Ph.D. CandidateSupply Chain ManagementRutgers Business School
Tonghua Lin
I am a researcher specializing in data-driven operations management. Currently pursuing my Ph.D. at Rutgers University, I integrate analytical modeling with empirical research to solve complex challenges in logistics and platform economy.
My work spans from formulating Markov Decision Processes (MDP) for inventory control to applying econometric methods and Machine Learning on large-scale datasets to analyze labor supply and driver behaviors. I am passionate about bridging theoretical rigor with practical, data-backed solutions for real-world business problems.
Core Competencies: Python, Gurobi, Machine Learning, Markov Decision Processes (MDP), Causal Inference, Stata.
Status: Actively seeking Summer 2026 Internship opportunities in Logistics and Algorithm Design.
Advisor: Weiwei Chen

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Research Highlights
Selected projects
Optimizing Order Assignments in On-Demand Delivery with Behavior Heterogeneity of Crowdsourced Drivers
Authors: Xinyi Huang, Tonghua Lin, Weiwei Chen, Hongyan Dai
Status: In Progress
Branch & Price algorithm with XGBoost for driver behavior prediction. Achieved 62-71% reduction in delivery delays.
PythonGurobiXGBoostOptimizationColumn Generation
Oversupply of Fissured Workforce and Operational Inefficiency: Evidence from Grab-Mode Competition in Food Delivery
Authors: Tonghua Lin, Weiwei Chen
Status: In Progress
Analyzed 650,000+ delivery records using trajectory reconstruction and causal inference (R² = 0.98).
Data AnalyticsStataCausal InferenceEconometrics
Modeling Liquidity and Survival: Inventory Speculation and Bankruptcy Risk Analysis
Authors: Tonghua Lin, Weiwei Chen, Xiaowei Xu
Status: In Progress
MDP model with CUDA-accelerated DP for financial constraint optimization. Proved log-concavity of value function.
Dynamic ProgrammingCUDAMathematical ProofSupply Chain Finance