Department of Computer Science
The College of William & Mary
Bio: I am an Assistant Professor in the Department of Computer Science at the College of William & Mary. Prior to joining W&M, I spent two years as a quant research (algo trading) in Two Sigma Investments. I received my Ph.D. from Harvard (2012), and spent two years as a postdoc at Princeton University. I graduated from the Hong Kong University of Science and Technology with a B.Eng in Computer Science and a minor in Mathematics.
My research focuses on building algorithmic foundations for large-scale end-to-end machine learning solutions. Our research program consists of two thrusts:
1. Computational learning theory for graphs and time series: we design computationally tractable, statistically sound, and practically relevant learning algorithms for graphs and times series data.
2. Large-scale learning system design and delivery: we design algorithmic tools to power large-scale machine learning systems. Specifically, we design low-cost systems that can train on peta-scale data, and systems that can deliver high-throughput machine learning services.
Funding & Industrial Collaborations
Our works are currently supported by both government and industrial funds:
1. NSF-1755769: CRII: III: Theory and Practice of Learning on Graphs
2. Rutherford Fellowship at the Alan Turing Institute (UK)
3. Activision/Blizzard gift
Selected Publications (Complete list)
DeepDecision: A Mobile Deep Learning Framework for Edge Video Analytics
Xukan Ran, Haoliang Chen, Xiaodan Zhu, Zhenming Liu, Jiasi Chen.
In the IEEE Conference on Computer Communications (INFOCOM), 2018
From which world is your graph?
Cheng Li, Felix Wong, Zhenming Liu and Varun Kanade.
In the 30th Advances in Neural Information Processing Systems, NIPS 2017
On the efficiency of social recommender networks? [best paper runner-up]
Felix Ming-Fai Wong, Zhenming Liu, Mung Chiang.
In the IEEE Conference on Computer Communications (INFOCOM), 2015
The diffusion of networking technologies
Sharon Goldberg and Zhenming Liu
In ACM-SIAM Symposium on Discrete Algorithms (SODA), 2013
Why Steiner-tree type algorithms work for community detection
Mung Chiang, Henry Lam, Zhenming Liu, Vince Poor
In Journal of Machine Learning Research W&CP (AISTATS), 2013
An efficient implementation of one big switch abstraction in Software Defined Networks
Nanxi Kang, Zhenming Liu, Jennifer Rexford, David Walker
In ACM International Conference on emerging Networking Experiments and Technologies (CoNEXT), 2013 [abstract | full paper]
Distributed non-stochastic experts
Varun Kanade, Zhenming Liu, Bozidar Radunovic
In Neural Information Processing Systems Conference (NIPS), 2012
Continuous distributed counting for Non-monotonic streams
Zhenming Liu, Bozidar Radunovic, Milan Vojnovic
In ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS), 2012
Chernoff-Hoeffding Bounds for Markov Chains: Generalized and Simplified
Kai-Min Chung, Henry Lam, Zhenming Liu, Michael Mitzenmacher
In Symposium on Theoretical Aspects of Computer Science (STACS), 2012