Derong Liu earned his Ph.D. in electrical engineering from the University of Notre Dame in 1994. He served as a Staff Fellow at General Motors Research and Development Center from 1993 to 1995, and subsequently as an Assistant Professor in the Department of Electrical and Computer Engineering at Stevens Institute of Technology from 1995 to 1999. In 1999, Dr. Liu joined the University of Illinois Chicago, where he advanced to the position of Full Professor of Electrical and Computer Engineering and of Computer Science in 2006. He was selected for the prestigious “100 Talents Program” by the Chinese Academy of Sciences in 2008. He also served as the Associate Director of The State Key Laboratory of Management and Control for Complex Systems at the Institute of Automation from 2010 to 2016. Currently, Dr. Liu holds the position of Chair Professor in the School of System Design and Intelligent Manufacturing at Southern University of Science and Technology, Shenzhen, China. He has authored 13 books and serves as the Editor-in-Chief of Artificial Intelligence Review (Springer). Previously, he served as the Editor-in-Chief of the IEEE Transactions on Neural Networks and Learning Systems from 2010 to 2015. Throughout his career, Dr. Liu has received numerous accolades for his contributions to the field, including the Faculty Early Career Development Award from the National Science Foundation in 1999, the University Scholar Award from the University of Illinois from 2006 to 2009, and the Overseas Outstanding Young Scholar Award from the National Natural Science Foundation of China in 2008. He has also been honored with prestigious awards such as the Outstanding Achievement Award from Asia Pacific Neural Network Assembly in 2014, the INNS Gabor Award in 2018, the IEEE SMC Society Andrew P. Sage Best Transactions Paper Award in 2018, the IEEE TNNLS Outstanding Paper Award in 2018, the IEEE/CCA J. Automatica Sinica Hsue-Shen Tsien Paper Award in 2018, and the IEEE CIS Neural Network Pioneer Award in 2022. Consistently recognized as a highly cited researcher by Clarivate since 2017, Dr. Liu is a Fellow of the IEEE, the International Neural Network Society, and the International Association of Pattern Recognition. He is also a Member of Academia Europaea (The Academy of Europe).

Research Interests
Adaptive Dynamic Programming and Reinforcement Learning
Intelligent Control and Information Processing
Modeling and Control of Complex Industrial Processes
Neural Networks and Computational Intelligence
Smart Grid

Professional Achievements
Member, Academia Europaea (The Academy of Europe, https://ae-info.org), 2021
Fellow, Institute of Electrical and Electronics Engineers (IEEE), 2005
Fellow, International Neural Network Society (INNS), 2013
Fellow, International Association for Pattern Recognition (IAPR), 2016
Editor-in-Chief, Artificial Intelligence Review, 2014-present
Editor-in-Chief, IEEE Trans. on Neural Networks and Learning Systems, 2010-2015
General Chair, 24th International Conference on Neural Information Processing, 2017
General Chair, 12th World Congress on Intelligent Control and Automation, 2016
General Chair, IEEE World Congress on Computational Intelligence, 2014
Program Chair, International Joint Conference on Neural Networks, 2008
Neural Networks Pioneer Award, IEEE Computational Intelligence Society, 2022
Dennis Gabor Award, International Neural Network Society, 2018
Outstanding Achievement Award, Asia Pacific Neural Network Assembly, 2014
Highly Cited Researcher, Clarivate, 2017–present
IEEE/CCA Journal of Automatica Sinica Hsue-Shen Tsien Paper Award, 2019
IEEE SMC Society Andrew P. Sage Best Transactions Paper Award, 2018
IEEE Trans. Neural Networks and Learning Systems Outstanding Paper Award, 2018
President, Asia Pacific Neural Network Society (2018)
Distinguished Lecturer, IEEE CIS, 2012-2014 and 2016-2018
University Scholar, University of Illinois, 2006-2009
CAREER Award, National Science Foundation, 1999
Harvey N. Davis Distinguished Teaching Award, Stevens Institute of Technology, 1997
Michael J. Birck Fellowship, University of Notre Dame, 1990

[1] D. Liu and A. N. Michel, Dynamical Systems with Saturation Nonlinearities: Analysis and Design, New York: Springer-Verlag, 1994.

[2] A. N. Michel and D. Liu, Qualitative Analysis and Synthesis of Recurrent Neural Networks. New York: Marcel Dekker, 2002 (This book has been translated into Chinese by H. Zhang, C. Ji, and Z. Wang, and has been published by the Science Press, 2004).

[3] D. Liu and P. J. Antsaklis, Editors, Stability and Control of Dynamical Systems with Applications. Boston, MA: Birkhauser, 2003.

[4] F. L. Lewis and D. Liu, Editors, Reinforcement Learning and Approximate Dynamic Programming for Feedback Control. Hoboken, NJ: Wiley, 2013.

[5] D. Liu, C. Alippi, D. Zhao, and H. Zhang, Editors, Frontiers of Intelligent Control and Information Processing. Singapore: World Scientific, 2014.

[6] D. Liu, Q. Wei, D. Wang, X. Yang, and H. Li, Adaptive Dynamic Programming with Applications in Optimal Control, London: Springer, 2017.

[7] D. Liu and A. N. Michel, “Asymptotic stability of discrete-time systems with saturation nonlinearities with applications to digital filters,” IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, vol. 39, no. 10, pp. 798–807, Oct. 1992.

[8] D. Liu and A. N. Michel, “Cellular neural networks for associative memories,” IEEE Transactions on Circuits and Systems-II: Analog and Digital Signal Processing, vol. 40, no. 2, pp. 119–121, Feb. 1993.

[9] D. Liu and A. N. Michel, “Stability analysis of state-space realizations for two-dimensional filters with overflow nonlinearities,” IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, vol. 41, no. 2, pp. 127–137, Feb. 1994.

[10] D. Liu and A. N. Michel, “Sparsely interconnected neural networks for associative memories with applications to cellular neural networks,” IEEE Transactions on Circuits and Systems-II: Analog and Digital Signal Processing, vol. 41, no. 4, pp. 295–307, Apr. 1994.

[11] D. Liu, “Cloning template design of cellular neural networks for associative memories,” IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, vol. 44, no. 7, pp. 646–650, July 1997.

[12] D. Liu and Z. Lu, “A new synthesis approach for feedback neural networks based on the perceptron training algorithm,” IEEE Transactions on Neural Networks, vol. 8, no. 6, pp. 1468–1482, Nov. 1997.

[13] D. Liu, “Lyapunov stability of two-dimensional digital filters with overflow nonlinearities,” IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, vol. 45, no. 5, pp. 574–577, May 1998.

[14] D. Liu, E. I. Sara, and W. Sun, “Nested auto-regressive processes for MPEG-encoded video traffic modeling,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, no. 2, pp. 169–183, Feb. 2001.

[15] D. Liu and A. Molchanov, “Criteria for robust absolute stability of time-varying nonlinear continuous-time systems,” Automatica, vol. 38, no. 4, pp. 627–637, Apr. 2002.

[16] D. Liu, T.-S. Chang, and Y. Zhang, “A constructive algorithm for feedforward neural networks with incremental training,” IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, vol. 49, no. 12, pp. 1876–1879, Dec. 2002.

[17] D. Liu, S. Hu, and J. Wang, “Global output convergence of a class of continuous-time recurrent neural networks with time-varying thresholds,” IEEE Transactions on Circuits and Systems-II: Express Briefs, vol. 51, no. 4, pp. 161–167, Apr. 2004.

[18] D. Liu, Y. Zhang, and H. Zhang, “A self-learning call admission control scheme for CDMA cellular networks,” IEEE Transactions on Neural Networks, vol. 16, no. 5, pp. 1219–1228, Sept. 2005.

[19] D. Liu and Y. Cai, “Taguchi method for solving the economic dispatch problem with nonsmooth cost functions,” IEEE Transactions on Power Systems, vol. 20, no. 4, pp. 2006–2014, Nov. 2005.

[20] D. Liu, X. Xiong, B. DasGupta, and H. Zhang, “Motif discoveries in unaligned molecular sequences using self-organizing neural networks,” IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 919–928, July 2006.

[21] D. Liu, S. Hu, and H. Zhang, “Simultaneous blind separation of instantaneous mixtures with arbitrary rank,” IEEE Transactions on Circuits and Systems-I: Regular Papers, vol. 53, no. 10, pp. 2287–2298, Oct. 2006.

[22] D. Liu, Z. Pang, and S. R. Lloyd, “A neural network method for detection of obstructive sleep apnea and narcolepsy based on pupil size and EEG,” IEEE Transactions on Neural Networks, vol. 19, no. 2, pp. 308–318, Feb. 2008.

[23] D. Liu, H. Javaherian, O. Kovalenko, and T. Huang, “Adaptive critic learning techniques for engine torque and air-fuel ratio control,” IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, vol. 38, no. 4, pp. 988–993, Aug. 2008.

[24] D. Liu, D. Wang, D. Zhao, Q. Wei, and N. Jin, “Neural-network-based optimal control for a class of unknown discrete-time nonlinear systems using globalized dual heuristic programming,” IEEE Transactions on Automation Science and Engineering, vol. 9, no. 3, pp. 628–634, July 2012.

[25] D. Liu and Q. Wei, “Finite-approximation-error-based optimal control approach for discrete-time nonlinear systems,” IEEE Transactions on Cybernetics, vol. 43, no. 2, pp. 779–789, Apr. 2013.

[26] D. Liu, D. Wang, and H. Li, “Decentralized stabilization for a class of continuous-time nonlinear interconnected systems using online learning optimal control approach,” IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 2, pp. 418–428, Feb. 2014.

[27] D. Liu and Q. Wei, “Policy iteration adaptive dynamic programming algorithm for discrete-time nonlinear systems,” IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 3, pp. 621–634, Mar. 2014.

[28] D. Liu, H. Li, and D. Wang, “Online synchronous approximate optimal learning algorithm for multiplayer nonzero-sum games with unknown dynamics,” IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 44, no.8, pp. 1015–1027, Aug. 2014.

[29] D. Liu, D. Wang, F. Wang, H. Li, and X. Yang, “Neural-network-based online HJB solution for optimal robust guaranteed cost control of continuous-time uncertain nonlinear systems,” IEEE Transactions on Cybernetics, vol. 44, no. 12, pp. 2834–2847, Dec. 2014.

[30] D. Liu, H. Li, and D. Wang, “Error bounds for adaptive dynamic programming algorithms for solving undiscounted optimal control problems,” IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 6, pp. 1323–1334, June 2015.

[31] D. Liu, X. Yang, D. Wang, and Q. Wei, “Reinforcement-learning-based robust controller design for continuous-time uncertain nonlinear systems subject to input constraints,” IEEE Transactions on Cybernetics, vol.45, no.7, pp.1372–1385, July 2015.

[32] D. Liu, Q. Wei, and P. Yan, “Generalized policy iteration adaptive dynamic programming for discrete-time nonlinear systems,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 45, no. 12, pp. 1577–1591, Dec. 2015.

[33] D. Liu, Y. Xu, Q. Wei, and X. Liu, “Residential energy scheduling for variable weather solar energy based on adaptive dynamic programming,” IEEE/CAA Journal of Automatica Sinica, vol. 5, no. 1, pp. 36–46, Jan. 2018.

[34] D. Liu, S. Xue, B. Zhao, B. Luo, and Q. Wei, “Adaptive dynamic programming for control: A survey and recent advances,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 1, pp. 142–160, Jan. 2021.

Ph.D. Electrical Engineering, University of Notre Dame, 1994
M.Sc. Automatic Control Theory and Applications, Institute of Automation, Chinese Academy of Sciences, 1987
B.Sc. Mechanical Engineering, East China Institute of Technology, 1982