Liu, Yang

Postdoctoral fellow, SEAS, Harvard University.
Email: yangl@seas.harvard.edu
Office: MD 110
Phone: (734)-546-7375

Short bio:

    Hello. I'm currently a postdoctoral fellow at Harvard University. I am very fortunate to be hosted by Professor Yiling Chen. I also affiliate with the Center for Research on Computation and Society. I obtained my Ph.D degree from University of Michigan, Ann Arbor in 2015, where I was happily advised by Professor Mingyan Liu. Before that, I got my Bachelor degree from Shanghai Jiao Tong University, China in 2010; then I went to Ann Arbor and obtained my Master of Science in EE:Systems and Mathematics, in 2012 and 2014 respectively, both from University of Michigan.

Research interests:

    Currently my main research efforts are on strategic/incentive compatible machine learning and learning the wisdom of crowd. I am also interested in cybersecurity/reputation and decision making in networks.

Recent news:

    • How to gossip when rumors evolve? Check out our paper "Distributed Belief Averaging Using Sequential Observations" (with Ji Liu, Tamer Basar and Mingyan Liu, to appear at American Control Conference'17).
    • Our paper "Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices" (with Yiling) is accepted to AAAI'17.
    • "Doubly Active Learning: when Active Learning meets Active Crowdsourcing" is accepted to CrowdML at NIPS'16.
    • Our paper on using bandits to provide long term incentives for strategic regression(with Yiling) is accepted to NIPS'16.
    • Gave a tutorial on "Bandits in Crowdsourcing" at CMO Workshop: Models and Algorithms for Crowds and Networks (Aug. 28th to Sep. 2nd).
    • Our paper on learning to elicit effort from crowdsourcing workers(with Yiling) is accepted to IJCAI 16.
    • Our data breach prediction work (USENIX SEC15: Cloudy with a Chance of Breach ..) is featured in a WSJ Article.

Recent & selected publications (full list):

Patent:

    Mingyan Liu, Manish Karir, Michael Bailey, Yang Liu and Jing Zhang
    Rating Network Maliciousness and Comparing Network Maliciousness Through Similarity Analyses.
    Patent No. 62/026,349.

Presentations:

    A list of presentations I gave. Click here.

CV:

    Detailed bio. Click here.