talk@Simons Poster@Zinal Slides@Zinal Slides@PKU Jiaheng's slides

Charilaos Efthymiou, Weiming Feng (2023). On the mixing time of Glauber dynamics for the hard-core and related models on G(n,d/n). In ICALP 2023.

PDF Slides@ICALP

Xiaoyu Chen, Weiming Feng, Yitong Yin, Xinyuan Zhang (2022). Optimal mixing for two-state anti-ferromagnetic spin systems. In FOCS 2022.

PDF Slides@FOCS

Weiming Feng, Heng Guo, Jiaheng Wang (2022). Improved bounds for randomly colouring simple hypergraphs. In RANDOM 2022.

PDF Jiaheng's slides

Weiming Feng, Heng Guo, Yitong Yin, Chihao Zhang (2022). Rapid mixing from spectral independence beyond the Boolean domain. ACM Transactions on Algorithms (TALG) 18(3): 28:1-28:32 (conference version in SODA 2021).

PDF Slides@SODA

Weiming Feng, Heng Guo, Yitong Yin (2022). Perfect sampling from spatial mixing. Random Structures & Algorithms (RSA) 61(4): 678-709.

PDF Slides@E-PIC

Xiaoyu Chen, Weiming Feng, Yitong Yin, Xinyuan Zhang (2021). Rapid mixing of Glauber dynamics via spectral independence for all degrees. SIAM Journal on Computing (SICOMP) special section for FOCS 2021.

PDF Talk@FOCS Poster@HALG Slides@FOCS Slides@Oxford Slides@UCSB

Weiming Feng, Heng Guo, Yitong Yin, Chihao Zhang (2021). Fast sampling and counting k-SAT solutions in the local lemma regime. Journal of the ACM (JACM) 68 (6), 1-42 (Conference version in STOC 2020).

PDF Talk@STOC Talk@IJTCS Slides@STOC Slides@ICT_CAS Heng's slides Heng's talk

Weiming Feng, Kun He, Yitong Yin (2021). Sampling constraint satisfaction solutions in the local lemma regime. In STOC 2021.

PDF Slides@BARC Kun's talk

Weiming Feng, Nisheeth K. Vishnoi, Yitong Yin (2021). Dynamic sampling from graphical models. SIAM Journal on Computing (SICOMP), 50(2), 350–381. (Confernece version in STOC 2019).

PDF Poster@STOC Slides@STOC Yitong's slides Yitong's talk

Weiming Feng, Thomas P. Hayes, Yitong Yin (2021). Distributed Metropolis sampler with optimal parallelism. In SODA 2021.

PDF Slides@SODA Yitong's slides

Weiming Feng, Kun He, Xiaoming Sun, Yitong Yin (2021). Dynamic inference in probabilistic graphical models. In ITCS 2021.

PDF Kun's talk

Weiming Feng, Yuxin Sun, Yitong Yin (2020). What can be sampled locally?. Distributed Computing (DC) 33, 227–253 (conference version in PODC 2017).

PDF Yitong's slides

Weiming Feng, Yitong Yin (2018). On local distributed sampling and counting. In PODC 2018.