Faculty
Auburn University
Faculty member in the Department of Statistics with interests in statistical learning, AI, data-efficient modeling, and interdisciplinary collaboration.
Auburn University · Statistics · AI Research
Professor Homepage & SPOHERO AI Lab
Welcome to my homepage. I am a faculty member in Statistics at Auburn University, and this site highlights my research, students, collaborations, and selected projects across Sports AI, Healthcare AI, and Robotics.
Your Name, Ph.D.
Assistant Professor
Department of Statistics
Auburn University
Research Areas
3+
Active Projects
10+
Students
Lab Team
Collaborations
Interdisciplinary
About
This homepage serves as a central portal for my academic profile and the SPOHERO AI Lab. My work combines statistics, machine learning, and real-world applications in health, sports, and intelligent assistive systems.
Research Vision
Statistics + AI + Real Impact
Build rigorous and practical methods that connect statistical reasoning with modern AI for healthcare, sports analytics, and next-generation assistive technologies.
Lab
SPOHERO AI Lab
A project-driven lab environment where students and collaborators work on applied AI systems, interpretable models, and data-centered research problems.
Research Themes
The lab focuses on methodological and applied research across several connected areas.
Core Areas
Statistical Learning
Machine Learning
AI for Health
Sports Analytics
Robotics
Human-Centered AI
What We Build
We develop data pipelines, predictive models, evaluation frameworks, interpretable analytics tools, and domain-specific AI systems that can support decision-making and scientific discovery.
Selected Projects
Click each project to visit its dedicated page.
Project
Sports AI
Player tracking, match intelligence, tactical analytics, performance modeling, and data-driven reporting for sports applications.
Visit project →
Project
Healthcare AI
Clinical prediction, personalized modeling, EHR-based research, and statistical methods for robust and efficient healthcare decision support.
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Project
Robotics
Smart glasses, assistive intelligence, human-robot interaction, and adaptive AI systems for real-world environments.
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Lab & Collaboration
The lab welcomes interdisciplinary collaboration across statistics, AI, health, robotics, and sports analytics.
Students
Student Research
Undergraduate and graduate students participate in data analysis, modeling, software development, and project-based research.
Partners
Collaborative Research
We collaborate with domain experts, clinicians, engineers, and applied researchers to build impactful and credible AI systems.
Output
Publications & Tools
Our work includes papers, methods, open research tools, and project websites that communicate both technical depth and practical value.
Contact
For collaboration, student opportunities, or research inquiries, please reach out.