CONTACT INFORMATION
Email: ivanlin9522@gmail.com
LinkedIn: https://www.linkedin.com/in/ivanlin9522/
EDUCATION
Ph.D. in Operations Research Georgia Institute of Technology, Atlanta, GA May 2024
Master of Science in Operations Research Columbia University, New York, NY Dec 2018
Bachelor of Economics in Financial Engineering Wuhan University, Wuhan, China Jun 2017
Bachelor of Engineering in Computer Science Wuhan University, Wuhan, China Jun 2017
INDUSTRY EXPERIENCE
C3.ai, Redwood City, CA
Senior Data Scientist Jun 2024 - Present
Morgan Stanley, New York, NY
Quant Strats Intern Jun 2023 - Aug 2023
Cardinal Operations, Beijing, China
Algorithm Engineer Intern Feb 2019 - Apr 2019
RESEARCH INTEREST
Simulation / Stochastic Optimization under input / distributional uncertainty
Risk-averse sequential decision making (MDPs, MAB, RL)
Combining RL + Optimization
PREPRINT AND WORKING PAPER
Utsav Dutta, Yifan Lin, and Zhaoyang Larry Jin. "Liner Shipping Network Design with Reinforcement Learning". In AAAI Conference on Artificial Intelligence PRL Workshop & AI+ORMS Bridge program. 2025.
Yingke Li, Yifan Lin, Enlu Zhou, and Fuming Zhang. "Bayesian Risk-averse Model Predictive Control with Consistency and Stability Guarantees". IEEE Transactions on Automatic Control, under Major Revision. 2024.
Yifan Lin, Yuxuan Ren, Jingyuan Wan, Massey Cashore, Jiayue Wan, Yujia Zhang, Peter Frazier, and Enlu Zhou. "Group Testing Enables Asymptomatic Screening for COVID-19 Mitigation: Feasibility and Optimal Pool Size Selection with Dilution Effects". 2020. [arXiv]
PUBLICATION
Alexander Shapiro, Enlu Zhou, Yifan Lin, and Yuhao Wang. "Episodic Bayesian Optimal Control with Unknown Randomness Distributions ". Operations Research, accepted. 2025. [arXiv]
Yifan Lin*, Yuhao Wang*, and Enlu Zhou. "Reusing Historical Trajectories in Natural Policy Gradient via Importance Sampling: Convergence and Convergence Rate". Operations Research. 2025.
Yifan Lin, and Enlu Zhou. "Approximate Bilevel Difference Convex Programming for Bayesian Risk Markov Decision Processes". In AAAI Conference on Artificial Intelligence (Oral). 2025.
Tianyi Liu*, Yifan Lin*, and Enlu Zhou. "Bayesian Stochastic Gradient Descent for Stochastic Optimization with Streaming Input Data". SIAM Journal on Optimization. 2024.
Yifan Lin, and Enlu Zhou. "Reusing Historical Observations in Natural Policy Gradient". In Proceedings of the Winter Simulation Conference. 2023.
Alexander Shapiro, Enlu Zhou, and Yifan Lin. "Bayesian Distributionally Robust Optimization". SIAM Journal on Optimization. 2023.
Yifan Lin, Yuxuan Ren, and Enlu Zhou. "Bayesian Risk Markov Decision Processes". In Advances in Neural Information Processing Systems (NeurIPS). 2022.
Yifan Lin*, Yuhao Wang*, and Enlu Zhou. ''Risk-averse Contextual Multi-armed Bandit Problem with Linear Payoffs''. Journal of Systems Science and Systems Engineering. 2022.
Yingke Li, Yifan Lin, Enlu Zhou and Fumin Zhang. ''Risk-Aware Model Predictive Control Enabled by Bayesian Learning''. In IEEE American Control Conference. 2022.
Tianyi Liu, Yifan Lin, and Enlu Zhou. "A Bayesian Approach to Online Simulation Optimization with Streaming Input Data". In Proceedings of the Winter Simulation Conference. 2021.
Yifan Lin, Enlu Zhou, and Aly Megahed. "A Nested Simulation Optimization Approach for Portfolio Selection". In Proceedings of the Winter Simulation Conference. 2020.
TEACHING EXPERIENCE
Graduate Teaching Assistant at Georgia Institute of Technology
Computational Data Analysis (ISYE 6740) Spring 2024
Stochastic Processes I (ISYE 6761) Fall 2023
Simulation (ISYE 6644-RSZ), Monte Carlo Methods (ISYE 6645-RSZ) Spring 2023
Basic Statistical Methods (ISYE 3030) Fall 2019, Spring 2020
Course Assistant at Columbia University
Introduction to Probability and Statistics (IEOR 4150) Spring 2018
AWARDS
18th INFORMS Workshop on DMDA Best Theoretical Paper Award Winner [2023]
NeurIPS Scholar Award [2022]
Kerry Clayton Fellowship [2019, 2020]
Stewart Fellowship [2019, 2020]
Shanshan Scholarship [2014]
TALKS
Liner Shipping Network Design with Reinforcement Learning
AAAI Conference on Artificial Intelligence PRL Workshop, 2025 [poster]
Approximate Bilevel Difference Convex Programming for Bayesian Risk Markov Decision Processes
AAAI Conference on Artificial Intelligence, 2025 [slide]
Data-driven Stohcastic Optimization in the Presence of Distributional Uncertainty
Job talk at Department of Data and Business Intelliegence, Shanghai Jiao Tong University, 2024 [slide]
Thesis Defense, Georgia Institute of Technology, 2024
Reusing Historical Observations in Natural Policy Gradient
Bayesian Risk Markov Decision Processes
NeurIPS, 2022 [slide]
Bayesian Stochastic Gradient Descent for Stochastic Optimization with Streaming Input Data
A Nested Simulation Optimization Approach for Portfolio Selection
SKILLS
Computer and Programming: Proficient in Python (pytorch, numpy, scipy etc.), Gurobi
Financial Certificate: CFA Level I Passed
PROFESSIONAL SERVICE
Reviewer for Operations Research, Management Science, Journal on Computing, Optimization Letters, NeurIPS, AISTATS, American Control Conference, Winter Simulation Conference
Session Chair for Simulation and Artificial Intelligence Track in Winter Simulation Conference 2023