معرفی
Dr. Kaixun Hua is an Assistant Professor in the Department of Industrial and Manufacturing Systems Engineering (IMSE) at the University of South Florida's College of Engineering. His research focuses on optimization-driven AI/ML, with expertise in clustering algorithms, decision trees, and machine learning applications in biorefining and energy systems. He holds a PhD in Computer Science from the University of Massachusetts, Boston, and completed postdoctoral research at the University of British Columbia's Institute of Applied Mathematics. Dr. Hua has been recognized with prestigious awards, including the NeurIPS 2022 Scholar Award and INFORMS 2022 Data Mining Best Paper Award. His work spans top-tier conferences such as NeurIPS, ICML, and ICNSE.
- Education: PhD in Computer Science (UMass Boston), Postdoc at UBC, BEng in Electrical and Computer Engineering (Shanghai Jiao Tong University).
Research interests include global optimization techniques for clustering, explainable AI models in biorefining, and scalable algorithms for large datasets. His publications emphasize solving complex optimization problems in engineering and environmental systems. Dr. Hua's awards reflect his contributions to machine learning and data mining. Current research trends involve advancing optimization algorithms for AI applications and sustainable energy solutions.
- Awards: NeurIPS Scholar Award (2022), INFORMS Best Paper (2022), BC System & Control Presentation Award (2021), UMass Outstanding Dissertation (PhD).
His advising and grant activities are not detailed in the provided text, but his work aligns with interdisciplinary collaborations in engineering and computer science. Dr. Hua’s lab focuses on developing innovative optimization methods for real-world challenges in data science and sustainable systems.
