Junming Yin

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I work at the intersection of statistics, machine learning, and business, focusing on the design of novel statistical models and computational algorithms for solving cutting-edge business problems. I received a Ph.D. in Computer Science and an M.A. in Statistics from UC Berkeley (advisors: Michael I. Jordan and Yun S. Song).

Research Interests:

  • Methodologies: statistical learning, probabilistic modeling and variational inference, nonparametric and high-dimensional statistics, deep generative models

  • Applications: business decision making, dynamic consumer behavior, matching markets, crowdsourcing, healthcare

Student Mentees:

  • Jerry Luo (Ph.D. in Math; now at Google), Xi Wang (CS; now Ph.D. student at UMass), Zisu Wang (MIS; ongoing)

I am looking for a postdoc interested in the intersection of business technologies and statistical learning. If interested, please email me a CV.

Selected Recent Papers

  • Z. Wang, L. Guo, J. Yin, and S. Li.
    Bandit Learning in Many-to-One Matching Markets.
    ACM International Conference on Information and Knowledge Management (CIKM), 2022.

Contact twitter

  • Email: junmingy[at]cmu[dot]edu

  • Mailing Address:
    5000 Forbes Avenue
    TEP - Tepper School of Business
    Pittsburgh, PA 15213