Photo of Abdullah Konak


Professor of Information Sciences and Technology, Penn State Berks
212, Gaige Building

Abdullah Konak is a Distinguished Professor of Information Sciences and Technology at the Pennsylvania State University, Berks.  Dr. Konak received his degrees in Industrial Engineering, B.S. from Yildiz Technical University, Turkey, M.S. from Bradley University, and Ph.D. from the University of Pittsburgh. Prior to his current position, he taught at Auburn University.  Dr. Konak also held visiting positions at Lehigh University and Cornell University, as well as at the Chinese University of Hong Kong where he taught engineering innovation for over a decade.

Dr. Konak’s primary research interest is in the modeling, analysis, and optimization of complex systems using computational intelligence combined with techniques from probability and statistics and from Operations Research.  He has published numerous academic papers in leading journals, such as Operations Research Letters, Informs Journal on Computing, and European Journal of Operations Research, on a broad range of topics including network design, reliable system design, cybersecurity, facilities design, green logistics, production management, and data sciences.  He has been a principal investigator in sponsored projects from the National Science Foundation, the National Security Agency, the US Department of Labor, and Venture Well.

Dr. Konak currently teaches courses on Database Management Systems, Data Mining, Artificial Intelligence, Cybersecurity, Agent-Based Modelling, and Entrepreneurship. He is a member of INFORMS, ISEE, and ASEE.

Research Interests

Computational Intelligence: Modeling and optimization of complex systems using computational intelligence techniques such as artificial neural networks, evolutionary algorithms, tabu search, and ant colony approach combined with techniques from probability and statistics.

Artificial Intelligence: Applying AI techniques for solving problems in operations management,  engineering, and education.

Applied Mathematical Programming: Application of operations research techniques such as linear, integer, and dynamic programming to large-scale real-life problems.

Simulation Optimization: Building and integrating simulation models into optimization algorithms for system optimization.

Virtual Computing in Cybersecurity Education: Advancing student learning through effective laboratory and activity designs based on collaborative, inquiry-based learning in virtual computer laboratories.

Online Hands-on Learning:  Designing online learning objects to simulate deep learning in students through hands-on activities.