Keynote Speakers

Prof. Jianwei Zhang, Professor and director of TAMS,
University of Hamburg, Germany

Jianwei Zhang is professor and director of TAMS, Department of Informatics, University of Hamburg, Germany. He received both his Bachelor of Engineering (1986, with distinction) and Master of Engineering (1989) at the Department of Computer Science of Tsinghua University, Beijing, China, his PhD (1994) at the Institute of Real-Time Computer Systems and Robotics, Department of Computer Science, University of Karlsruhe, Germany. Jianwei Zhang is life-long Academician of Academy of Sciences in Hamburg Germany.
Jianwei Zhang´s research interests include multimodal informatin processing; cognitive sensor fusion; fast learning algorithms; neuro-fuzzy models for sensory-motor control tasks; reinforcement learning of assembly sequences; natural human-robot interaction; self-valuing learning of robot grasping and in-hand manipulation; multimodal learning architecture; experience-based robot learning; coded structured light for 3D modelling; best view algorithm for active robot vision; bio-inspired multimodal control, modular reconfigurable robots; surgical assistant robots; mobile manipulation service robots, etc. In these areas he has published about 500 journal and conference papers, technical reports and four books. He holds 40+ patents on intelligent components and systems.
Jianwei Zhang is the coordinator of the DFG/NSFC Transregional Collaborative Research Centre SFB/TRR169 “Crossmodal Learning: Adaptivity, Prediction and Interaction” and several EU robotics projects, including the RACE (Robustness by Autonomous Competence Enhancement) Project which is the first one applying high-level learning, planning and reasoning AI methods in service robots. He has received multiple best paper awards. He is the General Chairs of IEEE MFI 2012, IEEE/RSJ IROS 2015, and the International Symposium of Human-Centered Robotics and Systems 2018.
For the Bachelor courses of Informatics, Jianwei Zhang teaches Computer Structures and Organization Introduction to Robotic, and Embedded Systems. For the Master courses of Informatics, he holds Intelligent Robot Systems, Machine Learning, and Advanced Seminar on Intelligent Multimodal Robot Systems. As a PhD course of Interdisciplinary Research Training, he also teaches Advanced Multimodal Information Processing.

Prof.Paweł D. Domański
Warsaw University of Technology, Poland

Paweł D. Domański was born in Warsaw, Poland in 1967. He received the M.S. degree in 1991, Ph.D. degree in 1996 and D.Sc. degree in 2018, all in control engineering from the Warsaw University of Technology, Faculty of Electronics and Information Technology. He works in the Institute of Control and Computational Engineering, Warsaw University of Technology from 1991. Apart from scientific research he participated in dozens of industrial implementations of APC and optimization in power and chemical industries. He is the author/co-author of two books and more than 140 publications. His main research interest is with industrial APC applications, control performance quality assessment, anomalies detection and optimization.

Title:How to measure the controller? Truths and myths.
Abstract: The quality of control systems affects the resulting process efficiency. This truth is obvious, at any rate to control engineers, or at least most of them. However, industrial reality very often contradicts this obvious principle. Visits to industrial facilities, especially in the process industry, indicate that the control system is not given due attention and control structures and their tuning leave much to be desired. There are many reasons for this, the rational ones and the others. From a technical point of view, something can only be improved when we are aware that it is something that is malfunctioning. Thus, we need to be able to measure and evaluate the quality of control systems. Unfortunately, or fortunately, the literature shows dozens of solutions. However, they are very often detached from industrial reality, which is neither simple nor linear nor Gaussian and human influence cannot be removed. This paper tries to organize, from an industrial perspective, an overview of methods indicating potential directions and ranges of applicability of available approaches. A one-size-fits-all prescription cannot be given. But one can at least sort out the approaches and eliminate erroneous habits. This will allow to update procedures and improve good practices.


Invited Speakers


Prof. Büchi Roland,
Zurich University of Applied Sciences, Switzerland

Roland Büchi, received the M.S. degree in Electrical Engineering at ETH Zurich in 1994 and the Ph.D Degree in 1996 at the Institute of Robotics at ETH Zurich.He is head of the section of Information Technology, Electrical Engineering and Mechatronics and researcher in the field of control theory at ZHAW, Zurich University of Applied Sciences, School of Engineering, Winterthur, Switzerland.

Assoc.Prof. Rafiq Ahmad
University of Alberta, Canada

Dr. Rafiq Ahmad is an Associate Professor in the Department of Mechanical Engineering at the University of Alberta. He is also a Faculty Associate at the Nasseri School of Building Sciences and Engineering at the University of Alberta. He is the founder and director of the “Smart & Sustainable Manufacturing Systems Laboratory (SMART Lab)”, which focuses on systems design and engineering. Dr. Ahmad is also the founder and director of “Aquaponics 4.0 Learning Factory (AllFactory),” a unique learning factory researching system design and development for plants and fish production in an indoor, vertical, symbiotic ecosystem soil-less environment. His research interest includes smart engineering systems design, technologies development, digitization, lean manufacturing, hybrid manufacturing, additive manufacturing, robotics, and green technologies (3Rs: recycling, remanufacturing, and repair). Dr. Ahmad is a Ph.D. in advanced manufacturing from Ecole Centrale de Nantes, France, and Master’s in design and manufacturing from ENSAM-Paris, France. He holds a BSc. Degree in Mechanical Engineering from the UET-Peshawar, Pakistan. Dr. Ahmad obtained a two-year Post-doctoral fellowship from the University of Luxembourg. Dr. Ahmad is a board member of the International Society of Automation - Edmonton (as Co-UofA Student Section Advisor) and a member of APEGA, CSME, and ASME. He is also an active editor, reviewer, and organizer of numerous international conferences and journals. Dr. Ahmad is the recipient of the prestigious Edmonton’s 2022 Top 40 under 40 Award by Edify Magazine for his serial innovation and streamlined technology development to impact our society. He is also the director and founder of the Canadian not-for-profit ProBEEs Digital Education Society. He served as conference chair and steering committee member for ICCMA for many years.


Asst. Prof. Xiaofeng Xiong
University of Southern Denmark, Denmark

He obtained PhD degree on Computer Science at Goettingen University (Germany) in 2015, later spent Postdoc at Goettingen Medical Center and Hamburg University, Germany. His research focuses on bionic robots, human motor control, robot-inspired biology, and wearable robotics, which have been funded by two EU and three Danish grants. He is an associate editor of the journal adaptive behaviour and advanced bionics (incoming) His research results have been published in high-ranking journals (IEEE trans. ), and given by Emerald Publishing Robot Innovation Award (UK, 2013), CLAWAR Association Best Technology Paper Award (UK, 2020), and WearRAcon Wear Robotics Challenge Competition Award finalist (USA, 2021). His research on bionic robots and wearable robotics were featured by Human Frontier Science Program (HFSP).

Title: Physical intelligence of robots and animals
Abstract: The capability to interact physically with complex environments is a hallmark of animals and humans, such as insect navigation and human manipulation (of flexible tools, e.g., whips). How they handle neural, muscle, and tool complexities is an interesting question, where robotics and computational neuroscience can mutually benefit from. In this talk, I will present how robots and neuromechanical models that can be used to provide novel hypotheses for insect navigation, human arm swings, and human manipulation of whips. It shows a way from machines for (uncovering) biological intelligence. Another way from biological to machine intelligence will be presented in insect-like walking and wearable robots.