معرفی
Hossein Moradi Rekabdarkolaee is an Associate Professor in the Department of Mathematics and Statistics at South Dakota State University (SDSU), affiliated with the Jerome J. Lohr College of Engineering. His research focuses on advanced statistical methodologies, including big data analytics, machine learning, spatial and spatiotemporal statistics, and their applications in environmental science, public health, and electrical engineering. He holds a Ph.D. in System Modeling and Analysis from Virginia Commonwealth University, alongside degrees in statistics and operations research.
Education:
- B.S. in Statistics
- M.S. in Mathematical Statistics (spatial statistics)
- M.S. in Operations Research
- Ph.D. in System Modeling and Analysis (Virginia Commonwealth University)
Research Interests:
- Machine Learning and Deep Learning Algorithms
- Spatiotemporal Data Modeling for Renewable Energy and Environmental Systems
- Public Health Disparities in Chronic Diseases
- Dimension Reduction Techniques for High-Dimensional Data
- Functional and Multivariate Statistical Analysis
Notable Achievements:
- Recipient of the 2024 Outstanding Early-Carer Researcher Award from SDSU's Lohr College of Engineering
- Editor’s Pick recognition for impactful work in Plant Health Progress (2023)
- Multiple awards for poster and oral presentations at national conferences (SRCOS, Virginia Academy of Science)
Grants and Collaborations:
- Lead investigator on NIH-funded projects addressing kidney disease disparities and end-stage renal disease (total funding: $1.7M+)
- NSF RII Track-2 FEC grant ($750K) for climate-impacted grid resilience research
- USDA grants for precision agriculture, renewable energy integration, and grassland management
His work bridges computational statistics with real-world challenges in energy sustainability, healthcare equity, and environmental monitoring through interdisciplinary collaborations.
