Jacek Zurada
Dr. Jacek M. Zurada has PhD degree in Electrical Engineering from Gdansk University of Technogy, Gdansk, Poland. He was a post-doc at the Swiss Federal Institute of Technology in Zurich. He now serves as a Professor of Electrical and Computer Engineering at the University of Louisville, Louisville, Kentucky, USA. In 2004-06 he served as Department Chair. He was a Visiting Professor at Princeton University, Northeastern University, Auburn University, the National University of Singapore, Nanyang Technological University in Singapore (as Nanyang Professor), Chinese University of Hong Kong, the University of Chile, Santiago, Toyohashi University of Technology, Japan, the University of Stellenbosch, South Africa, the University of Marie-Curie, Paris, France.Dr. Zurada has received a number of awards for distinction in research and teaching, including the 1993 Presidential Award for Research, Scholarship and Creative Activity and the 2001 Presidential Distinguished Service Award for Service to the Profession. He received the Golden Jubilee Medal from the Circuits and Systems Society in 2000 and the Meritorious Service Award from the Computational Intelligence Society in 2008. His other distinctions include IEEE Life Fellow, and numerous other IEEE and non-IEEE distinctions such as 2014 Joe Desch Award, International Neural Networks Society Fellow and 2020 IEEE TAB Hall of Honor Award. In 2003, he was conferred the Title of Professor by the President of Poland. In 2005 he was elected a Foreign Member of the Polish Academy of Sciences. He also holds a honorary doctorate. His hobbies include foreign languages, modern history, and music.
Education
- M.S. in Electrical Engineering, Gdansk University of Technology, 1968
- Ph.D. in Electrical Engineering, Gdansk University of Technology, 1975
Publications
Journal Articles
- Fan, Q., Kang, Q. & Zurada, J., M. (2022). Convergence analyses for sigma-pi-sigma neural network based on some relaxed conditions. Information Sciences, 585, 70-88
- Ayinde, B., Zurada, J., M. & Inanc, T. (2019). Redundant Feature Pruning for Accelerating Trained Deep Neural Networks. Neural Networks
- Bilski, J., ., Kowalczyk, B., ., Marjanski, A., ., Gandor, M., . & Zurada, J., . (2021). A NOVEL FAST FEEDFORWARD NEURAL NETWORKS TRAINING ALGORITHM. JOURNAL OF ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING RESEARCH, 11(4), 287-306
- Bilski, J., Kowalczyk, B., Kisiel-Dorohinicki, M., Siwocha, A. & Zurada, J. (2022). <span style="font-size:12pt;">Towards a Very Fast Feedforward Multilayer Neural Networks Training Algorithm</span>. JOURNAL OF ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING RESEARCH, 12(3), 181-195
- Ayinde, B., Zurada, J., M. & Inanc, T. (2019). Redundant Feature Pruning for Accelerated Inference in Deep Neural Networks. Neural Networks, 118, 148-158
- Wang, J., Zhang, H., Zurada, J., M. & Pal, N. (2019). Feature Selection for Neural Networks using Group Lasso Regularization. IEEE Transactions on Knowledge and Data Engineering(1)
- Ayinde, B., Zurada, J., M. & Inanc, T. (2019). Redundant Feature Pruning for Accelerated Inference in Deep Neural Networks. Neural Networks, 118, 148-158
- Li, F., Zurada, J., M. & Wu, W. (2018). Smoothing L1/2 Regularization for Input Layer of Feedforward Neural Networks. Neurocomputing, 2018(314), 109-119
- Ayinde, B. & Zurada, J., M. (2018). Deep Learning of Constrained Autoencoders for Enhanced Understanding of Data. IEEE Transactions on Neural Networks and Learning Systems, 29(9), 3969-3979
- Vu, V., P., Wang, W., J., Zurada, J., M., Chen, H., C. & Chiu, C., H. (2018). Unknown Input Method Based Observer Synthesis for a Discrete Time Uncertain T-S Fuzzy System. IEEE Transactions on Fuzzy Systems, 26(3), 1447-1458
- Wang, J., Xu, C., Yang, X. & Zurada, J., M. (2018). Novel Pruning Algorithm for Smoothing Feedforward Neural Networks based on Group Lasso Method. IEEE Transactions on Neural Networks and Learning Systems, 29(5), 2012-2024
- Vu, V., P., Wang, W., J., Chen, H., C. & Zurada, J., M. (2018). Unknown Input Method Based Observer Synthesis for a Polynomial T-S Fuzzy Model System with Uncertainties. IEEE Transactions on Fuzzy Systems, 26(2), 761-770
- Ayinde, B. & Zurada, J., M. (2018). Building Efficient ConvNets with Redundant Feature Pruning.
- Mirinejad, H., Gaweda, A., E., Brier, M., E., Zurada, J., M. & Inanc, T. (2017). Individualized drug dosing using RBF-Galerkin method: Case of anemia management in chronic kidney disease. Computer Methods and Programs in Biomedicine, 148, 45-53
- Li, F., Zurada, J., M. & Wu, W. (2017). Sparse Representation Learning of Data by Autoencoders with L1/2 Regularization. Neural Networks World, 5, 10979-10985
- Li, F., Zurada, J., M. & Wu, W. (2017). Input Layer Regularization of Multilayer Feedforward Neural Networks. IEEE Access
- Ayinde, B. & Zurada, J., M. (2017). Discovery Through Constraints: Imposing Constraints on Autoencoders for Data Representation and Dictionary Learning. IEEE Systems, Man and Cybernetics Magazine, 3(3), 13-24
- Ayinde, B. & Zurada, J., M. (2017). Non-redundant Sparse Feature Extraction using Autoencoders with Receptive Fields Clustering. Neural Networks, 93, 99-109
- Hou, J., Ong, Y., Feng, L. & Zurada, J., M. (2017). An Evolutionary Transfer Reinforcement Learning Framework for Multi-Agent System. IEEE Transactions on Evolutionary Computation, 21(4), 601-615
- Wang, J., Cai, Q., Chang, Q. & Zurada, J., M. (2017). Convergence analyses on sparse feedforward neural networks via group lasso regularization. Information Sciences, 381, 250-269
- Alansary, A., Ismail, M., Soliman, A., Khalifa, F., Nitzken, M., Elnakib, A., Mostapha, M., Black, A., Stinebrunner, K., Casanova, M., F., Zurada, J., M. & El-Baz, A., S. (2016). Infant Brain Extraction in T1-weighted MR Images using BET and Refinement using LCDG and MGRF Models. IEEE Journal of Biomedical and Health Informatics, 20(3), 925-935
- Asl, E., H., Zurada, J., M., Gimmel'farb, G. & El-Baz, A., S. (2016). 3D Lung Segmentation Using Incremental Constrained Nonnegative Matrix Factorization. IEEE Transactions on Biomedical Engineering, 63(5), 952-963
- Fan, Q., Wu, W. & Zurada, J., M. (2016). Convergence of batch gradient learning with smoothing regularization and adaptive momentum for neural networks. Springerplus, 5(1), 295-311
- Hosseini-Asl, E., Nasraoui, O. & Zurada, J., M. (2016). Deep Learning of Part-Based Representation of Data Using Sparse Autoencoders With Nonnegativity Constraints. IEEE Transactions on Neural Networks and Learning Systems, 27(12), 2486-98
- Hosseini-Asl, E., Zurada, J., M., Gimel'farb, G., El-Baz, A., S. & Gimel’farb, G. (2016). 3-D Lung Segmentation Using Incremental Constrained Nonnegative Matrix Factorization. IEEE Transactions on Biomedical Engineering, 63(5), 952-963
- Wang, J., Ye, Z., Y., Gao, W., F. & Zurada, J., M. (2016). Boundedness and convergence analysis of weight elimination for cyclic training of neural networks. Neural Networks, 82(October), 49-61
- Wen, Y., Wang, J., Huang, B. & Zurada, J., M. (2016). Convergence Analysis of Inverse Iterative Networks with L2 Penalty. Journal of Applied Computer Science Methods, 2(8), not available
- Chorowski, J. & Zurada, J., M. (2015). Learning understandable neural networks with non-negative weight constraints. IEEE Transactions on Neural Networks and Learning Systems, preprint published in 2014(26, no 1), 62-69
- Teng, T., H., Tan, A., H. & Zurada, J., M. (2015). Self-Organizing Neural Networks Integrating Domain Knowledge and Reinforcement Learning. IEEE Transactions on Neural Networks and Learning Systems, 26(5), 889-902
- Wang, J., Yang, G., Liu, S. & Zurada, J., M. (2015). Convergence Analysis of Multilayer Feedforward Networks Trained with Penalty Terms. Journal of Applied Computer Science Methods, 7(2), 89-103
- Zhou, W. & Zurada, J., M. (2015). New Stability Condition for Discrete-Time for Fully Coupled Neural Networks with Multivalued Neurons. Neurocomputing, 166(Oct 20, 2015), 38-43
- Akabua, E., Inanc, T., Gaweda, A., Brier, M., Kim, S. & Zurada, J., M. (2014). Individualized Model Discovery: The Case of Anemia Patients. Journal of Computer Methods and Programs in Biomedicine, 118(1), 23-33
- Chorowski, J., Wang, J. & Zurada, J., M. (2014). Review and performance comparison of SVM- and ELM- based classifiers. Neurocomputing, 128, 507-517
- Fan, Q., Zurada, J., M. & Wu, W. (2014). Convergence of online gradient method for feedforward neural networks with Smoothing L1/2 regularization penalty. Neurocomputing, 131, 208-216
- Li, B., Li, H. & Zurada, J., M. (2014). Cross-layer Design of Joint Beamforming and Random Network Coding in Wireless Multicast Networks. IEEE Communications Letters, 18(12), 2173-2176
- Nitzken, M., Casanova, M., Gimel'farb, G., Inanc, T., Zurada, J., M., El-Baz, A., S. & Gimel’farb, G. (2014). Shape Analysis of Human Brain: A Brief Survey. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, 18(4), 1337-1354
- Wu, W., Fan, Q., Wang, J., Yang, D., Liu, Y. & Zurada, J., M. (2014). Batch gradient method with smoothing L1/2 regularization for training of feedforward neural networks. Neural Networks, 50(2014), 72-78
- Zurada, J., M., Kang, M., Kim, H. & Boo, C. (2014). A Nonlinear Regression based Approach for Multilayer Soil Parameter Estimation. International Journal of Control and Automation, 7(2), 65-74
- Chorowski, J. & Zurada, J., M. (2014). Learning understandable neural networks with non-negative weight constraints. IEEE Transactions on Neural Networks and Learning Systems, preprint published in 2014, 62-69
- Torabi, A., J., Er, M., J., Li, X., Lim, B., S., Zhai, L., Oentaryo, R., J., Pen, G., O. & Zurada, J., M. (2014). A Survey on Artificial Intelligence-Based Modeling Techniques for High Speed Milling Processes. IEEE Systems Journal(preprint published in 2014), pp. 1-12
- Asl, E., H. & Zurada, J., M. (2013). Multiplicative Algorithm for Correntropy-Based Nonnegative Matrix Factorization, Journal of Applied Computer Science Methods. Journal of Applied Computer Science Methods, 5(2), 89-104
- Wang, J., Wu, W. & Zurada, J., M. (2012). Computational properties and convergence analysis of BPNN for cyclic and almost cyclic learning with penalty. Neural Networks, 33, 127-135
- Zhou, W. & Zurada, J., M. (2012). A competitive layer model for cellular neural networks. Neural Networks, 33, 216-227
- Affan, A., ., Zurada, J., M. & Inanc, T., . (2021). Adaptive Individualized Modeling From Limited Clinical Data for Precise Anemia Management. IEEE ACCESS, 9, 119466-119475
- Affan, A., Zurada, J., M. & Inanc, T. (2023). <span style="font-size:12pt;">Control–Relevant Adaptive Personalized Modeling from Limited Clinical Data for Precise Warfarin Management</span>. IEEE Open Journal of Engineering in Medicine and Biology , 3, 242-251
- Fan, Q. & Zurada, J., M. (2022). A Pruning Algorithm with Relaxed Conditions for High-Order Neural Networks based on Smoothing Group L1/2 Regularization and Adaptive Momentum. Knowledge Based Systems, 257(December 2022, 109858)
- Mirinejad, H., Inanc, T. & Zurada, J., M. (2021). Radial Basis Function Interpolation and Galerkin projection for direct trajectory optimization and co-state estimation. IEEE/CAA Journal of Automatica Sinica
- Ozdemir, T., Taher, F., Ayinde, B., Zurada, J., M. & Ozmen, O., Y. (2022). <span style="font-size:12pt;">Comparison of Feedforward Perceptron Network with LSTM for Solar Cell Radiation Prediction</span>. Applied Sciences, 12(9), paper # 4463
Books
- Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R. & Zurada, J., M. (2018). Artificial Intelligence and Soft Computing. Germany: Springer-Heidelberg
- Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R. & Zurada, J., M. (2018). Artificial Intelligence and Soft Computing. Germany: Springer-Heidelberg
- Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., A. & Zurada, J., M. (2017). Artificial Intelligence and Soft Computing. Germany: Springer-Heidelberg
- Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., A. & Zurada, J., M. (2016). Artificial Intelligence and Soft Computing. Germany: Springer-Heidelberg
- Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., A. & Zurada, J., M. (2015). Artificial Intelligence and Soft Computing. Germany: Springer-Heidelberg
- Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., A. & Zurada, J., M. (2015). Artificial Intelligence and Soft Computing. Germany: Springer-Heidelberg
- Igelnik, B. & Zurada, J., M. (2013). Efficiency and Scalability Methods for Computational Intellect. (p.346). Hershey, PA, USA: IGI Global
- Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L. & Zurada, J., M. (2012). Artificial intelligence and soft computing. (p.700 pp, Pt I; 720 pp, Pt II). Berlin, Germany: Springer Verlag
- Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L. & Zurada, J., M. (2012). Swarm and evolutionary computation. (p.440). Berlin, Germany: Springer Verlag
More about Jacek Zurada
- Google Scholar, 2019, Citation Count, Ranking
- Honorary Diploma of the Gdansk University of Technology, Gdansk, Poland, 2018, Certificate of Recognition by the University President
- Certificate - Diploma, 2019, Polish Neural Networks Society
- Board of Overseers Membership (ongoing-for 4 years), 2018, Polish Academy of Sciences
- Fellow, 2018, International Neural Networks Society
- Honorary Chair of the Artificial Intelligence and Soft Computing Conference, Zakopane, Poland, 2019, PTSN, IEEE
- Nominee for 2018 IEEE President-Elect (2019 President), 2018, IEEE Board of Directors
- Certificate of Recognition, 2017, IEEE Members and Geographical Activities Board
- Nominee for 2019 IEEE President-Elect (2020 President), 2017, IEEE Board of Directors
- Special Edited Research Volume in Honor of Prof. Jacek Zurada, 2017, Research Community
- Honorary Professorship Award (ongoing), 2017, Obuda University, Budapest, Hungary
- Certificate of Appreciation, 2019, IEEE Systems, Man and Cybernetics Society Conference and AGH Academy
- Honorary Chair of the Artificial Intelligence and Soft Computing Conference, Zakopane, Poland (ongoing), 2016, PTSN, IEEE
- Certificate of Recognition, 2015, IEEE Technical Activities
- Resolution from the IEEE Technical Activities Board, 2015, Ornated Resolution / Reading to IEEE Technical Activities
- Honorary Professorship Award (ongoing), 2015, Obuda University, Budapest, Hungary
- Honorary Chair of the Artificial Intelligence and Soft Computing Conference, Zakopane, Poland (on-going), 2015, PTSN, IEEE
- Outstanding Contribution Award, 2015, China University of Petroleum
- Board of Overseers Membership (ongoing-for 4 years), 2015, Polish Academy of Sciences
- Honorary Professorship Award (on-going through December 31, 2018), 2015, China University of Petroleum
- Wooden Plaque and Gifts, 2014, Wooden Plaque and Gifts by IEEE Technical Activities
- 2014 Distinguished Faculty Award in Service to the Profession, 2014, University of Louisville
- Certificate of Recognition, 2014, Certificate of Recognition by IEEE Computational Intelligence Society
- 2014 Outstanding Polish American, Science Category, 2014, 2014 Outstanding Polish American, Science Category by Pangea Network USA
- Board of Overseers Membership, 2014, Polish Academy of Sciences
- IEEE CIS Distinguished Speaker, 2014, IEEE CIS Distinguished Speaker by IEEE Computational Intelligence Society
- Certificate of Recognition, 2013, IEEE Technical Activities
- Joe Desch Innovation Award, 2013, Engineers Club of Dayton, Ohio
- Foreign Academy Membership (ongoing), 2005, Polish Academy of Sciences
- Honorary Professorship Award , 2013, China University of Petroleum
- Honorary Professorship Award, 2013, Chinese University of Electronic Science and Technology, Chengdu
- Honors and Awards received in 2012, 2012,
- IEEE Life Fellow, 1996, IEEE
- Google Scholar, 2020, Citation Count and Int'l Ranking
- IEEE Hall of Honor Distinction for Educational and Globalization Initiatives, 2020, IEEE Technical Activities Board
- Honorary Chair of the Artificial Intelligence and Soft Computing Conference, Zakopane, Poland, 2020, PTSN, IEEE
- Honorary Chair of the Artificial Intelligence and Soft Computing Conference, Zakopane, Poland, 2021, PTSN, IEEE
- Google Scholar, 2021, Citation Count and Int'l Ranking
- Certificate of Appreciations, 2021, IEEE Computational Intelligence Society
- Google Scholar, 2022, Citation Count
- Honorary Chair of the Artificial Intelligence and Soft Computing Conference, Zakopane, Poland, 2022, PTSN, IEEE
- Janusz Groszkowski Medal, 2022, Association of Polish Electrical Engineers (Stowarzyszenie Elektrykow Polskich, SEP)
- Honorary Doctorate (Dr. H.C.), 2022, Czestochowa University of Technology, Czestochowa, Poland
2023
Spring
- ECE 496 - PROF/CURR TOPICS SEMINAR
- ECE 614 - DEEP LEARNING
2022
Spring
- ECE 496 - PROF/CURR TOPICS SEMINAR
- ECE 614 - DEEP LEARNING
Fall
- ECE 333 - ELECTRONICS I
- ECE 334 - ELECTRONICS I LAB
- ECE 496 - PROF/CURR TOPICS SEMINAR
2021
Spring
- ECE 333 - ELECTRONICS I
- ECE 334 - ELECTRONICS I LAB
- ECE 334 - ELECTRONICS I LAB
- ECE 334 - ELECTRONICS I LAB
- ECE 614 - DEEP LEARNING
Summer
- ECE 693 - INDEPENDENT STUDY IN ECE
Fall
- ECE 514 - INTRO TO VLSI SYSTEMS LAB
- ECE 496 - PROF/CURR TOPICS SEMINAR
- ECE 515 - INTRO TO VLSI SYSTEMS
2020
Fall
- ECE 496 - PROF/CURR TOPICS SEMINAR
Spring
- ECE 614 - DEEP LEARNING
2019
Spring
- ECE 333 - ELECTRONICS I
- ECE 334 - ELECTRONICS I LAB
- ECE 334 - ELECTRONICS I LAB
- ECE 334 - ELECTRONICS I LAB
Fall
- ECE 333 - ELECTRONICS I
- ECE 334 - ELECTRONICS I LAB
- ECE 496 - PROF/CURR TOPICS SEMINAR
2018
Spring
- ECE 333 - ELECTRONICS I
- ECE 334 - ELECTRONICS I LAB
- ECE 334 - ELECTRONICS I LAB
- ECE 334 - ELECTRONICS I LAB
- ECE 496 - PROF/CURR TOPICS SEMINAR
Fall
- ECE 496 - PROF/CURR TOPICS SEMINAR
- ECE 613 - COMP INTELL- DATA ANALY
2017
Spring
- ECE 333 - ELECTRONICS I
- ECE 334 - ELECTRONICS I LAB
- ECE 334 - ELECTRONICS I LAB
2016
Fall
- ECE 333 - ELECTRONICS I
- ECE 334 - ELECTRONICS I LAB
- ECE 496 - PROF/CURR TOPICS SEMINAR
Spring
- ECE 514 - INTRO TO VLSI SYSTEMS LAB
- ECE 515 - INTRO TO VLSI SYSTEMS
2015
Fall
- ECE 333 - ELECTRONICS I
- ECE 334 - ELECTRONICS I LAB
- ECE 334 - ELECTRONICS I LAB
- ECE 496 - PROF/CURR TOPICS SEMINAR
Spring
- ECE 496 - PROF/CURR TOPICS SEMINAR
- ECE 614 - ARTIFICIAL NEURAL SYSTMS
2014
Spring
- ECE 496 - PROF/CURR TOPICS SEMINAR
- ECE 693 - INDEPENDENT STUDY IN ECE
- ECE 613 - COMP INTELL- DATA ANALY
Fall
- ECE 496 - PROF/CURR TOPICS SEMINAR
- ECE 693 - INDEPENDENT STUDY IN ECE
2013
Fall
- ECE 514 - INTRO TO VLSI SYSTEMS LAB
- ECE 515 - INTRO TO VLSI SYSTEMS