About
Biosketch:
Jianhua Zhang received PhD degree in electrical engineering and information sciences from Ruhr University Bochum, Germany in 2005. He was Postdoctoral Research Associate at the University of Sheffield, UK from 2005 to 2006.
Dr Zhang has been Professor of Computer Science and a founding deputy head of AI Lab at Department of Computer Science, OsloMet - Oslo Metropolitan University, Norway since 2018. Before joining OsloMet, he spent a stint working at Vekia (a French IT company), Lille, France, as Scientific Director as well as Head of Machine Learning Lab. He was Professor and Head of Intelligent Systems Group at School of Information Science and Engineering, East China University of Science and Technology, Shanghai between 2007 and 2017. From 1999 to 2002 he taught as a Lecturer at Collge of Electronic, Information & Control Engineering, Beijing University of Technology, China. He was Guest Scientist at Dresden University of Technology (TU Dresden), Germany from 2002 to 2003 and Visiting Professor at Technical University of Berlin (TU Berlin), Germany during 2008-2015 and the University of Catania, Italy in 2024.
Dr Zhang has worked in the fields of artificial intelligence, systems and control, and signal processing since mid-1990s. His recent research interests include computational intelligence, machine learning, cognitive human-machine systems, intelligent systems and control, modeling and control of complex systems, biomedical signal processing, and neurocomputing (neuroergonomics, affective computing, and brain-machine interaction). The primary applications of interest are in the domains of engineering, biomedicine, chemistry, business, and finance. He made significant research contributions in intelligent control of complex industrial systems, cognitive human-machine systems, and AI-driven neuroergonomics and affective computing. As PI he has led over 20 large-scale research projects. So far he has published 4 books, 13 book chapters, and around 200 peer-reviewed scientific journal and conference proceedings papers.
Dr Zhang served as Chair of IFAC (International Federation of Automatic Control) Technical Committee on Human-Machine Systems for two consecutive terms (2017-2023) and Vice Chair of IEEE Norway Section (2019-2023). He currently serves as Vice Chair of IFAC Technical Committee on Human-Machine Systems (2023-) and Vice Chair of IEEE CIS (Computational Intelligence Society) Norway Chapter (2019-). He is on editorial board of four international journals, including Frontiers in Neuroscience, Cognitive Neurodynamics (Springer), and Cognition, Technology & Work (Springer). He serves (or served) as IPC Co-Chair for IFAC LSS2013 (Shanghai), IFAC HMS2016 (Kyoto) and IFAC HMS2025 (Beijing), IPC Chair for IFAC HMS2019 (Tallinn) and IFAC HMS2022 (San Jose), and General Chair for the 9th Int’l. Conf. on Machine Learning Technologies (ICMLT 2024, Oslo) and the 7th Int’l. Conf. on Machine Learning and Machine Intelligence (MLMI 2024, Osaka). In addition, he was keynote speaker or chair for a number of international scientific conferences.
Dr Zhang was on the Stanford/Elsevier's List of World’s Top 2% Scientists in 2023 and 2024. He received Senior Research Fellowship from China Scholarship Council (CSC) in 2012 and Research Fellowship for Experienced Researchers from Max Planck Institute for Dynamics of Complex Technical Systems, Germany in 2011. He was selected into the Shanghai Pujiang-Talents Program by Shanghai Municipal Science Council, China in 2007. He was also the recipient of a full scholarship from the German Academic Exchange Service (DAAD) between 2002-04.
List of Publications:
- Google Scholar profile: https://scholar.google.com/citations?user=UPHhI1wAAAAJ&hl=zh-CN
- ResearchGate profile: https://www.researchgate.net/profile/Jianhua-Zhang-41
Teaching:
- Undergraduate Courses (7):
DAVE3605 Effective Coding in C and C++ (OsloMet)
ADSE1310 Internet of Things (OsloMet)
Principles of Automatic Control
Intelligent Control Systems
Artificial and Computational Intelligence
Fundamentals of Cybernetics
Fuzzy Sets and Systems
- Graduate Courses (5):
ACIT4620 Computational Intelligence: Theory and Applications (OsloMet Master)
ACIT4040 Applied Artificial Intelligence Project (OsloMet Master)
PENG9560 Advanced Topics in Artificial Intelligence and Machine Learning (OsloMet PhD)
Computational Intelligence (PhD)
Soft Computing and Intelligent Systems
- Others (1):
Applied Statistics (a module of TRTEK1000 Transportation Engineering; OsloMet)
Fields of study
Subject areas
Artificial intelligence Machine learning Pattern Recognition Control technology Datamining Neuroinformatics Intelligent systems Human-machine system Computational intelligence Non Stationary signal analysis
Research groups
Publications and research
Scientific publications
Wang, Qi; Chen, Li; Zhan, Zhiyuan;
Zhang, Jianhua
; Yin, Zhong
(2025).
SCVCNet: Sliding Cross-Vector Convolution Network for Task-Independent Cognitive Workload Recognition with EEG Measurement.
IEEE Transactions on Instrumentation and Measurement.
https://doi.org/10.1109/TIM.2025.3550250
Ma, Zhuang; Li, Ao; Tang, Jiehao;
Zhang, Jianhua
; Yin, Zhong
(2025).
Multimodal emotion recognition by fusing complementary patterns from central to peripheral neurophysiological signals across feature domains.
Engineering Applications of Artificial Intelligence.
Vol. 143.
https://doi.org/10.1016/j.engappai.2025.110004
Wang, Qi; Xie, Xin;
Zhang, Jianhua
; Yin, Zhong
(2024).
Cross-task cognitive workload measurement based on the sample selection of the EEG data.
Mau, Jochen; Mukhin, Sergey; Wang, Guanyu; Xu, Shuhua (Ed.).
BIOKYBERNETIKA: Mathematics for theory and control in the human and in society.
Walter de Gruyter (De Gruyter).
https://doi.org/10.1515/9783111341996-026
Zhang, Jianhua
(2024).
Prologue III: The historical perspective: From Macy Meetings and Cybernetics to Initiative Biokybernetik conferences and bioinspired AI.
Mau, Jochen; Mukhin, Sergey; Wang, Guanyu; Xu, Shuhua (Ed.).
BIOKYBERNETIKA: Mathematics for theory and control in the human and in society.
Walter de Gruyter (De Gruyter).
https://doi.org/10.1515/9783111341996-203
Mozaffari, Leila;
Zhang, Jianhua
(2024).
Predicting Stock Market Closing Prices: A Comparative Study Using Ensemble Learning with Transformer, ARIMA, and Linear Regression Models.
Chen, Yen-Wei; Zhang, Jianhua; Kwok, James Tin-Yau (Ed.).
Proc. of the 7th Intl. Conf. on Machine Learning and Machine Intelligence (MLMI 2024).
ACM Digital Library.
https://doi.org/10.1145/3696271.3696293
Chen, Yen-Wei; Zhang, Jianhua ; Kwok, James Tin-Yau (2024). Proc. of the 7th Intl. Conf. on Machine Learning and Machine Intelligence (MLMI 2024). ISBN: 9798400717833. ACM Digital Library.
Mozaffari, Leila;
Zhang, Jianhua
(2024).
Predictive Modeling of Stock Prices Using Transformer Model.
Flammini, Francesco; Xiong, Ning; Zhang, Jianhua; Neri, Filippo (Ed.).
ACM Proceedings of 9th International Conference on Machine Learning Technologies (ICMLT 2024).
Association for Computing Machinery (ACM).
https://doi.org/10.1145/3674029.3674037
Flammini, Francesco; Xiong, Ning; Zhang, Jianhua ; Neri, Filippo (2024). ACM Proceedings of 9th International Conference on Machine Learning Technologies (ICMLT 2024). ISBN: 979-8-4007-1637-9. 350 p. Association for Computing Machinery (ACM).
Yin, Zhong; Yang, J.; Zhang, J.; Wang, Z.;
Zhang, Jianhua
; Wang, Y.; Zhang, B.
(2024).
Generic Mental Workload Measurement Using a Shared Spatial Map Network With Different EEG Channel Layouts.
12 p.
IEEE Transactions on Instrumentation and Measurement.
Vol. 73.
https://doi.org/10.1109/TIM.2024.3373070
Gan, Kaiyu; Li, Ruiding;
Zhang, Jianhua
; Sun, Zhanquan; Yin, Zhong
(2024).
Instantaneous estimation of momentary affective responses using neurophysiological signals and a spatiotemporal emotional intensity regression network.
22 p.
Neural Networks.
Vol. 172.
https://doi.org/10.1016/j.neunet.2023.12.034
