Hung Q. Nguyen

Hung Q. Nguyen

Researcher in Operations Research and Applied AI

Advanced AI Innovation Center, Hitachi, Ltd.

My research focuses on queueing theory, stochastic service systems, strategic behavior, and optimization. I am particularly interested in systems where users react to congestion and where mathematical models must ultimately support decisions under uncertainty and operational constraints.

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Last updated: July 2026

About

I received a Ph.D. in Policy and Planning Sciences from the University of Tsukuba and an M.A. in Economics from Tohoku University. My academic work studies stochastic systems and strategic decision-making, especially queueing and matching systems. In industrial research, I work on optimization, forecasting, simulation, and data-driven decision support for operational problems.

The common theme is simple: how should we understand and improve systems in which uncertainty, limited capacity, and human or organizational decisions interact?

Research Interests

Queueing games and strategic behavior

Equilibrium behavior, externalities, information, and system design when users react to congestion.

Stochastic service systems

Performance analysis of queues and matching systems, with emphasis on waiting, reliability, and uncertain system dynamics.

Optimization and decision support

Mathematical optimization, simulation, forecasting, reinforcement learning, and other learning methods for operational decisions in real systems.

Selected Publications

Complete publication list →

Selected Applied Research

Industrial work is described at a deliberately high level. Client identities, proprietary data, operational parameters, and non-public performance results are not disclosed.

Inventory optimization at scale

Scalable model selection and optimization for heterogeneous multi-item inventory systems.

More projects →

News

  • 2026.09Granted the 16th Research Encourage Award for Young Researchers of the Operations Research Society of Japan.
  • 2026.07Our paper “Facial Recognition Ticket Gates in Railway Stations: A Queueing Model for Exceptions and Passenger Congestion” was accepted for COMOSA 2026 in Hanoi, Vietnam; proceedings publication forthcoming.
  • 2026.05New paper titled " Learning to allocate automated speed enforcement: An observational policy optimization framework with reinforcement learning" published in Case Studies on Transport Policy.
  • 2025.12New paper titled "Subgame perfect Nash equilibrium analysis in a two-population strategic matching queue with nonzero matching times" published in Operations Research Letters.

Contact

Email: nguyen.quoc.hung.xu [at] alumni.tsukuba.ac.jp