Hai Le
Assistant Professor of Computer Science
Dr. Hai Le grew up in Ho Chi Minh city, Vietnam. He came to the United States to study at the University of Central Arkansas, where he completed both a bachelor's and a master's degree in computer science and discovered his passion for teaching. He earned a PhD in Computer Science at Georgia State University with Dr. Xiaolin Hu as his supervisor before joining Oxford College in fall 2023.
Le’s past research includes studies of data science and data mining on Wineinformatics (Dr. Bernard Chen’s work). His current research is in Simulation and Modeling, and his most recent work focuses on developing a framework to automatically discover steering behaviors for agent-based simulations by using Genetic Algorithm.
His current research also focuses on:
- Integrating AI models to the framework in order to provide more comprehensive results for steering models.
- Implementing a cloud-based simulation application that helps users to actively interact with simulation models.
Education
PhD| Georgia State University| 2023
MS| University of Central Arkansas| 2015
BS| University of Central Arkansas| 2013
Publications
Conferences
Le. H,. X. Hu. 2022. “Automated Model Discovery for Steering Behavior Simulation”.
Proceedings of the 2022 Annual Modeling and Simulation Conference.
Le. H,. X. Hu. 2020. “Extended Model Space Specification for Mobile Agent-Based Systems to Support Automated Discovery of Simulation Models”.
Proceedings of the 2020 Winter Simulation.
X. Hu,. H. Le. 2019. “Support Remote Collaboration in Virtual Computer Labs”.
ASEE 2019-the 126th Annual Conference and Exposition.
X. Hu, H .Le, AG. Bourgeois, Y. Pan. 2018. “Collaborative Learning in Cloud-based Virtual Computer Labs”.
2018 IEEE Frontiers in Education Conference (FIE).
M. Toulouse, H. Le, C. V. Phung, D. Hock. 2017. “Defense Strategies Against Byzantine Attacks in a Consensus-based Network Intrusion Detection System”.
Informatica.
B. Chen, H. Le, C. Rhodes, D. Che. 2016. “Understanding the Wine Judges and Evaluating the Consistency through White-box Classification Algorithms”.
Industrial Conference on Data Mining.
Journals
B. Chen, H. Le, T. Atkison, D. Che. 2017 “A Wineinformatics Study for White-box Classification Algorithms to Understand and Evaluate Wine Judges.”
Trans. Mach. Learn. Data Min.