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Applied Probability Systems Lab
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The lab analyzes uncertain services using probabilistic models.
AboutAbout the lab
Reading uncertain services through probabilistic models.
The Applied Probability Systems Lab studies real-world service systems using applied probability theory, stochastic processes, and operations research.
Because service systems contain uncertain elements, the lab represents them with probabilistic models and analyzes them, then uses that understanding of system behavior to provide guidelines for areas such as design.
In addition to probabilistic models of communication systems, data centers, call centers, and logistics services, the lab works on theoretical research that widens the range of probabilistic models that can be analyzed, as well as on numerical solution methods.
The lab welcomes students who want to solve real-world problems with mathematics, and those who want to do research that makes use of mathematics.
Key terms
- Queueing theory
- A theory that mathematically examines the relationship between the amount of a shared resource, such as the number of chairs in a library, and how crowded its use is
- Stochastic process
- A way of describing movement that changes randomly over time, used as a mathematical model of services that share resources
- Asymptotic analysis
- A method that examines multidimensional stochastic processes in the form of fluid limits and diffusion limits, in order to rigorously understand parts of a system's behavior
NewsLab news
Paper by a doctoral student accepted to the international conference IFIP Performance 2026
Paper co-authored by doctoral students wins the Best Paper Award at CITA2026
Paper by a doctoral student accepted to the international journal Methodology and Computing in Applied Probability
Paper by the professor accepted to the international journal Journal of Systems Scalability
Master's student wins a Research Encouragement Award from the Queueing Research Group
ResearchResearch themes
The Applied Probability Systems Lab represents the uncertain elements of real-world service systems with probabilistic models and analyzes them, aiming to understand system behavior and to develop guidelines such as for design. So far, it has proposed and analyzed probabilistic models of communication systems, data center systems, call centers, and logistics services.
*Illustrative imageProbabilistic models of resource-sharing systems
The lab uses queueing theory to mathematically analyze services shared by many people, such as roads and libraries. Its work includes models that incorporate customer retrials and abandonment, as well as energy-saving data centers, 5G, and redelivery in logistics.
*Illustrative imageApplied stochastic processes
The lab explores ways to efficiently solve stochastic processes, which are mathematical models of resource-sharing services, by making use of the characteristics of each problem. It works on the asymptotic analysis of multidimensional stochastic processes and is also interested in modeling systems with machine learning.
MembersFaculty
The members of the Applied Probability Systems Lab consist of faculty members, doctoral, master's, and undergraduate students, and research students.As of 2026
- ProfessorPhung-Duc Tuan
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Le torrette con i bocchettoni per il raffreddamento ad aria dei server in un data center attivo dal 2015” Lapalmauz / CC BY-SA 4.0 (cropped)
- Probabilistic models of resource-sharing systems: “THSR Taipei Station ticket counter at 1F 20070109” 台灣少年 / CC BY-SA 3.0 (cropped)
- Applied stochastic processes: “BalticServers data center” BalticServers.com / CC BY-SA 3.0 (cropped)
- Related lab (吉瀬研究室): “CLR-2 logistics, Supply, transition through planning 130828-M-ZB219-309” Cpl. Paul Peterson / Public domain (cropped)
- Related lab (有馬澄佳研究室): “002 Production line - car assembly line in General Motors Manufacturing Poland - Gliwice, Poland” Marek Ślusarczyk (Tupungato) Photo portfolio / CC BY 3.0 (cropped)
- Related lab (サービス工学・実験経済学・計量経済学
（髙橋 裕紀） ): “Customer Service counter, Pimpama Railway Station, Old Pacific Highway, Gold Coast P1130327” John Robert McPherson / CC0 (cropped) - Related lab (シームラボ): “Grounds & facilities - data analysis office, UNIVAC 1106” U.S. Army Natick Soldier Systems Center / CC BY 4.0 (cropped)
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