Pavel Loskot

IEEE Senior Member

Zhejiang University, China

Biography: 

Dr. Pavel Loskot joined the ZJU-UIUC Institute in January 2021 as the Associate Professor after being nearly 14 years with Swansea University in the UK as the Senior Lecturer in Engineering. He received his PhD degree in Wireless Communications from the University of Alberta in Canada, and the MSc and BSc degrees in Radioelectronics and Biomedical Electronics, respectively, from the Czech Technical University of Prague in the Czech Republic. He is the Senior Member of the IEEE, Member of the Signal Processing and Life Sciences Societies, Fellow of the Higher Education Academy in the UK, and the Recognized Research Supervisor of the UK Council for Graduate Education. He received 3 Best Paper awards from international conferences, and delivered tutorials and keynotes in over 40 international conferences. He was a member of Organizing Committees and the Chair or Co-Chair in nearly 20 international conferences, and Technical Program Committee member in over 120 engineering and scientific conferences.

In the past 25 years, he participated in and led numerous industrial and academic collaborative projects with large and small institutions in the Czech Republic, Finland, Canada, the UK and China, and worked as a paid technology consultant for several SMEs and larger companies. In academic year 2014/2015, he was a visiting researcher in Computational Science Research Center of the Chinese Academy of Engineering in Beijing, China. In 2010-2012, he was the Digital Economy Adviser for the Welsh Government, and the Swansea University representative in Mobile Virtual Centre of Excellence in Mobile Communications in the UK. From 1999 to 2001, he was the Research Scientist in the Centre for Wireless Communications in Oulu, Finland where he received the Nokia Research Award for his innovative work on adaptive transmission systems. He was involved in design, implementation and standardization efforts of the 2G, 3G and 4G mobile cellular networks and the early versions of WiFi and Bluetooth systems. In the past 8 years, he diversified his research interests and got directly involved in projects concerning computational molecular biology, air transport management, and renewable energy systems. This experience allowed him to truly understand the underlying principles of interdisciplinary working, and crossing the disciplines boundaries. His current research focuses on the problems involving statistical signal processing and importing methods from Telecommunication Engineering and Computer Science to other disciplines in order to improve the efficiency and the information power of system modeling and analysis. Elected IARIA Fellow in December 2025.

Ata Jahangir Moshayedi

IEEE Senior Member

Jiangxi University of Science and Technology, China

Biography: 

Dr. Ata Jahangir Moshayedi?an Associate Professor at Jiangxi University of Science and Technology in China, holds a PhD in Electronic Science from Savitribai Phule Pune University in India. He is a distinguished member of IEEE(Senior Member) and ACM, as well as a Life Member of the Instrument Society of India and a Lifetime Member of the Speed Society of India. Additionally, he contributes to the academic community as a valued member of various editorial teams for international conferences and journals.

Dr. Moshayedi's academic achievements are, marked by a portfolio of over 90 papers published,2 patent and 12 copyright , across esteemed national and international journals and conferences along with 3 books on robotics (VR and mobile olfaction) and embedded systems.

In addition to his scholarly publications, he has authored three books and is credited with two patents and nine copyrights, emblematic of his pioneering contributions to the field. His research interest includes Robotics and Automation/ Sensor modeling/Bio-inspired robot, Mobile Robot Olfaction/Plume Tracking, Embedded Systems / Machine vision-based Systems/Virtual reality, and Machine vision/Artificial Intelligence. Currently, Dr. Moshayedi is actively engaged in pioneering work at Jiangxi University, where he is developing a model for Automated Guided Vehicles (AGVs) and advancing the realm of Food Delivery Service Robots.

Professor Dongrui Wu

IEEE Fellow

Huazhong University of Science and Technology, China

Biography: Dongrui Wu received a B.E in Automatic Control from the University of Science and Technology of China, Hefei, China, in 2003, an M.Eng in Electrical and Computer Engineering from the National University of Singapore in 2006, and a PhD in Electrical Engineering from the University of Southern California, Los Angeles, CA, in 2009. He is now Professor and Deputy Director of the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China.

Prof. Wu's research interests include affective computing, brain-computer interface, computational intelligence, and machine learning. He has 150 publications (6,400+ Google Scholar citations; h=39), including a book "Perceptual Computing" (Wiley-IEEE Press, 2010), and five US/PCT patents. He received the IEEE International Conference on Fuzzy Systems Best Student Paper Award in 2005, the IEEE Computational Intelligence Society (CIS) Outstanding PhD Dissertation Award in 2012, the IEEE Transactions on Fuzzy Systems Outstanding Paper Award in 2014, the North American Fuzzy Information Processing Society (NAFIPS) Early Career Award in 2014, the IEEE Systems, Man and Cybernetics (SMC) Society Early Career Award in 2017, and the IEEE SMC Society Best Associate Editor Award in 2018. He was a finalist of the IEEE Transactions on Affective Computing Most Influential Paper Award in 2015, the IEEE Brain Initiative Best Paper Award in 2016, the 24th International Conference on Neural Information Processing Best Student Paper Award in 2017, the Hanxiang Early Career Award in 2018, and the USERN Prize in Formal Sciences in 2019. He was a selected participant of the Heidelberg Laureate Forum in 2013, the US National Academies Keck Futures Initiative (NAKFI) in 2015, and the US National Academy of Engineering German-American Frontiers of Engineering (GAFOE) in 2015. His team won the First Prize of the China Brain-Computer Interface Competition in 2019.

Prof. Wu is an Associate Editor of the IEEE Transactions on Fuzzy Systems (2011-2018; 2020-), the IEEE Transactions on Human-Machine Systems (since 2014), the IEEE Computational Intelligence Magazine (since 2017), and the IEEE Transactions on Neural Systems and Rehabilitation Engineering (since 2019). He was the lead Guest Editor of the IEEE Computational Intelligence Magazine Special Issue on Computational Intelligence and Affective Computing, and the IEEE Transactions on Fuzzy Systems Special Issue on Brain Computer Interface. He is a Senior Member of the IEEE, a Board member and Distinguished Speaker of the NAFIPS, and a member of IEEE Systems, Man and Cybernetics Society Brain-Machine Interface Systems Technical Committee, IEEE CIS Fuzzy Systems Technical Committee, Emergent Technologies Technical Committee, and Intelligent Systems Applications Technical Committee. He has been Chair/Vice Chair of the IEEE CIS Affective Computing Task Force since 2012.

Speech Title: Efficient Optimization of Fuzzy Systems

Abstract: Fuzzy systems have been widely used in classification and regression. However, for big data, traditional evolutionary algorithm based and full-batch gradient descent based optimization strategies become too costly. This talk first introduces functional similarity/equivalence between fuzzy systems and classical machine learning models such as radial basis function network, mixture of experts. Then, it extends their optimization techniques, such as mini-batch gradient descent, DropOut, Batch normalization and Adam, to the optimization of fuzzy systems.

Professor Jun Yang

IEEE Fellow, IET Fellow, AAIA Fellow

Loughborough University, U.K

Biography: Jun received the B.Sc. degree in automation from the Department of Automatic Control, Northeastern University, Shenyang, China, and the Ph.D. degree in control theory and control engineering from the School of Automation, Southeast University, Nanjing, China, in 2006 and 2011, respectively. He worked in School of Automation, Southeast University as Lecturer from 2011, Associate Professor from 2014, and Full Professor from 2018 all in Control Systems. Since 2020, he has been with the Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough, U.K., as a Senior Lecturer and is promoted to a Reader in 2023. His research interests include disturbance observer, motion control, mechatronics, robotics, and automation. Dr. Yang was the recipient of the EPSRC New Investigator Award. He serves as an Associate Editor or Technical Editor for IEEE Transactions on Industrial Electronics, IEEE-ASME Transactions on Mechatronics, IEEE Open Journal of Industrial Electronics Society, etc. He is a Fellow of IEEE, IET, and AAIA.

Speech Title: Safety-Critical Control Under Disturbances: A Control Barrier Function Approach

Abstract: Safety-critical control is significant for autonomous system applications where safety is an utmost concern. Control barrier function (CBF)-based control has shown its promising potential and power in delivering formal safe property of dynamic nonlinear systems. The presence of disturbances has negative effects on CBF-based control, leading to formal safety guarantee violations and degraded control performance. In this talk, we will introduce the background of safety-critical control, highlight the motivation why formal method is required, give a comprehensive tutorial on CBF-based control approaches, and elaborate the emerging methods on safety-critical disturbance rejection control and their applications to interactive robotics and autonomous cranes.