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Industrial Engineering

The Department of Industrial Engineering faculty are widely recognized for their significant contributions to industrial engineering research and education. Their diverse research expertise often pairs with other departments and colleges within the university.

Research Applications

Research Methodologies

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 powers 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

Cha profile

Jackie Cha

ASSISTANT PROFESSOR
(864) 656-1874
jackie@clemson.edu

Hamed Rahimian profile

Hamed Rahimian

ASSISTANT PROFESSOR
(864) 656-7889
hrahimi@clemson.edu

neyens2.jpg

David M. Neyens

ASSOCIATE PROFESSOR
(864) 656-4719
dneyens@clemson.edu

Kevin M. Taaffe profile

Kevin M. Taaffe

PROFESSOR/DEPARTMENT CHAIR
Harriet and Jerry Dempsey Professor
(864) 656-0291
taaffe@clemson.edu

The Department of Industrial Engineering faculty are widely recognized for their significant contributions to industrial engineering research and education. Their diverse research expertise often pairs with other departments and colleges within the university.

Research Applications

Research Methodologies