Active research programmes in intelligent operations research, artificial intelligence, decision analytics, and intelligent technology.
As a research center of artificial intelligence and intelligent operations, our researchers work across four complementary domains — intelligent operations research, AI, decision analytics, and intelligent technology — each grounded in rigorous methodology and oriented toward practical impact in industry and society.
Mathematical programming, stochastic optimization, robust optimization, and large-scale combinatorial methods — applied to scheduling, routing, network design, and resource allocation.
Machine learning, reinforcement learning, deep learning, and AI-augmented decision systems — from learning theory to deployed artificial intelligence applications in operations and control.
Predictive modelling, simulation, decision theory, and behavioural analytics — the science of converting data and models into reliable decisions.
Industry 4.0, smart manufacturing, technology adoption, and innovation systems — intelligent technology research bridging engineering and management.
Our research follows the principles of reproducibility, transparency, and open science. Where appropriate, we publish data, code, and computational notebooks alongside our research outputs. We support the FAIR data principles (Findable, Accessible, Interoperable, Reusable) and pre-registration of empirical studies where applicable.
We actively seek research partners — universities, industry labs, public agencies, and standards bodies — interested in intelligent operations research and AI. To discuss a potential collaboration, please contact our research office.