معرفی
Duong Nguyen serves as an Assistant Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University. His research integrates operations research, artificial intelligence, economics, and engineering to develop mathematical models for decision-making in large-scale networked systems including cloud/edge computing, smart grids, and crowdsourcing. He directs the NEMO research group focused on building intelligent multi-agent platforms through optimization and market design.
His educational credentials include:
- Ph.D. in Electrical and Computer Engineering from the University of British Columbia (2020)
- M.Sc. in Telecommunications from INRS, University of Quebec (2014)
- B.Sc. in Electronic and Telecommunications from Hanoi University of Science and Technology (2011)
Dr. Nguyen's research spans Operations Research, Artificial Intelligence, Decision-Making, Market Design, and Optimization with applications in edge computing, power systems, and network economics. His work emphasizes robust algorithms for uncertain environments and secure multi-agent platforms, recently expanding into quantum machine learning and privacy-preserving distributed systems. Current projects address decentralized federated learning, dynamic pricing, and EV charging network design.
Analysis of his publication record reveals consistent focus on distributed optimization techniques for edge/cloud systems, with increasing integration of game theory and quantum computing. His work demonstrates strong methodological innovation in handling spatio-temporal uncertainty while addressing practical challenges in energy flexibility and secure genomic computation.
His scientific recognition includes:
- Finalist for Best Student Paper Award at American Control Conference (ACC) 2024
- Finalist for Best Paper Award at International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt) 2023
Dr. Nguyen actively mentors Ph.D. students including Jiaming Cheng and Long Vu, with student-led research achieving significant recognition. His NEMO group collaborates with institutions including ETH Zurich on projects spanning autonomous driving, edge AI, and quantum optimization. Current research directions emphasize fair resource allocation, privacy-preserving learning, and dynamic pricing frameworks for next-generation networked systems.
