Kaixun Hua
Postdoctoral Fellow
My current research focused on applying deterministic global optimization algorithms to solve typical machine learning problems. I am also interested in designing machine learning algorithms that utilize high-performance computing equipment such as GPU and HPC
Supervisor
Research Classification
Research Interests
Clustering
Global Optimization
Optimal Decision Tree
Research Methodology
k-means and hierarchical clustering
branch and bound
ultrametric
Research Options
I am available and interested in collaborations (e.g. clusters, grants).
I am interested in and conduct interdisciplinary research.
Publications
- Stochastic Optimal Device Sizing Model for Zero Energy Buildings: A Parallel Computing Solution (2022)
IEEE Transactions on Industry Applications, 58 (3), 3275--3284 - Water Price Prediction for Increasing Market Efficiency Using Random Forest Regression: A Case Study in the Western United States (2019)
Water, 11 (2), 228
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