Bai Liu (刘柏)

bailiu [at]   [CV]   [LinkedIn]   [GitHub]  

I am currently a Ph.D. student in Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology.

My research interests lie in learning and control problems in networked systems (data networks, logistic networks etc.), with application of reinforcement learning, stochastic optimization, inference methods.

Previously, in Summer 2016, I was fortunate enough to be selected into Stanford UGVR program and worked as a research assistant in Information Systems Laboratory, advised by Prof. Ayfer Özgür. In Spring 2016, I visited Imperial College London and worked at Centre for Transport Studies, advised by Prof. Ke Han. In 2016, I worked at Institute for Interdisciplinary Information Sciences, advised by Prof. Longbo Huang. In 2015, I worked in Institute of System Engineering, advised by Prof. Jianming Hu.



  • Bai Liu, Jianming Hu, Pan Gao, and Xudong Xie. Dynamic Traffic Guidance Generating Method on Variable Message Sign in Small and Medium-Sized Cities. 14th ITS Asia Pacific Forum. Full version accepted. Invited to do oral presentation.
  • Bai Liu, Ke Han, and Jianming Hu. Global Optimization Framework for Real-time Route Guidance via Variable Message Sign. Submitted to Transportmetrica A. Currently under review.   [arXiv]
  • Bai Liu, Xiugang Wu, and Ayfer Özgür. Efficiently Reaching the Largest Wireless Capacity with the Fewest Relays. In preparation for submission.   [Poster]


  • Jianming Hu, Xin Pei, Bai Liu, et al. An Information Distribution Method of Variable Message Sign Based on Prediction Method. Chinese Invention Patent. Publication Number: CN105303856A. Publication Date: 2016.02.03.

Software Copyright

  • Intelligent Networking Transportation Guidance System Platform [INGSP] V1.0. Computer Software Copyright. Registration Number: 2016SR252223. Date: 2016.06.01.

Selected Research Projects

Subnetwork Selection of Gaussian Relay Network   [Poster]

Bai Liu, Xiugang Wu, Ayfer Özgür

In wireless communication, some relays can be turned off while the optimal capacity still holds. We can apply traversing search approach to find the trimmed network, but its time cost might be unbearable. To solve the problem, we thoroughly study and rigorously prove properties of layered Gaussian relay network. We then develop and implement an algorithm that can find optimal global subnetwork exponentially faster.

Dynamic Transportation Network Modeling   [arXiv]

Bai Liu, Ke Han

Aiming at improving VMS (variable message sign) display strategy, we formulate transportation network model with feedback scheme. We then design optimization algorithm with linear decision rule and heuristic optimization approach. A simulation case study is conducted on a real-world test network in China, which shows the advantage of the proposed adaptive VMS display strategy.


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