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Junyi Liu, Assistant Professor


Name: Junyi Liu Phone: +86-10-62787546 E-mail: Fax: Address: Room 506A, Shunde Building, Tsinghua University Homepage:


Honors and Awards

1. Finalist, Dupacova-Prekopa Best Student Paper Prize in Stochastic Programming, 2019.
(Awarded by the Committee on Stochastic Programming for the paper “Two-stage stochastic programming with linearly bi-parameterized recourse functions". Committee on Stochastic Programming selects 4 finalists every 3 years in recognizing the outstanding student-authored papers in stochastic programming.)
2. Second place, Daniel J. Epstein Institute Research Festival, University of Southern California, 2019.
3. Viterbi Graduate School Graduate Fellowship, University of Southern California, 2015.    

Educational Background

Ph.D. Industrial and Systems Engineering, University of Southern California, 2019
B.S., Statistics, School of Gifted Young, University of Science and Technology of China, 2015    

Employment History

Assistant Professor, Industrial Engineering, Tsinghua University, April 2020– Now
Postdoc Associate, Industrial and Systems Engineering, University of Southern California, Sep 2019 - March 2021    


Foundations of Nonlinear Programming (an undergraduate course, 2021 fall semester)    

Research Interests

Data-driven models and methodologies for decision-making under the uncertainty.
Methdologies: stochastic optimization, nonsmooth and nonconvex optimization, distributionally robust optimization, risk measure minimization, chance-constrained stochastic programming.
Applications: machine learning, supply chain management, revenue management, risk management.    



1. Cui, Y., Liu,  J. and Pang, J-S.* (2021) Nonconvex and Nonsmooth Approachs for Affine Chance Constrained Stochastic Programs. Submitted.

2. Liu,  J.* and Pang, J-S. (2022) Risk-based Robust Statistical Learning By Stochastic Difference-of-Convex Value-Function Optimization. Operations Research.

3. Liu,  J.*, Cui, Y., and Pang, J-S. (2022) Solving Nonsmooth and Nonconvex Compound Stochastic Programs with Applications to Risk Measure Minimization.  Mathematics of Operations Research.

4. Liu,  J.*, Li, G. and Sen, S. (2021) Coupled Learning Enabled Stochastic Programming with Endogenous Uncertainty. Mathematics of Operations Research.

5. Liu,  J. and Sen, S.* (2020) Asymptotic Convergence Rate of Stochastic Decomposition Algorithm for Two-stage Stochastic Quadratic Programming. SIAM Journal on Optimization.

6. Liu,  J., Cui, Y.*, Pang, J-S. and Sen, S. (2020) Two-stage Stochastic Programming with Linearly Bi-parameterized Recourse Functions. SIAM Journal on Optimization. (Finalist of 2019 Dupacova-Prekopa Best Student Paper Prize in Stochastic Programming)

7. Deng, Y., Liu,  J. and Sen, S.* (2018) Coalescing Data and Decision Sciences for Analytics, INFORMS TutORials in Operations Research.


Department of Industrial Engineering, Tsinghua University
Phone: 010-62772989
Address:Shunde Building, Tsinghua University, Beijing 100084

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