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Quan Zhang

Assistant Professor
Department: Accounting and Information Systems
Office:
North Business Building
632 Bogue St Rm N253
East Lansing, MI 48824
Phone: (517) 355-7486
Areas of Expertise
  • Biography
    Dr. Quan Zhang received his Ph.D. degree from McCombs School of Business, the University of Texas at Austin in 2020. He graduated from Peking University with a bachelor's degree in Biology and Economics in 2012 and from the University of Minnesota with a master's degree (doctoral study) in Biostatistics in 2015.
  • Publications
    Article
    Zhang, Quan, Yanxun Xu, Mei-Cheng Wang, and Mingyuan Zhou. "Weibull Racing Survival Analysis with Competing Events, Left Truncation, and Time-Varying Covariates." The Journal of Machine Learning Research (2023): Vol.24(295) 1-43.
    Article
    Zhang, Quan, and Mingyuan Zhou. "Permuted and augmented stick-breaking Bayesian multinomial regression." The Journal of Machine Learning Research 18.1 (2017): 7479-7511.
    Article
    Zhang, Quan, Youssef Toubouti, and Bradley P. Carlin. "Design and analysis of Bayesian adaptive crossover trials for evaluating contact lens safety and efficacy." Statistical methods in medical research 26.3 (2017): 1216-1236.
    In proceedings
    Liu, Tianci, Tong Yang, Quan Zhang, and Qi Lei. "Optimization for Amortized Inverse Problems." International Conference on Machine Learning. PMLR, 2023.
    In proceedings
    Zhang, Yuxin, Yalei Du, Yuanyuan Zhang, and Quan Zhang. "Moral Hazard and Transparency in Peer-to-Peer Auto Insurance with Telematics." ICIS 2023 Proceedings. 19.
    In proceedings
    Zhang, Quan and Liu, Yixuan, "Understanding Patient Journeys with Telehealth: A Poisson-Factor-Marked Hawkes Process" (2022). ICIS 2022 Proceedings. 21. https://aisel.aisnet.org/icis2022/is_health/is_health/21
    In proceedings
    Pentland, Brian T., Inkyu Kim, Quan Zhang, Julie Ryan Wolf. "Effects of Concurrency in Complex Service Organizations: Evidence from Electronic Health Records." In International Conference on Business Process Management, pp. 149-160. Cham: Springer International Publishing, 2022.
    In proceedings
    Tianci Liu, Quan Zhang, and Qi Lei. "PANOM: Automatic Hyper-parameter Tuning for Inverse Problems." NeurIPS 2021 Workshop on Deep Learning and Inverse Problems. 2021.
    In proceedings
    Zhang, Quan, and Mingyuan Zhou. "Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks." Neural Information Processing Systems 31 (2018): 5002-5013.
  • Courses
    • ITM 885: Machine learning and optimization
    • STT 805: Statistical Modeling for Business Analytics
  • Links

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Front entrance to the Edward J. Minskoff Pavilion
Join us in welcoming 10 full-time faculty members new to five of our departments.