Dr. Hao Ye is a Researcher affiliated with the Gruppe Pané Vidal at ETH Zürich. His work focuses on advanced nanomaterials, biomedical engineering, and their applications in targeted therapies, drug delivery systems, and regenerative medicine. He specializes in developing nanoscale systems for cancer treatment, including microrobotic devices and biomimetic platforms for enhanced therapeutic efficacy. Dr. Ye's research explores interdisciplinary areas such as piezoelectric catalysis, magnetic nanomaterials, and exosome-based drug delivery. His group pioneers innovations like clinically applicable magnetic microrobots and nanoassemblies tailored for tumor microenvironment interactions. Key achievements include the design of sub-10 nm magnetic nanoparticles with pH stability, magnetoelectric microrobots for spinal cord injury repair, and bioinspired extrusion-based microfluidic fabrication of soft microrobots. His work emphasizes translating nanotechnology into practical medical solutions.
Swiss Federal Institute of Technology in LausanneSwitzerland
Bokeon Kwak is a Postdoctoral Researcher at the Swiss Federal Institute of Technology Lausanne (EPFL) , affiliated with the School of Engineering and the Institute of Mechanical Engineering . They work within the Laboratory of Intelligent Systems , focusing on interdisciplinary robotics research. Fields of Interest: Bio-inspired robotics, Edible Robotics, Soft Robotics Contact: bokeon.kwak@epfl.ch
Swiss Federal Institute of Technology in LausanneSwitzerland
Charbel Toumieh is a Research Fellow at the École Polytechnique Fédérale de Lausanne (EPFL), based in the Intelligent Systems Laboratory (LIS) under the School of Engineering (STI). His research focuses on advanced robotics, particularly in aerial systems, motion planning, and autonomous systems. He holds a postdoctoral position and contributes to projects involving multi-agent coordination, high-speed navigation, and energy-efficient drone designs. Key research areas include teleoperation of aerial swarms, adaptive morphing for avian-inspired drones, and decentralized multi-agent planning. His work addresses challenges in cluttered environments, dynamic obstacle avoidance, and real-time trajectory optimization. The LIS lab, part of the Institute of Microengineering (IGM), emphasizes innovative solutions in intelligent systems and robotics. Recent publications highlight advancements in motion planning algorithms, safe corridor generation using voxel grids, and GPU-accelerated exploration techniques. His research bridges theoretical control systems with practical applications in autonomous robotics, aiming to enhance efficiency and resilience in robotic systems.
Swiss Federal Institute of Technology in LausanneSwitzerland
Esther Amstad is an Associate Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering and the Department of Materials Science and Engineering. She leads the Soft Matter for Life Sciences Laboratory (SMAL) and directs the doctoral program in Materials Science and Engineering. Her roles include teaching courses on soft matter and mentoring PhD students in interdisciplinary research. Current affiliations: EPFL STI IMX SMAL, EPFL STI STI-SMX SMX-ENS, EPFL VPA-AVP-DLE AVP-DLE-EDOC EDMX-GE (Doctoral Program Director), and EPFL VPA-AVP-DLE AVP-DLE-EDOC CDOCT (Doctoral Commission Member). Her research focuses on soft matter , hydrogels , 3D printing , and colloidal systems . She develops self-healing materials , biocompatible composites , and bioinspired structures using microfluidics and advanced fabrication techniques. Key themes include mechanical reinforcement , stimuli-responsive materials , and multi-sensory integration for biomedical and robotics applications. Recent publications highlight her work on granular hydrogels , 3D-printed biocomposites , and microfluidic encapsulation . These studies span tissue engineering , photonic materials , and sustainable resource conversion . Her lab's output emphasizes soft robotics , structural color , and programmable release systems . Esther Amstad supervises 12 current PhD students and has directed 14 PhD theses at EPFL. Her team explores applications in artificial cells , self-healing e-skin , and mechanoreceptive devices . The lab employs microfluidic platforms , colloidal assembly , and additive manufacturing to address challenges in materials longevity and functionality.
Swiss Federal Institute of Technology in LausanneSwitzerland
Benhui Dai is a Doctoral Assistant at the Computational Robot Design & Fabrication Lab within the Create Lab (CREATE-LAB), part of the School of Engineering at École Polytechnique Fédérale de Lausanne (EPFL) , Switzerland. He is also enrolled in the Doctoral Program in Robotics, Control, and Intelligent Systems at EPFL. Education Bachelor's Degree in Mechanical Engineering Master's Degree in Biosystems Engineering, Zhejiang University (ZJU), China Research Interests : Soft robotics and materials development, e-skins (tactile and biosensors), bio-inspired and humanoid robots, food robotics, agricultural robotics, and human-robot-environment interactions. His work integrates mechanics, bioengineering, materials science, optics, and artistic approaches to robotics design. Scientific Awards Best Poster Award, IEEE RoboSoft 2025 Labs & Teams : Affiliated with the CREATE Lab at EPFL, focusing on computational methods for robot design and fabrication.
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.
Swiss Federal Institute of Technology in LausanneSwitzerland
Alexander Dittrich is a doctoral researcher at École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the School of Engineering and the Laboratory of Intelligent Systems . His work focuses on Hebbian learning , bio-inspired neural network architectures , and the simulation of tensegrity robots , with applications in deep reinforcement learning , meta learning , and neuroevolution . Recent publications include: (1) a 2025 RoboSoft paper on tensegrity-based robotic legs with variable stiffness (a Best Paper Finalist ), and (2) a 2023 ICRA paper on the AIMY table tennis ball launcher's high-level trajectory control system. These projects reflect his expertise in merging adaptive AI with soft robotics. Awards : Best Paper Finalist, RoboSoft 2025
Swiss Federal Institute of Technology in LausanneSwitzerland
Auke Ijspeert is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), leading the Biorobotics Laboratory (BioRob). He earned a B.Sc./M.Sc. in physics from EPFL (1995) and a Ph.D. in artificial intelligence from the University of Edinburgh (1999). After postdoctoral work at IDSIA, EPFL, and the University of Southern California (USC), he returned to EPFL as an SNF assistant professor, becoming associate professor in 2009 and full professor in 2016. He holds primary affiliation with EPFL's Institute of Bioengineering and secondary affiliation with the Institute of Mechanical Engineering. 1995: B.Sc./M.Sc. in Physics, EPFL 1999: Ph.D. in Artificial Intelligence, University of Edinburgh 2002: SNF Assistant Professor, EPFL 2009: Associate Professor, EPFL 2016: Full Professor, EPFL His research explores the intersection between robotics, computational neuroscience, nonlinear dynamical systems, and machine learning. He develops robotic models to study animal locomotion principles and creates bio-inspired adaptive controllers. His work extends to assistive technologies like exoskeletons and smart furniture for mobility assistance. Notable publications include Science 2007 and 2014, and Nature 2019 with Nyakatura et al. He has received numerous awards, including: 2020: IEEE Fellow 2006: SNSF Professorship 1997: Marie Curie Scholarship 2024: IEEE ICRA Most Influential Paper Award 2019: CLAWAR Best Paper Prize 2018: SAB Best Conference Paper Award 2014: IEEE RO-MAN Best Paper Award 2007: IEEE Humanoids Best Paper Award 2002: ICRA Overall Best Paper Award Professor Ijspeert teaches courses in autonomous robotics, computational motor control, and legged robots at EPFL. He supervises numerous PhD students and contributes to editorial boards of leading journals in robotics and neuroscience. His laboratory investigates locomotion principles through robotic models and simulations, bridging biological understanding with technological innovation.
Swiss Federal Institute of Technology in LausanneSwitzerland
Eduardo Sanchez is an Honorary Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Computer and Communication Sciences (IC) and the IC-DEC department. He holds the email address eduardo.sanchez@epfl.ch . His research spans bio-inspired computing, materials science, and robotics, with a focus on evolvable hardware systems and advanced manufacturing processes. Key contributions include work on electrical resistance sintering, neural network modeling, and robotic cooperation frameworks. His interdisciplinary research integrates material science with computational approaches, emphasizing applications in powder metallurgy, neural network design, and autonomous systems. Notable projects include the PERPLEXUS framework for complex system simulation and studies on bio-inspired hardware platforms. Recent work explores decision-making models for recommendation systems and material characterization techniques for amorphous alloys. Publications highlight advancements in evolvable hardware, including dynamically reconfigurable FPGA platforms and methodologies for modeling large-scale neural networks. His contributions to robotics include heterogeneous robot cooperation strategies and embedded system optimization. Current activities maintain a focus on bridging biological inspiration with engineering solutions in both materials and computational domains.
Swiss Federal Institute of Technology in LausanneSwitzerland
Vijay Kumar is the Nemirovsky Family Dean of Penn Engineering with professorial appointments in Mechanical Engineering and Applied Mechanics, Computer and Information Science, and Electrical and Systems Engineering at the University of Pennsylvania. He leads research on autonomous ground/aerial robots and bio-inspired swarm algorithms at the GRASP Laboratory, where he previously served as director (1998–2004). His work spans robotics, cyberphysical systems, and AI applications in disaster response and construction. Education: B.Tech from Indian Institute of Technology Kanpur, Ph.D. from Ohio State University (1987) Research focuses on robot swarms , autonomous navigation , and bio-inspired collective behaviors . Recent publications explore connectivity optimization, semantic SLAM, and stochastic traffic modeling using robot swarms and neural networks. Applications include GPS-denied environments and decentralized edge AI infrastructure. Scientific Awards: IEEE/ASME Fellow, NAE/APS/AAAS member Entrepreneurship: Co-founded Exyn Technologies, advisor to Treeswift, board member of WeRobotics and O2Micro Labs/teams include the GRASP Laboratory and collaborations with industry partners like Rivian and Amazon. Grant activities involve AI for medicine, intelligent assistive robotics, and digital twin infrastructure.
Swiss Federal Institute of Technology in LausanneSwitzerland
Charlotte Frenkel is a Tenure-Track Assistant Professor in the Microelectronics Department at Delft University of Technology (TU Delft), where she leads research in neuromorphic engineering and low-power AI hardware. Her work bridges the gap between biological intelligence and artificial neural networks, focusing on energy-efficient computing at the edge. Dr. Frenkel's research spans digital and mixed-signal IC design, computer architecture, learning algorithms, and neuroscience. She directs the Cognitive Sensor Nodes and Systems (CogSys) lab, which develops neuromorphic processors like ODIN, MorphIC, SPOON, and ReckOn that demonstrate competitive advantages over conventional neural network accelerators. Her publications reveal a strong focus on spiking neural networks, event-based processing, and on-chip learning. Key trends include developing hardware that leverages sparsity for energy efficiency, creating bio-inspired learning algorithms that solve weight transport and update locking problems, and establishing frameworks for benchmarking neuromorphic systems through initiatives like NeuroBench. Scientific Awards: IBM Innovation Award 2021 Nokia Bell Labs Scientific Award 2021 IEEE ISCAS 2020 Best Paper Award NEUROTECH/NICE Best Early Researcher Presentation 2021 AiNed Fellowship Grant Dr. Frenkel is actively expanding her research group through PhD and postdoc positions. She serves as Associate Editor for IEEE Transactions on Biomedical Circuits and Systems and Frontiers in Neuroscience, and has held numerous leadership roles in conference organization including Program Chair for tinyML Research Symposium 2024 and Neuro-Inspired Computational Elements conference 2023-2024. Her service includes extensive reviewing activities for top IEEE journals and conferences in her field.
Sarah Rochat is a Professor at the Bern University of Applied Sciences (BFH), affiliated with the Institute for Human-Centered Engineering. Her work focuses on human-robot interaction, intuitive robot programming, and agile production systems. She leads the Robot Programming by Demonstration project, which aims to simplify robot reprogramming through gesture-based interfaces using tools like the Logitech VR Ink Stylus. This innovation targets industries needing flexible automation solutions, particularly in manufacturing sectors with diverse products and small production volumes. Education: Sarah holds a Psychology half-degree, a Mathematics Master's, a Robotics PhD, and a postdoc in brain-machine interfaces. She has been at BFH since 2014, combining teaching and research in robotics and human-centered engineering. Research interests include human-robot collaboration, no-code programming for production workers, and ethical implications of AI/robotics in society. Her projects emphasize practical applications such as cobot integration, worker empowerment through accessible tools, and reducing production costs via agile systems. Current collaborations involve 7 industry partners (robot developers, medical firms, sensor manufacturers, and watchmakers) to refine demonstration-based learning for industrial use. Supported by Microtech Booster and Innosuisse grants, her team explores feasibility through simplified case studies. Labs/Teams: Active in BFH’s Human-Centered Engineering group, focusing on interdisciplinary projects blending robotics, ethics, and industrial needs. Future work aims to expand no-code programming tools and validate technologies in real-world manufacturing environments.
Dr. Thomas Jakob Konrad Buchner is a Postdoctoral Researcher at ETH Zurich within the Department of Mechanical and Process Engineering, working under Professor Robert K. Katzschmann in the Institute of Robotics and Intelligent Systems. His research focuses on creating robots that interact with the world in a natural way through the design and fabrication of soft-rigid hybrid robotic structures. Based at CLA F 3, Tannenstrasse 3, 8092 Zürich, Switzerland, Dr. Buchner combines expertise in experimental physics and engineering to advance the field of soft robotics. Dr. Buchner completed his PhD in Mechanical and Process Engineering at ETH Zurich (2020-2025), following an M.Sc. in Physics from the Technical University Munich (2016-2020) and a B.Sc. in Physics from Heidelberg University (2010-2014). His academic journey included a Master's Thesis period at Massachusetts General Hospital, Harvard Medical School, and MIT (2018-2019), as well as an Exchange Semester at Tsinghua University in China (2017-2018). His research program centers on developing robotic systems that leverage materials with properties similar to biological models, allowing robots to utilize functionality inherent in natural designs. With particular expertise in additive manufacturing, system integration, medical imaging, and high voltage electrostatic actuation systems, his work enables robots to move efficiently, rapidly, and silently. His research bridges fundamental materials science with practical robotic applications, focusing on how to create more natural human-robot interactions through biomimetic design principles. Dr. Buchner's publication record demonstrates significant contributions to advancing soft robotics through innovative manufacturing techniques and actuation methods. His work spans from fundamental materials research to complex robotic system integration, with particular emphasis on electrohydraulic actuation, vision-based control of deformable robots, and the development of biomimetic musculoskeletal systems. Publications in high-impact venues like Nature, Science Advances, and Nature Communications reflect the importance of his research in pushing the boundaries of what's possible in soft robotics. As a researcher with strong interdisciplinary training spanning physics, engineering, and medical applications, Dr. Buchner represents the new generation of robotics scientists working at the intersection of multiple fields to create more capable and natural robotic systems. His work on energy-efficient electrohydraulic robotics and vision-controlled manufacturing techniques positions him at the forefront of next-generation robotic development.
Prof. André R. Studart is a Full Professor and Deputy Head of the Department of Materials at ETH Zurich, leading the Complex Materials group. Born in Brazil, he holds a Bachelor's and PhD from the Federal University of São Carlos. His research focuses on bio-inspired materials, advanced ceramics, 3D printing, and sustainable manufacturing. Notable contributions include engineered living materials for carbon sequestration and microbial-based ceramic fabrication. He has received awards from Alcoa Co., Thermo Haake Co., and the Brazilian Ceramic Society. His work spans applications in energy, healthcare, and environmental technologies. Education: Bachelor's in Materials Science and Engineering, Federal University of São Carlos, Brazil PhD in Materials Science, Federal University of São Carlos, Brazil Research Interests: Development of smart materials for medical implants and energy systems Integration of microorganisms into materials for self-regulating functionalities Low-temperature ceramic processing via biocementation 3D printing of functional and reprocessable materials Scientific Awards: Alcoa Co. Award Thermo Haake Co. Award Brookfield Co. Award Magnesita Award Brazilian Ceramic Society Award Advising & Grants: Leads the Complex Materials group at ETH Zurich, with over 50 publications and three patents. His research is supported by grants from SNF and industry partnerships. Labs/Teams: Directs the Complex Materials group, focusing on bio-hybrid materials and advanced manufacturing techniques.
Swiss Federal Institute of Technology in LausanneSwitzerland
Erikas Simanaitis is a Doctoral Assistant at the Laboratory of Intelligent Systems (LIS) within the School of Engineering at the Swiss Federal Institute of Technology Lausanne (EPFL), actively pursuing his Doctoral program in robotics, control, and intelligent systems. His research centers on Robotics, Control Systems, and Intelligent Systems, with emphasis on autonomous robotic platforms and adaptive control algorithms. The Laboratory of Intelligent Systems specializes in evolutionary robotics, bio-inspired control systems, and machine learning applications for physical robots, operating at the intersection of mechanical engineering and artificial intelligence. Based at the MED 1 1612 facility on EPFL's Lausanne campus, Mr. Simanaitis contributes to LIS's experimental research in soft robotics and swarm intelligence. His work supports the laboratory's mission to develop next-generation robotic systems capable of complex decision-making in unstructured environments.
