Areas of Interest
- Big Data Analytics
- Graph Theoretical Algorithms
- Life Science Applications
- Ph.D. in Computer Science, Texas A&M University, 1981
Dr. Langston’s current research interests include big data analytics, combinatorial optimization, computer science, data science, defense and life science applications, graph theoretical algorithms, high performance implementations, machine learning and statistical software. He is perhaps best known for his long-standing research on combinatorial algorithms, complexity theory and design paradigms for sequential and parallel computation. In recent years, his work has found broad application in computational biology and the study of health disparities. In addition to maintaining his research program, he regularly teaches courses on algorithm design, automata theory, fixed parameter tractability, graph theory and related subjects.
Dr. Langston has authored over 400 journal articles, conference papers, book chapters and other reports. The National Science Foundation, the National Institutes of Health, the Department of Defense, the Department of Energy, the Environmental Protection Agency and a variety of other federal agencies have funded his work in the U.S. The Australian Research Council and the European Commission have supported his research overseas. He has served on an assortment of editorial boards, including the Association for Computing Machinery’s flagship publication, Communications of the ACM. Recent awards include the College of Engineering Faculty Research Fellow Award, 2012, and the University of Tennessee Chancellor’s Award for Research and Creative Achievement, 2014.