Statistical Modeling and Learning
Statistical modeling and learning use statistical models and assumptions to translate complex real-world problems into tractable structures so that predictions about uncertain outcomes or prescriptions to design systems can be made. Going from data to models, our methodological research in this area is shaped around devising novel frameworks that can lead to fair and interpretable decisions and insights. Key drivers to our fundamental research in this area are the explosion in the availability of data and computational power in the last decade.
Focus Areas
- Reinforcement Learning
- Machine Learning
- Applied Probability
- Data-driven human performance and behavior modeling; digital (wearable) monitoring and analytics
- Statistical Modeling
Faculty
Cheoljoon Jeong
ASSISTANT PROFESSOR
(864) 656-1498
cjeong@clemson.edu
David M. Neyens
ASSOCIATE PROFESSOR
(864) 656-4719
dneyens@clemson.edu
Hamed Rahimian
ASSISTANT PROFESSOR
(864) 656-7889
hrahimi@clemson.edu
Kevin M. Taaffe
PROFESSOR/DEPARTMENT CHAIR
Harriet and Jerry Dempsey Professor
(864) 656-0291
taaffe@clemson.edu
Feng Ye
ASSISTANT PROFESSOR
(864) 656-9893
fengy@clemson.edu
