Research interest

My research involves integration of statistics, operations research and information theory to develop advanced statistical models and statistical monitoring methods, with a focus on advancing the science of health care delivery.


  1. Das, D., and Zhou, S. “Detecting Entropy Increase in Categorical Data Using Maximum Entropy Distribution Approximations”, accepted in IISE Transactions ( Selected as feature article in IIE Magazine) (previously named IIE Transactions).
  2. Sir, M. Y., Nestler, D., , Hellmich, T., Das, D., Laughlin, M., Dohlman, M., Pasupathy, K.S., “Data-driven Optimization for Multi-disciplinary Staffing in Mayo Clinic Improves Patient Experience”, accepted, Interfaces.
  3. Das, D., Zhou, S., Chen, Y., and Horst, J. (2015) “Approximate Likelihood Inference for Monitoring Multivariate Count Data” International Journal of Production Research, vol. 54(21), pp. 6579-6593.
  4. Das, D., Chen, Y., Zhou, S. and Sievenppiper, C. (2016) “Monitoring multiple binary data stream using a hierarchical model structure” 2015. Quality Reliability Engineering International, vol. 32(4), pp. 1307-1319.
  5. Das, D. and Zhou, S. (2015) “Statistical Process Monitoring Based on Maximum Entropy Density Approximation and Level Set Principle.” IIE Transactions, vol 47(3), pp. 215-229. ( Selected as feature article in IIE Magazine)
  6. Das, D., Zhou, S. and Lee, J. D.,(2012) Differentiating Alcohol-Induced Driving Behavior Using Steering Wheel Signals.” Intelligent Transportation Systems, IEEE Transactions on } vol. 13 (3), pp. 1355-1368.
  7. Prasoon, R., Das, D., Tiwari, M. K. and Wang, L., (2011) “An algorithm portfolio approach to re-configurable set-up planning”, International Journal of Computer Integrated Manufacturing, vol. 24 (8), pp. 756-768.