Hongsong Yuan

BIO

Hongsong Yuan is a tenured associate professor at School of Information Management and Engineering, Shanghai University of Finance and Economics (SUFE). He received his bachelor’s degree in mathematics from Peking University in 2006, and obtained his PhD degree in operations research from Stanford University in 2012. He was visiting scholar to Stanford University in 2015-2016, and visiting scholar to University of Toronto in 2019.

Dr. Yuan’s research interest mainly include statistical learning, network analysis, and data-driven revenue management. His work was published in top journals such as IEEE Transactions on Information Forensics and Security, Journal of Machine Learning Research, Production and Operations Management, etc.

Education Experience

• Sep. 2006 – Apr. 2012 Stanford University Ph.D. in Operations Research
• Dec. 2007 – Jun. 2010 Stanford University M.S. in Financial Mathematics
• Sep. 2002 – Jul. 2006 Peking University B.S. in Mathematics

Work Experience

• May 2014 – present Shanghai University of Finance and Economics (SUFE), tenured associate professor
• Aug. 2015 – Sep. 2016 Visiting Scholar, Department of Statistics, Stanford University
• Mar. 2019 – Jun. 2019 Visiting Scholar, Rotman School of Management, University of Toronto
• Oct. 2013 – Apr. 2014 Shanghai Fuwei Inc., trader
• Aug. 2011 – Aug. 2013 London Capula Investment Services, quantitative researcher
• (E.g 2009.1-2010.2 Havard University Visiting Scholar)

Honors and Awards

Publications

1. S. Cao, S. He, R. Jiang, J. Xu and H. Yuan. Best Arm Identification in Batched Multi-armed Bandit Problems. [arXiv: 2312.13875].
2. O. Baron, C. Deng, S. He and H. Yuan. Forecasting using reference prices with exposure effect. Naval Research Logistics, 71(7): 1017-1034, 2024. F. Gao, Z. Ma and H. Yuan. Community Detection in Sparse Latent Space Models, Journal of Machine Learning Research, 23(322): 1-50, 2022.
3. Z. Wang, C. Yang, H. Yuan* and Y. Zhang. Aggregation bias in estimating log-log demand function. Production and Operations Management, 30(11): 3906-3922, 2021.
4. H. Yuan* and T. L. Lai. Stochastic approximation: From statistical origin to big-data, multidisciplinary applications. Statistical Science, 36(2): 291-302, 2021.
5. Z. Ma, Z. Ma and H. Yuan. Universal latent space model fitting for large networks with edge covariates. Journal of Machine Learning Research, 21(4): 1-67, 2020.
6. X. A. Chen, Z. Wang and H. Yuan. Optimal pricing for selling to a static multi-period newsvendor, Operations Research Letters, 45(5): 415-420, 2017.
7. H. Xing, H, Yuan* and S. Zhou. A mixtured localized likelihood method for GARCH models with multiple change-points, Review of Economics & Finance, 8(2): 44-60, 2017.
8. M. Baveja, H. Yuan and L. Wein. Asymptotic biometric analysis for large gallery sizes. IEEE Transactions on Information Forensics & Security, 5(4): 955-964, 2010.