Tonghua Lin

I am a Ph.D. candidate in Supply Chain Management at Rutgers Business School, advised by Weiwei Chen. I study how firms make operational decisions under financial and behavioral constraints, combining stochastic modeling and optimization with empirical analysis. My current work spans three areas: the operations–finance interface (inventory decisions under bankruptcy risk, valuation of cash conversion systems), platform logistics (order assignment with heterogeneous crowdsourced drivers), and healthcare operations (workforce structure and service quality in dialysis care). Papers from this work are under revision at the Journal of Operations Management and the European Journal of Operational Research. I approach research as a builder. My strength is turning models into working systems: implementing large-scale optimization algorithms, accelerating computation (including GPU-based dynamic programming), and constructing data pipelines from messy real-world sources. I am also an active adopter of AI tooling — designing agent workflows and reusable skills for LLM-based agents — and I bring this into both my research and my teaching. Core Competencies: Optimization (Mixed Integer Programming, Branch-and-Price, Dynamic Programming), Markov Decision Processes (MDP), Machine Learning, Causal Inference, Software Design & Engineering. Collaboration: Actively welcoming research collaborators and coauthors.