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Peter A. Beling

Position: Professor and Interim Chair
Office: Olsson 114A
Phone: 434-982-2066
Personal Homepage

Ph.D, Industrial Engineering and Operations Research, University of California at Berkeley, 1991
M.S., Operations Research, George Washington University, 1987
B.A., Mathematics, University of Virginia, 1985.


Peter A. Beling is an associate professor in the Department of Systems and Information Engineering at the University of Virginia (UVa). Dr. Beling received his Ph.D. in Operations Research from the University of California at Berkeley. Dr. Beling has held positions at the Center for Naval Analyses and the IBM Almaden Research Center. Dr. Beling’s research interests are in data analytics and decision-making in complex systems, with emphasis on adaptive decision support systems and reinforcement learning. His research has found application in a variety of domains, including smart manufacturing, resiliant cyber physical systems, finance, and consumer credit. Dr. Beling is Director of UVa site of the Center for Visual and Decision Informatics, a National Science Foundation Industry/University Cooperative Research Center. He also directs the Adaptive Decision Systems Laboratory, which focuses on data analytics and decision support in cyber-physical systems. He is the co-founder of the Financial Decision Engineering research group at UVa, which is a focal point for research on systems engineering approaches to decisions and analyses in the financial and consumer credit domains. Dr. Beling has served as editor and reviewer for many academic journals. He has served as a member of two National Research Council panels.

Research Interests:

  • Decision modeling in complex and cyber-physical systems
  • Adaptive decision systems
  • Reinforcement and inverse reinforcement learning
  • Probabilistic machine learning
  • Data-driven process improvement in smart manufacturing systems
  • Decision modeling in consumer lending financial markets
  • Decision models for cybersecurity assessment

Research Groups:

Research Centers:

Representative Publications:

  1. Landau, M. and Beling, P. (2017). Optimal Model-Based (3D/6D) Pose Estimation with Structured-Light Depth Sensors. IEEE Transactions on Computational Imaging, pp. 1-14 (published online).
  2. Choo, B., Adams, S., Marvel, J., Weiss, B., and Beling, P. (2016). Adaptive Multi-scale PHM for Smart Manufacturing Systems. International Journal of Prognostics and Health Management, pp. 1-15 (published online).
  3. Adams, S., Beling, P., and Cogill, R. (2016). Feature Selection for Hidden Markov Models and Hidden Semi-Markov Models. IEEE Access, 4, pp. 1642-1657.
  4. Rajaratnam, K., Beling, P., and Overstreet, G. (2016). Regulatory Capital Decisions in the Context of Consumer Loan Portfolios. Journal of the Operational Research Society, pp. 1-20 (published online).
  5. Reyes, I., Beling, P., and Horowitz, B. (2015). Adaptive Multi-scale Optimization: Concept and Case Study on Simulated UAV Surveillance Operations. IEEE Systems Journal, pp. 1-12 (published online).
  6. Rude, D., Adams, S., and Beling, P. (2015). Task Recognition from Joint Tracking Data in an Operational Manufacturing Cell. Journal of Intelligent Manufacturing, pp. 1-15 (published online).
  7. Yang, S., Qiao, Q., Beling, P., Scherer, W., and Kirilenko, A. (2015). Gaussian Process-Based Algorithmic Trading Strategy Identification. Quantitative Finance, 15, no. 10, pp. 1683-1703.
  8. Qiao, Q. and Beling, P. (2013). Recognition of Agents from Observation of Their Sequential Behavior. European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Databases (ECML-PKDD 2013), pp. 33-48.
  9. Qiao, Q. and Beling, P. (2011). Inverse Reinforcement Learning with Gaussian Processes. American Control Conference (ACC 2011), pp. 113-118.
  10. Zhao, Y., Patek, S., and Beling, P. (2008). Decentralized Bayesian Search using Approximate Dynamic Programming Methods. IEEE Transactions on Systems, Man and Cybernetics, Part B, 38 (4), pp. 970-975.

Other Activities:

Graduate Students: