Jagannathan Sarangapani is at the Missouri University of Science and Technology, Rolla, MO, USA, where he is a Rutledge-Emerson Distinguished Professor and was Site Director for the graduated NSF Industry/University Cooperative Research Center on Intelligent Maintenance Systems. He also has a courtesy appointment with the Department of Computer Science. He has co-authored 175 peer-reviewed journal articles, over 289 refereed IEEE conference articles, several book chapters, and co-authored four books and two edited books. He holds 21 patents, one defense publication, with several pending. He has supervised the completion of 30 doctoral students and 31 M.S. thesis students. His research funding is in excess of $17.5 million dollars from NSF, NASA, AFOSR, ARO, AFRL, Boeing, Honeywell, Sandia and from other companies. His current research interests include adaptive and neural network control, networked control systems/cyber physical systems, prognostics, and autonomous systems/robotics. He served on various editorial boards and as a co-editor for the IET Book series on Control.
Journal Papers (recent)
- Prakash, L. Behera, S. Mohan, and S. Jagannathan, “Dual loop optimal control of a robot manipulator and its application in warehouse automation”, IEEE Transactions on Automation Science and Engineering, accepted for publication, September 2020.
- Krishnan Raghavan, S. Jagannathan, and V. Samaranayake, "A game-theoretic approach for addressing domain-shift in big-data", IEEE Transactions on Bigdata, conditionally accepted with minor revision, September 2020.
- Jinna Li, Xiao, T. Chai, F.L. Lewis, and S. Jagannathan, " Adaptive interleaved reinforcement learning: robust stability of affine nonlinear systems with unknown uncertainty", IEEE Transactions on Neural Networks and Learning Systems, accepted for publication, October 2020.
- Krishnan Raghavan, Shweta Garg, S. Jagannathan, and V. Samaranayake, "Distributed min-max learning scheme for neural network with applications to high dimensional classification", IEEE Transactions on Neural Networks and Learning Systems, accepted for publication, August 2020.
- Narayanan, H. Moderes, S. Jagannathan and F. L. Lewis, “Event-driven off-policy reinforcement learning for control of interconnected systems”, IEEE Transactions on Cybernetics, accepted for publication, April 2020.
- Choudhary, V. Misra, A. Goswami, and S. Jagannathan, “A comprehensive survey on model based compression and acceleration”, Artificial Intelligence Review, accepted for publication, January 2020.
- Prakash, L. Behera, S. Mohan, and S. Jagannathan, “Dynamic trajectory generation and a robust controller to intercept a moving ball in a game setting”, IEEE Transactions on Control Systems Technology, vol. 28, no. 4, pp. 1418-1432, July 2020.
- Krishnan Raghavan, S. Jagannathan, V. Samaranayake, “Direct error-driven learning for deep neural networks with applications to big-data”, IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 5, pp. 1763-1770, May 2020.
- Daniel Peterson, Tansel Yucelen, Jagannathan Sarangapani, and Eduardo Pasiliao, “Active-passive dynamic consensus filters with reduced information exchange and time-varying agent roles”, IEEE Transactions on Control Systems Technology, vol. 28, no. 3, pp. 844-856, May 2020.
- Haifeng Niu, C. Bhowmick, and S. Jagannathan, “Attack detection and approximation in nonlinear networked control systems using neural networks”, IEEE Transactions on Neural Networks and Learning Systems, Vol. 31, No. 1, pp. 235-245, January 2020.
- Rohollah Moghadam, and S. Jagannathan, “Optimal Adaptive Regulation of Uncertain Linear Continuous-time Systems with State and Input Delays”, of the IEEE Conference on Decision and Control, to appear in December 2020.
- Rohollah Moghadam, P. Rajan, and S. Jagannathan, “Multilayer Neural Network-based Optimal Adaptive Tracking Control of Partially Uncertain Nonlinear Discrete-time Systems”, of the IEEE Conference on Decision and Control, to appear in December 2020.
- Jinna Li, Zhenfei Xiao, TianYou Chai, Frank L. Lewis, and S. Jagannathan, “Off-policy Q-learning for anti-interference control of multi-player systems”, Proc of the IFAC World Congress, Berlin Germany, July 2020.
- Rohollah Moghadam, Pappa Natarajan, Krishnan Raghavan and S. Jagannathan, “Online optimal adaptive control of a class of uncertain nonlinear discrete-time systems”, of the IEEE International Joint Conference on Neural Networks (IJCNN) as part of WCCI, to appear in August 2020.
- Moghadam and S. Jagannathan, “Optimal control of linear continuous-time systems in the presence of state and input delays with application to a chemical reactor”, Proc. of American Controls Conference, to appear in June 2020.
- Moghadam and S. Jagannathan, “Approximate optimal adaptive control of partially unknown linear continuous-time systems with state delay”, Proc. of the IEEE Conference on Decision and Control, pp. 1985-1990, December 2019.
- Haifeng Niu, C. Bhowmick, A Sahoo and S. Jagannathan, “Attack detection in linear networked control systems by using learning methodology”, of the IEEE Conference on Controls Technology and Applications (CCTA), pp. 148-153, August 2019.
- K. Vomvudulakis, and S. Jagannathan, “Control of Complex Systems: Recent Advances and Future Directions”, Wiley, (Edited) 2016.
- Rohollah Moghadam, S. Jagannathan, and Krishnan Raghavan, “Optimal adaptive control of uncertain linear systems with time-delay”, Springer, in Hanbook of Reinforcement Learning and Control, Editors: K.G. Vomvoudakis, Y. Wan, F. Lewis and D.Canseer, 2020.
- Krishnan Raghavan, S. Jagannathan, and V. Samaranayake, “Direct error driven learning for classification with applications to Bigdata”, Editors: W. Pedrycz and S. Chen, Springer 2020.
- Al Salour, D. Trimble, J. Sarangapani, and E. Taqieddin, "Ultra-lightweight Mutual Authentication Protocol with Substitution Operation”, US Patent No. 10198605, February 5, 2019.
Recent Grants (active)
- Planning Grant: Engineering Research Center for Integrative Manufacturing and Remanufacturing Technologies (iMart) to Spur Rural Development, Co-PI, NSF, 2019-2021.
- A Doctoral Program in Big Data, Machine Learning, and Analytics for Security and Safety”, Co-PI, Dept. of Education, 2018-2021.
- RFID based Asset Tracking and Evolvable DNA, Honeywell, PI, 2020-2021.
- Event Triggered Control of Networked Control Systems by using Adaptive Dynamic Programming, PI- NSF, 2014-2019.
- 2020 Outstanding Associate Editor Award, IEEE Systems, Man, and Cybernetics-Systems.
- 2018 IEEE Control System Society’s Transition to Practice Award
- Fellow, National Academy of Inventors
- Fellow of the IEEE
- Fellow of the IET (UK)
- Fellow of the Inst. Of Measurement & Control (UK)
- Commended for Teaching Excellence in 2006-2007, 2012-2013, 2013-2014
- Outstanding Teaching Award 2014-2015, 2015-2016, 2017-2018
- Faculty Excellence Award 2005-2006, 2006-2007
Students Graduated (recent)
- Rohollah Moghadam, “Optimal adaptive control of timed-delay dynamical systems with known and uncertain dynamics”, October 2020. (Now at Assistant Professor, Arkansas Tech. University)
- Krishnan Raghavan, “Deep learning neural network based classifier design with applications to bigdata analytics”, March 2019. (Now at Argonne National Laboratory, Chicago)