Optimization
Optimization theory is a building block of operations research and data science. It combines the disciplines of algebra, geometry, analysis, combinatorics, probability, statistics, and computer science for data-driven decision-making in complex systems. Our methodological research in optimization spans theory, analysis, and design of computationally efficient, robust, and scalable algorithms to handle real-world problems in engineering, operations, economics, and business.
Focus Areas
- Discrete and Combinatorial Optimization
- Stochastic and Robust Optimization
- Network Optimization
- Approximate Dynamic Programming
- Markov Decision Process
- Approximation Algorithms
- Game Theory
- Reinforcement Learning
Faculty
Tuğçe Işık
ASSISTANT PROFESSOR
(864) 656-2454
tisik@clemson.edu
Amin Khademi
ASSOCIATE PROFESSOR
(864) 656-6919
khademi@clemson.edu
Mary Elizabeth Kurz
ASSOCIATE PROFESSOR
(864) 656-4652
mkurz@clemson.edu
Qi Luo
ASSISTANT PROFESSOR
(864) 656-5649
qluo2@clemson.edu
Hamed Rahimian
ASSISTANT PROFESSOR
(864) 656-7889
hrahimi@clemson.edu
Thomas Sharkey
PROFESSOR
(864) 656-7891
tcshark@clemson.edu
Yongjia Song
ASSOCIATE PROFESSOR
(864) 656-9832
yongjis@clemson.edu
Kevin M. Taaffe
PROFESSOR/DEPARTMENT CHAIR
Harriet and Jerry Dempsey Professor
(864) 656-0291
taaffe@clemson.edu
Emily Tucker
ASSISTANT PROFESSOR
(864) 656-9573
etucke3@clemson.edu
