IEEE Fellows - Class of 2018
Hong Kong Baptist University, Hong Kong SAR, CHINA
for contributions to cluster analysis and visual computing.
Yiu-ming Cheung is currently a Full Professor at Department of Computer Science in Hong Kong Baptist University (HKBU). He received Ph.D. degree from Department of Computer Science and Engineering at The Chinese University of Hong Kong in 2000, and then joined the Department of Computer Science at HKBU in 2001. He is an IET/IEE Fellow, British Computer Society (BCS) Fellow, and Fellow of International Engineering and Technology Institute, Hong Kong (IETI), as well as the “Chu Tian Scholars” in China.
His research interests include Computational Intelligence, Statistical Learning, Intelligent Visual Computing, Pattern Recognition, Data Mining, and Watermarking. He has published over 200 research articles and has been granted three invention patents. In recognition of his innovative work, he was awarded two prestigious prizes: (1) the Gold Medal with Distinction (i.e. the highest grade in Gold Medals) and (2) Swiss Automobile Club Prize, both of which were selected from 1000 new inventions and products of 700+ competition teams from 40 countries, in the 45th International Exhibition of Invention, Geneva, in 2017. Furthermore, he was the Gold Award Winner of Hong Kong Innovative Invention Award in the Seventh Hong Kong Innovative Technologies Achievement Award 2017. In addition, he was the recipient of 2011 Best Research Award in Department of Computer Science, HKBU, and therecipient of Best Paper Awards in SEAL’2017, ISICA’2017, ICNC-FSKD’2014, and IWDVT’2005, respectively.
He is the Founding Chairman of IEEE (Hong Kong) Computational Intelligence Chapter and the Vice Chair of IEEE Computer Society Technical Committee on Intelligent Informatics (TCII). He has served in various capacities (e.g., Organizing Committee Chair, Program Committee Chair, Program Committee Area Chair, Financial Chair, etc.) in several top-tier international conferences, including WCCI 2016, ICDM 2006&2017, WI-IAT 2006&2012. Currently, he is an Associate Editor of IEEE Trans. on Neural Networks and Learning Systems, Pattern Recognition, Knowledge and Information Systems (KAIS), to name a few.
University of Granada, SPAIN
for contributions to genetic and evolutionary fuzzy systems.
Oscar Cordón received his M.S. degree (1994) and his Ph.D. (1997) both in Computer Science from the University of Granada, Spain, where he is currently Professor at the Department of Computer Science and Artificial Intelligence. He was the founder and leader of this University’s Virtual Learning Center (2001-2005) and is the Vice-President for Digital University since 2015. He was founding Principal Researcher (2006-2011) and Distinguished Affiliated Researcher (2011-2015) of the European Centre for Soft Computing.
He has been, for more than 23 years, an internationally recognized contributor to R&D Programs in fundamentals and real-world applications of computational intelligence. He has published around 340 peer-reviewed scientific publications (including a research book on genetic fuzzy systems with more than 1230 citations in Google Scholar and 98 JCR-SCI-indexed journal papers, 55 in Q1), advised 18 Ph.D. dissertations, coordinated 30 research projects and contracts (with an overall amount of 7.4M€), has a granted international patent on an intelligent system for forensic identification commercialized in Mexico and South Africa, and is currently or was an Associate Editor of 16 international journals. By December 2017, he is included in the 1% of most-cited researchers in the world (source: Thomson’s Web of Knowledge, h-index = 32) and has received around 11700 citations in Scholar Google (h-index = 50).
He was awarded with the IEEE CIS Outstanding Early Career Award in its 2011 edition, the first such award conferred; the IFSA Award for Outstanding Applications of Fuzzy Technology in 2011, and the Spanish National Award on Computer Science ARITMEL by the Spanish Computer Science Scientific Society in 2014. He has taken many different representative positions with Eusflat and IEEE CIS. Among them, he was an elected member of IEEE CIS AdCom (2010-2012) as well as General Chair of FUZZ-IEEE 2016 and Technical Co-Chair of IEEE CEC 2015, 2017 and 2019, FUZZ-IEEE 2020, and IFSA-EUSFLAT 2015.
Shanghai Jiao Tong University, CHINA
for contributions to stability analysis for time-delay fuzzy systems and intelligent control of nonlinear systems.
Xinping Guan received the BSc degree in mathematics from Harbin Normal University, P. R. China in 1986, and the Ph.D. degree in Control Science andEngineering from Harbin Institute of Technology, P. R. China in 1999. He is currently a Chair Professor at the Department of Automation, Shanghai Jiao Tong University, P. R. China.
His research interests include fuzzy control, neural network based control and optimization of complex systems. He has published more than 200 journal papers and co-authored 6 books. According to Google Scholar, his publications have received more than 8400 citations with h-index 45. Dr. Guan has made seminal contributions to stability analysis and synthesis of time delay T-S fuzzy systems since 1999. The generalized parallel distributed control (GPDC) method proposed by Dr. Guan is recognized as the first delay-dependent stability analysis for time-delay T-S fuzzy systems. This technique has been seen as a milestone by establishing an analytical framework, and the stability criteria are generally acknowledged as benchmarks for conservatism comparison by peers. He received the “IEEE Transaction on Fuzzy Systems Outstanding Paper Award for 2005”. He also received the Second Prize of National Natural Science Award of China in 2008, and the First Prize of Natural Science Award of Ministry of Education of China in 2006 and 2016, respectively.
He is/was on the editorial board of IEEE Trans. on Systems, Man and Cybernetics- Part C and five other international journals. He is an Executive Committee Member of Chinese Automation Association Council and the Chinese Artificial Intelligence Association Council. He also serves as Chair Technical Program Committee Member for more than 60 international conferences. He is a “National Outstanding Youth” awarded by National Natural Science Foundation of China, a distinguished professor of “Changjiang Scholar Program”, and a “State-level Scholar” of “New Century Bai Qianwan Talent Program” of China.
University of Rhode Island, USA
for contributions to adaptive learning.
Haibo He received the B.S. and M.S. degrees in Electrical Engineering from Huazhong University of Science and Technology (Wuhan, China) in 1999 and 2002, respectively, and the Ph.D. degree in Electrical Engineering from Ohio University (Athens, USA) in 2006. From 2006 to 2009, he was an Assistant Professor at the Department of Electrical and Computer Engineering at Stevens Institute of Technology (Hoboken, USA). Currently, he is the Robert Haas Endowed Chair Professor at the Department of Electrical, Computer, and Biomedical Engineering at the University of Rhode Island (Kingston, USA).
His research focuses on adaptive learning and its wide applications in cyber-physical systems, such as smart grid, smart city, robotics, communication systems, and cyber security. He has published one sole-author research book, edited one book (Wiley-IEEE) and six conference proceedings (Springer), and authored/co-authored over 280 high profile journal and conference papers, including several highly cited papers, IEEE Transaction cover page paper, spotlight paper, and best papers. His classic paper entitled “Learning from Imbalanced Data” (IEEE Trans. on Knowledge and Data Engineering, vol. 21, no. 9, pp. 1263-1284, 2009) has received more than 2700 citations.
He has served the IEEE Computational Intelligence Society (CIS) at various capacities, including Chair of IEEE CIS Emergent Technologies Technical Committee (ETTC) (2015) and Chair of IEEE CIS Neural Networks Technical Committee (NNTC) (2013 and 2014). He was the Finance Chair of the IEEE World Congress on Computational Intelligence (IEEE WCCI’16), General Chair of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI’14), Technical Program Co-Chair of the International Joint Conference on Neural Networks (IJCNN’15), among others. He has served as an Associate Editor for IEEE Trans. on Smart Grid (2010-2015) and IEEE Computational Intelligence Magazine (2015), among others. Currently, he is the Editor-in-Chief of IEEE Trans. on Neural Networks and Learning Systems. He was a recipient of the IEEE International Conference on Communications (IEEE ICC) “Best Paper Award” (2014), IEEE CIS “Outstanding Early Career Award” (2014), National Science Foundation “Faculty Early Career Development (CAREER) Award” (2011), and Providence Business News (PBN) “Rising Star Innovator” Award (2011).
Xidian University, CHINA
for contributions to artificial neural networks and evolutionary computation.
Licheng Jiao received the B.S. degree from Shanghai Jiaotong University, Shanghai, China, in 1982 and the M.S. and Ph.D. degree from Xi’an Jiaotong University, Xi’an, China, in 1984 and 1990, respectively. Since 1992, he has been a Professor with the School of Electronic Engineering, Xidian University, Xi’an, where he is currently the Director of Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of China.
In 1992, Dr. Jiao was awarded the Youth Science and Technology Award. In 1996, he was granted by the Cross-century Specialists Fund from the Ministry of Education of China. And he was selected as a member of the First level of Millions of Talents Project of China from 1996. In 2006, he was awarded the First Prize of Young Teacher Award of High School by the Fok Ying Tung Education Foundation. From 2006, he was selected as an Expert with the Special Contribution of Shaanxi Province. Dr. Jiao is a member of the IEEE Xi’an Section Execution Committee, the Chairman of the Awards and Recognition Committee and the Chairman of Computational Intelligence Society, the Chairman of IET Xi’an Section, the Vice Board Chairperson of the Chinese Association of Artificial Intelligence, a committee member of the Chinese Committee of Neural Networks, an expert of the Academic Degrees Committee of the State Council, an Associate Editor of IEEE Trans. on Geoscience and Remote Sensing, and the Chairman of Xi’an Chapter of IEEE Geoscience and Remote Sensing Society. He has published more than 20 monographs and a hundred papers ininternational journals and conferences. His research interests include artificial neural networks, evolutionary computation, image processing, and intelligent information processing.
University of Technology Sydney, AUSTRALIA
for contributions to fuzzy machine learning and decision support systems.
Jie Lu is a Distinguished Professor in the areas of fuzzy transfer learning, decision support systems, concept drift, and recommender systems. She is the Associate Dean in Research Excellence in the Faculty of Engineering and Information Technology at University of Technology Sydney (UTS), and the Director of Centre for Artificial Intelligence at UTS. She has published six research books and 400 papers in Artificial Intelligence, IEEE Trans. on Fuzzy Systems, Decision Support Systems, other refereed journals, and conference proceedings (H-index 44, Google Scholar). She has won more than 20 Australian Research Council (ARC) discovery and other research grants for over $4 million in the last 15 years. She serves as Editor-in-Chief for Knowledge-Based Systems (Elsevier), Editor-in-Chief for International Journal on Computational Intelligence Systems (Atlantis), Associate Editor for IEEE Trans. on Fuzzy Systems, Editor for book series on Intelligent Information Systems (World Scientific), and has served as a guest editor of 12 special issues for IEEE transactions and other international journals, has delivered 17 keynote speeches at international conferences, and has chaired 10 IEEE and other international conferences. She received the first UTS Research Excellence Medal for Teaching and Research Integration in 2010. She services as an ARC panel member (2016-2018). She is the Founding Chair of Australian NSW Computation Intelligence Chapter. She is a Fellow of IFSA (International Fuzzy Systems Association).
Jie Lu’s outstanding and lasting contribution to computational intelligence focuses on integration of fuzzy techniques into machine learning and decision support systems. She has contributed to the development of theories and methods to cross-disciplinary research including fuzzy transfer learning, concept drift detection and adaptation, fuzzy classification, fuzzy recommender systems and fuzzy bi-level decision-making models and decision support systems. She has also pioneered real-world applications by applying computational intelligence techniques in e-government, e-business, logistics and customer retention.
Nanyang Technological University, SINGAPORE
for contributions to memetic computation and applications.
Yew-Soon Ong is a Professor and Chair of the School of Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. He is Founding Director of the Data Science and Artificial Intelligence Research Center (DSAIR), Founding Director of the A*Star SIMTECH-NTU Joint Lab on Complex Systems and Principal Investigator of the Data Analytics & Complex System Programme in the Rolls-Royce@NTU Corporate Lab. He received his Ph.D. from University of Southampton, United Kingdom, and has held visiting appointments at Massachusetts Institute of Technology and Honda Research Institute Europe.
Dr. Ong is founding Editor-In-Chief of the IEEE Trans. on Emerging Topics in Computational Intelligence, founding Technical Editor-In-Chief of Memetic Computing and serves as Associate Editor of the IEEE Trans. on Evolutionary Computation, IEEE Trans. on Neural Network and Learning Systems, IEEE Trans. on Cybernetics, and IEEE Trans. on Big Data. His research interests in computational intelligence span across memetic computation, data-centric evolutionary optimization, and machine learning. Dr. Ong’s research has contributed to the academic advancementof computational intelligence, particularly evolutionary memetic computation, earning him the recognition as a Thomson Reuters Highly Cited Researcher and cited amongst the World's Most-Influential-Scientific Minds in the field of Computer Science. He received the 2015 IEEE Computational Intelligence Magazine Outstanding Paper Award and the 2012 IEEE Transactions on Evolutionary Computation Outstanding Paper Award for his work in memetic computation. Several of his research technologies have been commercialized and licensed to companies and institutions. One of which led to the AI-enabled IOS 'Dark-Dots Game'. It emerged as the top action game in 48 countries including USA, China and Singapore; downloaded by well over 448,000 players worldwide when launched.
At the IEEE Computational Intelligence Society, he chaired the Intelligent Systems Applications Technical Committee (2013-2014) and the Emergent Technology Technical Committee (2011-2012). He has also served as Conference Chair of the IEEE Congress on Evolutionary Computation, Vancouver, Canada, 2016.
University of Massachusetts Amherst, USA
for contributions to neural computation.
Dr. Hava Siegelmann is a Full Professor at the highly regarded College of Computer Science at the University of Massachusetts Amherst and director of the BINDS Lab. Her research focuses on advancing the state of neural networks and on the emerging field of Lifelong Learning, which is at the cutting edge of Machine Learning and Artificial Intelligence. She is currently on a leave of absence to initiate and direct DARPA’s L2M lifelong learning program to develop computational systems capable of true learning, and applying prior learning to novel circumstances without retraining.
Dr. Siegelmann received her Ph.D. (Fellow of Excellence) in Computer Science from Rutgers (1993) with her ground-breaking thesis, “Foundation of Recurrent Neural Networks;” Master’s (Cum Laude) Hebrew University (1992); BSc Technion (Summa Cum Laude) (1988). Siegelmann’s seminal paper: Computation Beyond the Turing Limit, Science (1995), and subsequent book: Neural Networks and Analog Computation: Beyond the Turing Limit (1998), outlined her Super-Turing theory, an entirely new field of computation, the only known alternative to Turing computation, and now, a critical element in Lifelong Learning system development. Siegelmann, with Vladimir Vapnik, developed Support Vector Clustering – one of the most widely employed hierarchical clustering algorithms. Siegelmann is one of the few scientists to have successfully applied neural networks to complex, real-world applications as with her radar, and nuclear power plant control systems. Her findings are widely cited in textbooks and papers, and taught in curricula as foundational to the latest generation of AI and ML.
Dr. Siegelmann has held visiting appointments at MIT, Harvard, ETH Zurich, UC Berkeley, Cambridge University, Salk Institute, Bell Labs, NEC, the Weizmann Institute and more. In 2015 the NSF named Siegelmann one of 16 presidential BRAIN Initiative awardees; In 2016, the International Neural Network Society (INNS) named her the Donald O. Hebb Awardee, and IEEE named her a Distinguished Lecturer. Dr. Siegelmann has served extensively on the executive boards, and numerous committees for IEEE and INNS. She has chaired the 2011 IJCNN and others. She has given plenary and keynote talks in over 30 international conferences and has served as a longtime Editor at various journals including Frontiers in Computational Neuroscience (Nature), Neural Networks, and Scholarpedia. Dr. Siegelmann remains highly active in supporting young researchers and minorities. She also has years of experience consulting with industry, creating educational programs, fundraising, and in administration and organization.