Zurich University of Applied Sciences (ZHAW)Switzerland
Prof. Dr. Roland Büchi is a Professor at the School of Engineering, Zurich University of Applied Sciences (ZHAW), specializing in control systems engineering and applied AI. His affiliation includes leadership roles in research projects such as the ongoing 'Digital Bridge to Computer Science' initiative. With a career spanning decades, he maintains active research output and industrial collaborations. Research Interests: Büchi focuses on control systems optimization , particularly PID controller tuning using AI methods, system identification, and applications in robotics and drone technology. His work bridges theoretical control theory with practical implementations in mechatronics. Recent efforts explore machine learning for hysteresis modeling and swarm optimization for control systems. Publication Trends: His 15 most recent works (2018-2024) emphasize AI-driven control optimization , drone technology advancements, and engineering education. Dominant themes include PID parameter tuning for time-delayed systems, drone telemetry, and adaptive learning algorithms. A notable shift toward AI/ML applications in control engineering emerged post-2020. Labs and Teams: Büchi collaborates with researchers like Lukas Gruber and has historical ties to ETH Zurich’s robotics projects. His work involves experimental validation at ZHAW’s engineering facilities, with patents in turbocharger magnetic bearing systems.
Bianca Badii is a Researcher affiliated with the Rehabilitation Engineering Lab at ETH Zürich, part of the College of Engineering. She is based at the Gloriastrasse 37/39 location in Zurich, Switzerland. Her work focuses on interdisciplinary engineering solutions for rehabilitation, likely involving cutting-edge technologies to enhance human mobility and neural interfaces. Contact: bianca.badii@hest.ethz.ch .
Prof. Dr. Sarah Dégallier Rochat is Head of the strategic thematic field 'Humane Digital Transformation' at Bern University of Applied Sciences (BFH). She holds a joint appointment as Professor at the School of Engineering and Computer Science and serves as co-leader of the Computer Perception and Virtual Reality Lab (cpvrLab) within the Institute for Human-Centered Engineering. Her educational background includes: Ph.D. in Robotics from École Polytechnique Fédérale de Lausanne (EPFL) Master's in Mathematics from EPFL Teaching Diploma in Mathematics from Haute École Pédagogique de Lausanne Psychology studies at University of Lausanne Her research focuses on human-centered technological development with emphasis on: Designing inclusive human-machine interfaces through participatory approaches Developing upskilling strategies for industrial workforce adaptation Examining how techno-narratives shape societal perceptions of technology Creating collaborative robotic systems for agile manufacturing (Cobotics) Exploring mixed reality interfaces for worker augmentation Her publications demonstrate strong interdisciplinary focus on robotics and human-centered AI, with recent works exploring human augmentation in industry, ethical AI implementation, and participatory robot programming. The trajectory shows increasing emphasis on socio-technical systems and workforce empowerment. Significant awards include: Industry 4.0 Shapers Award (2019) CHIRA Best Paper Award (2023) She leads multiple research projects funded by Innosuisse, SNF, and EU programs, including: CODIMAN (Cobotics and workplace humanization) Agile Robotics for High-Mix Low-Volume Production Upskill at Work (digital literacy initiatives) Augmented workers with mixed reality interfaces As founder of Auto-Mate Robotics, she develops flexible robotic cells for industrial applications. She co-leads the Computer Perception and VR Lab and serves on advisory boards including the Swiss Cobotics Competence Center and EUA Task Force on AI.
Swiss Federal Institute of Technology in LausanneSwitzerland
Auke Jan Ijspeert is a full professor at the École Polytechnique Fédérale de Lausanne (EPFL), where he serves as head of the Biorobotics Laboratory (BioRob). He holds a primary affiliation with the Institute of Bioengineering and a secondary affiliation with the Institute of Mechanical Engineering. His academic leadership and research excellence have established him as a leading figure in bio-inspired robotics and computational neuroscience. B.Sc./M.Sc. in Physics, École Polytechnique Fédérale de Lausanne (EPFL), 1995 Ph.D. in Artificial Intelligence, University of Edinburgh, 1999 Postdoctoral research at IDSIA/EPFL and University of Southern California (USC) SNF Assistant Professor at EPFL, 2002 Promoted to Associate Professor, October 2009 Promoted to Full Professor, April 2016 His research lies at the intersection of robotics, computational neuroscience, nonlinear dynamical systems, and applied machine learning. He investigates animal locomotion and movement control using numerical simulations and robotic platforms, aiming to understand biological principles and apply them to novel robot designs and controllers. His work has led to groundbreaking robots like the salamander-inspired Pleurobot and amphibious robotic systems. He also explores applications in assistive technologies such as exoskeletons and smart furniture for people with limited mobility. The recent publications reflect a strong trend in bio-inspired robotics, neuromechanical modeling, and the use of robots to understand biological locomotion. Key themes include spinal cord modeling for gait control, amphibious and aquatic locomotion, central pattern generators, and the evolutionary transition from swimming to walking. His work integrates neuroscience, biomechanics, and robotics to create physical models that serve both engineering and scientific discovery purposes. Scientific Awards and Honors: IEEE Fellow (2020) Best Paper Prize, CLAWAR 2019 Best Conference Paper Award, SAB 2018 Best Paper Award, IEEE RO-MAN 2014 Best Paper Award, IEEE Humanoids 2007 Overall Best Paper Award, IEEE ICRA 2002 Young Professorship Award, Swiss National Science Foundation Marie Curie Scholarship, European Commission Auke Ijspeert has been actively involved in academic service, serving as an associate editor for IEEE Transactions on Robotics (2009–2013) and Soft Robotics (2018–2021), and as an associate editor for IEEE Transactions on Medical Robotics and Bionics and the International Journal of Humanoid Robotics. He has secured major funding from the Swiss National Science Foundation, Human Frontier Science Program, European Commission (FP7, H2020), Human Brain Project, and other international agencies. He has organized seven major international conferences and served on over 50 program committees. His laboratory, BioRob, is a hub for interdisciplinary research, training students and researchers in biorobotics, and fostering collaboration across neuroscience, robotics, and biomechanics.
Swiss Federal Institute of Technology in LausanneSwitzerland
Rafael Pereira Pires is a Lecturer and researcher at École polytechnique fédérale de Lausanne (EPFL) , affiliated with the Scalable Computing Systems Laboratory (SACS) and IC-SIN units. His research focuses on systems solutions at the intersection of privacy, efficiency, and machine learning in distributed environments. Education PhD in Computer Science (2019, University of Neuchâtel, Switzerland) Professional Master in Mechatronics (2014, IFSC, Brazil) Master in Computer Science (2009, UFSC, Brazil) His work explores privacy-preserving decentralized learning , trusted execution environments , and resource-efficient distributed systems . Recent publications address techniques like model fragmentation, approximate caching, and secure aggregation in decentralized learning contexts. Key trends in his 2023-2025 publications include: Advancements in federated learning and Mixture-of-Experts (MoE) models Applications of Trusted Execution Environments (SGX) to decentralized systems Optimization techniques for energy-aware and low-cost learning Scientific recognition includes the 2019 Léon Du Pasquier et Louis Perrier award for his PhD thesis. He has contributed to open-source tools like DecentralizePy and served as reviewer/PC member for top conferences including NeurIPS , Middleware , and ICDCS .
University of Applied Sciences and Arts LucerneSwitzerland
Björn Jensen is a Professor and Co-Head of the AI Robotics Research Lab at Lucerne University of Applied Sciences and Arts (HSLU), specifically within the Lucerne School of Computer Science and Information Technology. He also teaches medical robotics at the University of Bern's Biomedical Engineering Program. His professional background includes roles at the Autonomous Systems Lab at EPFL, Switzerland, and founding the startup Singleton 3D focusing on 3D laser measurement technology. Educational background: MSc in Electrical Engineering (Automation & Image Processing) from TU Darmstadt (1998), followed by a Master's in Industrial Management from the same institution. PhD in human-robot interaction from EPFL (2005), with research stints at Tokyo University (2005) and involvement in projects like Robox@Expo.02 and Smarter-Elrob. Research interests span robotics, human-robot interaction, autonomous systems, medical robotics, and sensor-based navigation. Notable projects include the 'Smart Ennoblement Factory', 'NaviMow' autonomous lawnmower, and 'Bagger Assistenzsysteme'. His work emphasizes real-world applications of robotics in dynamic environments and human-centric systems. Lab leadership includes co-directing the AI Robotics Research Lab, focusing on advancing robotics technologies for practical scenarios. No scientific awards explicitly listed, but contributions to industry-academia collaborations are highlighted through startup ventures and applied research projects.
Zurich University of Applied Sciences (ZHAW)Switzerland
Alberto Colotti is a Professor at the Zurich University of Applied Sciences (ZHAW), School of Engineering, where he heads the Power Electronics and Drives team within the Institute of Mechatronic Systems. He serves as a lecturer for Power Electronics and Drive Systems and maintains an active research profile in power conversion technologies. His research spans power electronics, electric drives, and mechatronic systems with emphasis on wide-bandgap semiconductors (GaN/SiC), motor design for traction applications, and thermal management in power converters. Key specialties include synchronous reluctance machines, IPMSM development, and educational test bench design for instructional purposes in drive systems. Publications from 2014-2024 reveal consistent innovation in power converter topologies and machine design, with recent work focusing on instructional test benches (2024) and SiC thermal modeling (2019). His research bridges theoretical modeling with experimental validation, particularly in gallium nitride applications and traction drive systems for small vehicles. Colotti has led multiple research projects: Control platform for gallium nitride-based power converter (Project leader, completed) Sigrid – Smart Interlocking Grid (Project leader, completed) Adastec (Project leader, completed) Lisrel (Project leader, completed) Holistic mechatronic design for a sonic toothbrush (Deputy project leader, completed) Multipol Resolver with passive Rotor (Deputy project leader, completed) He directs the Power Electronics and Drives team at ZHAW's Institute of Mechatronic Systems, which specializes in advancing power electronics research through both simulation and experimental validation of next-generation drive systems.
Dr. Peter Wolf is a Lecturer at the Department of Health Sciences and Technology (D-HEST) at ETH Zurich. His research focuses on robot-aided motor learning and sports engineering, particularly exploring concurrent feedback strategies for efficient motor task learning and applications in rowing and climbing. He advises students in the Medical Technology and Human Movement Science & Sport majors, emphasizing interdisciplinary approaches combining biomechanics, mechatronics, and coding. His research group develops tools to support athletes and rehabilitation patients, with a focus on exosuits, exoskeletons, and robotic feedback systems. Notable projects include optimizing gait parameters for adolescents with crouch gait and enhancing wearable robotic systems for daily mobility support. Dr. Wolf also contributes to curriculum design, recommending courses like Biomedical Engineering, Neural Control of Movement, and Machine Learning for Healthcare. His work bridges biomechanical analysis, robotics, and clinical applications, with recent innovations in vestibular stimulation for sleep disorders and thermal stress monitoring for occupational workers. Collaborations span sports science, rehabilitation engineering, and human-robot interaction, reflecting his commitment to applied and interdisciplinary research.
Bruno Kaufmann is affiliated with ETH Zürich as a Researcher in the Department of Rehabilitation Engineering under the Professorship for Robotic Systems. His role involves contributing to research and development within the field of robotic systems applied to rehabilitation engineering. He is based at the LEO B 1 building in Leonhardstrasse 27, Zürich, Switzerland. His research interests focus on advancing robotic technologies for medical applications, including mechatronics, biomedical engineering, and human-machine interaction. These efforts aim to improve assistive devices and rehabilitation methodologies through innovative engineering solutions.
Zurich University of Applied Sciences (ZHAW)Switzerland
Dr. Duncan Webster is a Researcher at the Institute of Mechatronic Systems , affiliated with the School of Engineering at the Zurich University of Applied Sciences (ZHAW) . Based in Winterthur, Switzerland, he leads advanced research projects at the intersection of engineering and biomedical applications, focusing on automation, molecular analysis, and diagnostic technologies. Email: duncan.webster@zhaw.ch Contact: +41 (0) 58 934 42 20 Address: Technikumstrasse 9, 8400 Winterthur, Switzerland His research interests include: Automation of protein evolution for biochemical engineering Development of multi-mode Raman optical activity instruments Next-generation prostate cancer diagnostics via protein detection Integration of solid-state nanopores into microfluidic architectures
Adrian Ensmenger is a Researcher affiliated with the Professur für Robotersysteme (Robotics Systems Professorship) at ETH Zürich. His work focuses on advancing robotic systems and intelligent automation technologies. While specific details about his educational background or grants are not provided in the text, his role indicates engagement with cutting-edge research in robotics engineering. No publications authored by him were listed in the provided materials.
Fidel Esquivel Estay is a Professor holding the Staff of Professorship for Robotic Systems at ETH Zürich, affiliated with the Institute for Robotics and Intelligent Systems (IRS) under the Department of Mechanical and Process Engineering. His research focuses on Robotics, Intelligent Systems, and Automation. He is based in Zürich, Switzerland, and can be reached at fidel.esquivel@mavt.ethz.ch. The IRS at ETH Zürich is renowned for advancing robotics and intelligent system technologies across engineering and applied sciences.
Zurich University of Applied Sciences (ZHAW)Switzerland
Dr. Philip Marmet is a Researcher and Lecturer at the Institute of Computational Physics (ICP) within the School of Engineering at Zurich University of Applied Sciences (ZHAW). His work focuses on Multiphysics and Multiscale simulations, characterization and stochastic modeling of microstructures, with particular expertise in solid oxide fuel cell electrode design. His educational background includes a PhD in Physics/Modeling and Simulation from the University of Fribourg (2019-2023), an MSc in Physics/Soft Matter Theory from the same institution (2013-2016), and an MSc in Engineering from Bern University of Applied Sciences (2011-2013). PhD in Physics / Modeling and Simulation, Solid Oxide Fuel Cells, University of Fribourg (2019-2023) MSc in Physics / Soft Matter Theory, University of Fribourg (2013-2016) MSc in Engineering BFH / Industrial Technologies, Bern University of Applied Sciences (2011-2013) BSc in Mechanical Engineering / Mechatronics, Bern University of Applied Sciences (2003-2007) Dr. Marmet's research spans Multiphysics Simulation, Multiscale Modeling, Microstructure Characterization, and Digital Materials Design. His work bridges theoretical modeling with experimental validation to optimize materials for energy applications. He has developed specialized methodologies for virtual microstructure variation and optimization of porous materials, particularly for solid oxide fuel cells and aerosol filters. His publication record shows a clear progression toward increasingly sophisticated multiscale modeling approaches, with recent work focusing on stochastic microstructure modeling using pluri-Gaussian methods. His research demonstrates strong integration of computational techniques (including GeoDict, Comsol Multiphysics, ANSYS, OpenFOAM, and Matlab/Simulink) with experimental validation. Best graduation results of 2013 "Gold", Master of Science in Engineering Dr. Marmet supervises student projects and lectures Analysis 1 and 2 for bachelor courses. His research has received funding from the Swiss Federal Office of Energy (SFOE) and Eurostars program. He has developed practical software tools including the Python app for stochastic microstructure modeling of SOC electrodes and the Characterization-app for standardized microstructure analysis, demonstrating his commitment to translating research into practical engineering solutions. His work is organized around the Digital Materials Design workflow, connecting virtual microstructure generation, automated characterization, and multiphysics simulation to enable data-driven optimization of energy materials without extensive experimental iteration.
Prof. Marco Hutter is a Full Professor at the Department of Mechanical and Process Engineering at ETH Zürich, and Deputy Head of the Institute for Robotics and Intelligent Systems. His research focuses on advanced robotics, including autonomous legged systems, robotic perception, and control strategies for challenging environments. He leads projects in areas such as forest inventory using legged robots, space exploration robotics, and mobile manipulation systems. His work emphasizes real-world deployment, with contributions to robotic navigation, sensor integration, and policy optimization. Prof. Hutter collaborates on large-scale datasets and frameworks like ROS-LLM for embodied AI, and explores applications in logistics, construction, and planetary exploration. His team develops both hardware (e.g., LEVA logistic vehicles) and software solutions (e.g., risk-guided diffusion models for safety-critical systems). Key projects include ETHcavation (construction environment understanding) and TartanGround (robot perception datasets). He pioneers work in agile locomotion policies, magnetic climbing robots, and multi-agent robotic teams for parcel delivery. His research bridges theoretical advancements with practical implementations, addressing challenges in terrain adaptation, energy efficiency, and robustness in autonomous systems.
Swiss Federal Institute of Technology in LausanneSwitzerland
Giovanni Iacca is an Associate Professor at the Department of Information Engineering and Computer Science (DISI) of the University of Trento, Italy, where he leads the Distributed Intelligence and Optimization Lab (DIOL). He serves as Coordinator of the Master's Degree in Computer Science and Deputy Director of the Information Engineering and Computer Science Doctoral School. Dr. Iacca has over 15 years of industrial experience in mechatronics and optimization applied to engineering, logistics, and scheduling. Dr. Iacca received his PhD in 2011 from the University of Jyväskylä, Finland, and his MSc in 2006 from the Technical University of Bari, Italy. His academic career includes: 2021-present: Associate Professor, University of Trento 2018-2021: Tenure-track Assistant Professor, University of Trento 2017-2018: Postdoc, RWTH Aachen University, Germany 2013-2016: Postdoc, EPFL and University of Lausanne, Switzerland 2012-2016: Postdoc, INCAS³, The Netherlands Dr. Iacca's research bridges fundamental and applied aspects of artificial intelligence with particular emphasis on evolutionary computation and explainable AI. His work spans machine learning, optimization techniques, distributed systems, and their practical implementations. Recent research directions include federated learning, interpretable reinforcement learning, neural architecture search, and optimization for resource-constrained environments. He teaches courses on Computer Architectures, Introduction to Machine Learning, Bio-Inspired Artificial Intelligence, Optimization Techniques, and AI in Medicine. His publication record demonstrates a strong trend toward developing transparent and efficient AI systems. Recent papers focus on making complex AI models more interpretable while maintaining performance across diverse domains from healthcare to supply chain management. His work on evolutionary approaches to explainable AI has gained significant recognition in the computational intelligence community. Scientific Awards and Editorial Roles EvoApplications Best Paper Award (2017) UKCI AWARENESS Best Paper Award (2012) IEEE CIS Outstanding Student-Paper Award (2011) IEEE Senior Member (2023) Associate Editor, Evolutionary Intelligence (2024) Editorial Board Member, Memetic Computing (2024) Associate Editor, IEEE Transactions on Evolutionary Computation (2023) Dr. Iacca has successfully supervised multiple PhD students including Andrea Ferigo, Hyunho Mo, and Leonardo Lucio Custode. His research is supported by various grants and collaborations with industry partners like MyAv. He serves as chair for PPSN 2026 and has organized workshops including the Workshop on Awareness and Consciousness in Artificial Intelligence (ACAI). As leader of the Distributed Intelligence and Optimization Lab (DIOL), Dr. Iacca oversees a research team working at the intersection of evolutionary computation, machine learning, and distributed systems. The lab focuses on developing novel algorithms that balance computational efficiency with interpretability, with applications spanning from embedded systems to large-scale distributed computing environments. Current projects include interpretable reinforcement learning, federated neuroevolution, and optimization for edge computing.
