
Keynote Speakers (to be updated soon)
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.
Prof. Alex Mason,
Norwegian University
of Life Sciences (NMBU), Norway
Professor Alex Mason received a BSc(Hons) in Computer and Multimedia Systems from the University of Liverpool in 2005, and a PhD in Wireless Sensor Networks and their Industrial Applications from Liverpool John Moores University (LJMU) in 2008, both in the UK. From 2008-2017 he performed research related to sensor technology and led a research team at LJMU related to this topic. He moved to Norway in 2017 to take a position as Project Engineer for Animalia AS where he was responsible for developing sensor and automation technology for the meat sector. In 2018 he also joined NMBU and became a Research Professor in 2020 after establishing a team working on Food Automation. In 2025, Alex was awarded tenured Professorship, and appointed Head of Robotics at NMBU. Alex has ca. 270 peer-reviewed publications, which include several patents. He currently co-ordinates the Horizon 2020 project RoBUTCHER.
Prof. Adrian Olaru
University Politehnica of Bucharest,
Romania
Prof. Adrian Olaru finished the
University Politehnica of Bucharest,
Faculty of Machines and Manufacturing
Systems, Romania, in 1974, head of
promotion. From 1974 until 1990 he
worked as a designing engineer at the
"Optica Romana" Enterprise, also being
an associate assistant at the Faculty of
Machine-Building Technology of the
Polytechnic Institute of Bucharest. In
1990 Prof. Adrian became an appointed
lecturer at the Faculty of Technological
Systems Engineering and Management, the
Machine-Tools Department. Now, he is
university full professor, and teaches
the following courses: Industrial Robots
Dynamics, LabVIEW application in
modeling and simulation of the dynamic
behavior of robots, Technological
Transport Systems, Electrohydraulic
Servosystems, Analyze and Syntese of
Electrohydraulic Servosistems for
Industrial Robots, Personal and social
robots and Vibration of the virtual
prototypes of industrial robots. Prof.
Adrian Olaru has published over 160
national and international papers
concerning modeling and simulation of
hydraulic power system, technological
transport systems, electrical and
hydraulic servo systems and dynamic
behavior of industrial robots. For
recent relevant details, see the
publication list and the web page. He
also has substantial contribution for
over than ten technical books. Prof.
Adrian Olaru was invited professor of
the prestigious universities arround the
world and the invited speacker at the
different international conferences from
Slovakie, France, Italy, China, India,
Iran, Poland, Autrich, Rusian
Federation, United Arab Emirates,
Turkie, Croatie. He was coopted each
year in the more than 30 International
Technical Committees and like general
co-chair from the different
international conferences arroun the
world: USA, Australy, India, United Arab
Emirates, Porto Rico, China, Singapore,
Malayesia, Japan, Tayland, Slovaky,
Czech Republic.
Assoc. Prof. Fernando Perez-Peña,
University of Cádiz, Spain
Fernando Perez-Peña received the Engineering degree in Telecommunications from the University of Seville (Spain) and his Ph.D. degree (specialized in neuromorphic motor control) from the University of Cadiz (Cadiz, Spain) in 2009 and 2014 respectively. In 2015 he was a postdoc at the Center for Cognitive Interaction Technology (CITEC) of Bielefeld University, Germany. He has been an Assistant Professor in the Architecture and Technology of Computers Department of the University of Cadiz since 2014. He is serving as a Technical Member of the Neural Systems and Applications in the Circuits and System Society of IEEE. His research interests include neuromorphic engineering, CPG, motor control and neurorobotics.
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.