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Office Location: ETC 5.122

Dragan Djurdjanovic


Temple Foundation Endowed Faculty Fellowship No. 3

Department Research Areas:
Analytics and Probabilistic Modeling

Dragan Djurdjanovic obtained his B.S. in Mechanical Eng. and in Applied Mathematics in 1997 from the Univ. of Nis, Serbia, his M.S. in Mechanical Eng. from the Nanyang Technological Univ., Singapore in 1999, and his M.S. in Electrical Eng. (Systems) and Ph.D. in Mechanical Eng. in 2002 from the Univ. of Michigan, Ann Arbor. His research interests include advanced quality and process control in multistage manufacturing systems, intelligent proactive maintenance techniques and applications of advanced data analytics in biomedical engineering. He was the director of the recently graduated NSF Industry-University Cooperative Research Center (I-UCRC) on Intelligent Maintenance Systems at The University of Texas at Austin and is Associate Director of the NSF Engineering Research Center on Nanomanufacturing Systems (NASCENT Center). He co-authored 69 journal publications, 9 book chapters and more than 30 refereed conference publications. He is a Fellow of the International Society for Engineering Asset Management, Associate Member of the International Academy for Production Research (CIRP) and is the recipient of several prizes and recognitions, including the 2018 August-Wilhelm Scheer Visiting Professorship from Technical University of Munich, 2006 Outstanding Young Manufacturing Engineer Award from the Society of Manufacturing Engineers (SME) and 2005 Teaching Incentive Award from the Department of Mechanical Engineering of the University of Michigan.

Selected Publications
  1. A. Ul Haq and D. Djurdjanovic, “Robust Control of Overlay Errors in Photolithography Processes,” IEEE Transactions on Semiconductor Manufacturing, Vol. 32, No. 3, pp. 320-333, August 2019. (
  2. Y. Xie and D. Djurdjanovic, “Monitoring of Human Neuromusculoskeletal System Performance Through Model Based Fusion of Electromyogram Signals and Kinematic/Dynamic Variables,” SAGE Journal on Structural Health Monitoring, Special Edition on Human Monitoring Systems for Health, Fitness and Performance, 14 pages, available on line since May 2019. (
  3. Z. Cai, A. Ul Haq, M. Cholette and D. Djurdjanovic, “Energy Efficiency and Tracking Performance Evaluation for Dual-Mode Model Predictive Control of HVAC Systems”, ASME Journal of Thermal Science and Engineering Applications, Vol. 10, No. 4, pp. 041023-1 – 041023-10, August 2018. (
  4. D. Djurdjanovic, L. Mears, F. Niaki, A. Ul Haq and L. Li, “State of the Art Review on Process, System, and Operations Control in Modern Manufacturing,” ASME Journal of Manufacturing Science and Engineering, Vol. 140, No. 6, pp. 061010-1 - 061010-18, June 2018. (
  5. D. Zhang, A. D. Bailey, III, and D. Djurdjanovic, “Bayesian Identification of Hidden Markov Models and Their Use for Condition-Based Monitoring,” IEEE Transactions on Reliability, Vol. 65, No. 3, pp. 1471-1482 September 2016. (


Most Recent Publications
  1. H. Zhang and D. Djurdjanovic, ”Integrated Production and Maintenance Planning with Concurrent Learning of Yield Rate,” Flexible Services and Manufacturing, available online since May 7, 2021. (
  2. K. E. Madden, D. Djurdjanovic and A. Deshpande, “Using a System-Based Monitoring Paradigm to Assess Fatigue during Submaximal Static Exercise of the Elbow Extensor Muscles,” MDPI Sensors, Vol. 21, No. 1, Article Number 1024, 23 pages, January 2021. (
  3. L. Ma, D. Djurdjanovic and R. Dugnani, “Ceramic” Statistical Accuracy of Fractographic Estimation in Silicate Glasses with Design of Experiments and Pairwise T-tests,” Engineering Failure Analysis, Vol. 116, October 2020. (
  4. R. Sabbagh, Z. Cai, A. Stothert and D. Djurdjanovic, “Physically Inspired Data Compression and Management for Industrial Data Analytics,” Frontiers in Computer Science, Special Edition on Data-Driven Cognitive Manufacturing - Applications in Predictive Maintenance and Zero-Defect Manufacturing,, September 2020. (
  5. M. Celen and D. Djurdjanovic, “Integrated Maintenance and Operations Decision Making with Imperfect Degradation State Observations,” SME Journal of Manufacturing Systems, Vol. 55, pp. 302-316, April 2020. (