Pietro de Anna is an Associate Professor at the Institute of Earth Sciences (ISTE), University of Lausanne, since August 2021. He holds an Italian nationality and completed a Master's in Theoretical Physics (2009) at the University of Florence, followed by a PhD in Earth Sciences at the University of Rennes 1 (2012). His research focuses on reactive transport in porous media, filtration, and interactions between bacteriological activity and flow dynamics. He directs the Environmental Fluid Mechanics Laboratory since 2015, employing microfluidics, numerical simulations, and theoretical models to study coupled physical, biological, and chemical mechanisms in confined systems. He has published 21 peer-reviewed articles, teaches environmental science courses at the Bachelor's and Master's levels, and supervised two PhD theses and four postdoctoral researchers. His work includes investigations into microbial biomass accumulation in porous media, diffusion-limited mixing, and biocementation processes. Key research themes are spatial heterogeneity effects, chemotaxis, and quorum sensing in microbial systems. He has pioneered methods combining microfluidics with microscopy to analyze transport at pore scales.
Prof. Ioannis Anastasopoulos is a Full Professor and Head of the Department of Civil, Environmental and Geomatic Engineering at ETH Zurich. He leads the Chair of Geotechnical Engineering, focusing on advanced geotechnical modeling, seismic resilience, and infrastructure systems. His research integrates experimental and numerical methods to address challenges in tunnel engineering, offshore foundations, and seismic protection. Key research areas include seismic response of geotechnical structures, soil-structure interaction, metamaterial-based vibration mitigation, and innovative foundation technologies. He directs the Geotechnical Centrifuge Center and Soil Testing Laboratories at ETH Zurich, advancing physical modeling and material characterization. Recent work emphasizes earthquake engineering applications, including fault rupture interactions with tunnels, pile group dynamics under combined loading, and hybrid modeling of scour effects on bridge foundations. His contributions span geotechnical design methodologies, nuclear facility safety, and additive manufacturing for masonry structures. Prof. Anastasopoulos collaborates internationally on projects like the GEOLAB initiative, advancing Europe's geotechnical physical modeling infrastructure. His teaching includes courses on geotechnical design and theoretical soil mechanics, bridging academic research with practical engineering solutions.
Juerg Leuthold is a Full Professor and Head of the Department of Information Technology and Electrical Engineering (D-ITET) at ETH Zürich, Switzerland. He also leads the Institute of Electromagnetic Fields (IEF) at the same institution. His academic career spans leadership roles at ETH Zürich, Karlsruhe Institute of Technology (KIT), and Bell Labs, with expertise in photonics, plasmonics, and THz technology for communication and sensing applications. Research Interests Photonics for high-speed communication Plasmonics and nonlinear optical signal processing Terahertz technology Applications in sensing and network systems Scientific Awards Optica Fellow IEEE Fellow ERC Advanced Grant (2015) Landesforschungspreis (Baden-Württemberg, 2009) Leadership & Committees Head of D-ITET (2023–present) General Chair of ECOC 2022 Board of Directors, OSA/Optica
Francesca Da Lio is a Professor at the Department of Mathematics, ETH Zurich, where she has held a titular professorship since 2014. Her research focuses on nonlinear elliptic and parabolic partial differential equations (PDEs), with applications in stochastic and deterministic optimal control, homogenization, front propagation, and geometric analysis. She has pioneered work on conformally invariant variational problems and nonlocal PDEs, including fractional harmonic maps and stability analysis for critical points. PhD in Mathematics (1998) and Summa Cum Laude Degree in Mathematics (1994) from University of Padova. Her research explores the interplay between nonlinearity and non-locality, particularly in problems arising from geometry, mathematical finance, and physics. She has led major Swiss National Fund (SNF) projects, including grants for geometric analysis and conformally invariant variational theory. Her work on 3-commutators, integrability by compensation, and Morse index stability has advanced the understanding of harmonic maps and elliptic systems. Francesca Da Lio has mentored numerous PhD, postdoctoral, and Master/Bachelor students, including Dominik Schlagenhauf, Jerome Wettstein, and Ali Hyder. She has served on hiring committees for full professorships at ETH Zurich and co-organized international conferences such as 'Recent Advances in Nonlocal and Nonlinear Analysis' and 'Topics in Sub-Elliptic PDEs.' Scientific Awards: Italian Scientific Qualification as Full Professor in Mathematical Analysis (2013). She contributes to editorial boards, including Advances in Calculus of Variations , and participates in academic services like refereeing for SNF projects and international journals.
Dr. Christian Jaeger is a Researcher at the Zurich University of Applied Sciences (ZHAW) School of Engineering, focusing on Machine Learning in Optimal Control for Industry. His work bridges engineering and computer science with applications in industrial automation and building systems. His research interests span Machine Learning , Optimal Control , Reinforcement Learning , Energy Management Systems , and Industrial Automation . Jaeger has led multiple research projects including a preliminary study on automated IBN heat pumps and a feasibility study on Reinforcement Learning Control for heating systems. His work demonstrates a clear trajectory from traditional manufacturing technology toward contemporary AI-driven control systems. Jaeger's publication record shows consistent output from 2005 to 2024, with recent focus on energy optimization in building control using reinforcement learning, 3D printing techniques, and model predictive control. His research demonstrates strong interdisciplinary connections between computer science, engineering, and practical industrial applications. His scientific contributions include publications in journals such as Applied Sciences and the Journal of the British Interplanetary Society, along with numerous conference proceedings from international events including EuroSun and the International Symposium on Nonlinear Theory and its Applications. At ZHAW, Jaeger has served as project leader for multiple completed research initiatives including adaptive energy management systems for buildings and automated heat pump systems. His work demonstrates strong industry connections with applications in building automation and industrial manufacturing processes.
Dr. Fabian Schmid is a Researcher affiliated with the Institute for Quantum Electronics at ETH Zürich, working within the Professorship for Experimental Quantum Information . His research focuses on quantum control, precision spectroscopy, and optical frequency comb technologies. Key applications include molecular ion manipulation, laser cooling techniques, and advanced spectroscopic methods for atomic and molecular systems. His work bridges quantum physics and optics, with contributions to ultra-stable laser systems, low-repetition-rate frequency combs, and high-resolution spectroscopic measurements. Recent efforts target applications in trapped ion systems and new boson constraints via calcium isotope studies. Schmid's experimental setups often involve precision engineering of optical components and cavity-stabilized laser systems. Notable experimental achievements include demonstrating quantum control over single molecular ions (H₂⁺) and developing number-resolved detection methods for Coulomb crystals. His research also explores synergies between dual-species laser cooling and cavity-based technologies. While currently holding no listed academic awards, Schmid's contributions are evident through his prolific publishing record in top-tier physics journals. His lab work integrates cutting-edge quantum optics with atomic physics to advance fundamental understanding and precision measurement capabilities.
Dr. Chenhao Chu is a Professor at ETH Zürich, holding the Professur für Elektronik (Professorship for Electronics). He specializes in RF/mm-Wave circuits, AI-driven design methods, and advanced power amplification technologies. His research focuses on energy-efficient, wideband systems, antenna-in-package solutions, and GaN-based applications for 6G and beyond. Education: Ph.D. in Electronic Engineering, University College Dublin (2022) M.Sc. in Electronic Information Engineering, City University of Hong Kong (2017) Research Interests: His work bridges AI and hardware design, emphasizing reconfigurable circuits , high-linearity power amplifiers , and mm-Wave phased arrays . Key areas include: AI-assisted rapid design synthesis III-V/Si co-design for mm-Wave Efficient antenna integration Dynamic load modulation techniques Awards: Award-winning researcher with distinctions including the First Place Best Student Paper Award (2022 Royal Irish Academy Colloquium) and multiple HEPA-SDC Competition Awards (2021-2022). Recognized for innovations in PA efficiency and design automation. Advising & Grants: Leading projects on 6G PA architectures and AI-driven RF design. Active in IEEE with contributions to conferences like IMS and ARFTG. No explicitly stated grants mentioned but widely cited in industry-academia collaborations. Labs & Teams: Associated with ETH Zürich's Electronics Laboratory, focusing on next-generation wireless systems. Collaborates internationally on 5G/6G infrastructure and mm-Wave innovations.
George Haller is a Professor at the Department of Mechanical and Process Engineering at ETH Zurich . He leads the Institute of Mechanical Systems and holds the Chair in Nonlinear Dynamics . His research focuses on: Nonlinear dynamical systems theory Data-driven model reduction Spectral submanifolds (SSMs) Coherent structure identification in fluids and solids Control of complex nonlinear systems His recent work emphasizes equation- and data-driven modeling across solids, fluids, and control systems . Key contributions include: SSMTool - a MATLAB package for nonlinear model reduction SSMLearn - open-source software for data-driven modeling Transport barrier detection algorithms with oceanographic applications Scientific accolades include: 2025 Lyapunov Award (ASME) 2023 Stanley Corrsin Award (APS) Fellowships: ASME, APS, SIAM External Member, Hungarian Academy of Sciences His group has trained notable alumni: Thomas Breunung (Assistant Professor, University of Wisconsin-Madison) Shobhit Jain (Assistant Professor, Delft University of Technology) Mattia Serra (Assistant Professor, UCSD) Publications span Nonlinear Dynamics, Nature Communications , and Physical Review Fluids , with a 2025 book Modeling Nonlinear Dynamics for Equations and Data (SIAM Press). Current projects include: Reduced-order modeling of fluid-structure interactions Control of soft robots via nonlinear dynamics Identifying material barriers in turbulence
Dr. Yi Guo is an External Scientific Staff member at the Power Systems and High Voltage Lab, part of ETH Zurich's Department of Information Technology and Electrical Engineering. His research focuses on advancing smart grid technologies, particularly in power system coordination, stochastic control, and distributed energy resource integration. His work emphasizes real-time operational frameworks for integrated transmission-distribution systems, flexibility modeling, and robust optimization under uncertainty. Collaborations include projects funded by NCCR Automation (SNF). Key research areas include: - Real-time grid control and NMPC applications - Stochastic modeling of distributed energy resources (DERs) - Sparsity-promoting control design for power grids - Joint optimization-estimation architectures for distribution networks - Two-stage electricity market frameworks for DER participation Recent publications (2020-2024) highlight contributions to grid resilience, DER aggregation, and sensor placement optimization. His work addresses challenges in energy transition through advanced control systems and market mechanisms. Lab affiliations include the Power Systems and High Voltage Lab, collaborating on projects like NCCR Automation Phase I. His research bridges theoretical control advancements with practical grid implementation.
Prof. Dr. Romain Quidant is a Full Professor in the Department of Mechanical and Process Engineering at ETH Zürich, where he also serves as Head of the Institute for Energy and Process Engineering. His research focuses on nanophotonics, optomechanics, and plasmonics with applications in quantum optics, biomedical engineering, and thermal control systems. He leads a multidisciplinary team exploring light-matter interactions at the nanoscale, particularly in levitated nanoparticles and plasmonic therapies. Key research interests include quantum optomechanical systems, plasmonic nanothermometry, and targeted photothermal therapies. His work bridges fundamental physics with practical applications such as precision measurement, medical imaging, and energy-efficient materials. Recent studies highlight advancements in optical trapping techniques, thermal wavefront shaping, and robotic surgery guidance using fluorescent nanothermometry. Prof. Quidant’s publications showcase innovations in reconfigurable meta-surfaces, optofluidic platforms for high-throughput analysis, and adaptive thermal microscopy for brain imaging. His lab develops integrated systems for medical diagnostics, environmental sensing, and quantum-enabled technologies. These efforts have been applied to cancer treatment optimization and novel materials for energy systems.
Xuming He is an Associate Professor at the School of Information Science and Technology (SIST), ShanghaiTech University, where he leads the PLUS Lab. His research spans computer vision and machine learning with a focus on developing algorithms that operate effectively under limited supervision and evolving data conditions. His core research interests include weakly-supervised and few-shot learning for scenarios with sparse annotations, continual learning frameworks for knowledge retention during sequential task acquisition, semantic segmentation techniques for scene understanding, and multimodal vision-language representations. He emphasizes interpretable machine learning to build transparent AI systems capable of human-understandable reasoning, addressing critical challenges in model trustworthiness and deployment reliability. Recent publications reveal strong trends toward novel class discovery in long-tailed recognition scenarios, physics-informed generative modeling for scientific applications, and robust segmentation under distribution shifts. His work increasingly integrates large language models for multimodal reasoning while maintaining focus on efficiency in resource-constrained environments like robotic grasping and medical imaging analysis. He actively mentors students, having supervised Qian He to PhD completion and Chuanyang Hu to Master's degree in 2023. He welcomes prospective graduate students through ShanghaiTech's Computer Science & Technology program and offers undergraduate research projects requiring minimum six-month commitments. The PLUS Lab under his direction drives innovation in learning under supervision constraints, with recent work spanning medical tumor analysis, cross-view geolocation, photonic computing, and semiconductor design verification. The lab's research bridges theoretical advances with practical applications across healthcare, robotics, and scientific discovery domains.
Andrea Del Prete is an Associate Professor in the Industrial Engineering Department at the University of Trento (Italy) since 2022. His research focuses on robot control, reinforcement learning, trajectory optimization, and numerical algorithms for dynamic systems. He leads the Interdepartmental Robotics Lab (IDRA) and has previously held roles as a tenure-track assistant professor at the University of Trento (2019-2021), a research scientist at the Max-Planck Institute for Intelligent Systems (2018), and an associated researcher at LAAS-CNRS (2014-2017) working with the HRP-2 humanoid robot. Earlier, he conducted PhD and post-doc research at the Italian Institute of Technology (2010-2013) on iCub robot control. PhD in Robotics (2013) - Italian Institute of Technology MEng in Computer Engineering (2009) - University of Bologna BSc in Computer Engineering (2006) - University of Bologna Dr. Del Prete specializes in merging learning and model-based techniques for safe robot control, particularly in legged systems. His work bridges trajectory optimization (TO) with reinforcement learning (RL) to overcome local minima challenges (CACTO/CACTO-SL algorithms) and develops robust controllers for humanoid and quadrupedal robots in unstructured environments. He explores viability kernels in MPC, safety certificates, and bi-level optimization for co-designing hardware/control policies. Key application areas include mountain rescue robotics (ALPINE platform), aerial maneuver recovery, and energy-efficient legged locomotion. His recent publications (2023-2025) emphasize numerical optimization algorithms, multi-contact locomotion, and hybrid control frameworks. Topics span from analytical integral optimization (2025) to climbing robots for mountain operations (2025), demonstrating a trajectory from theoretical algorithm development to real-world robotic applications. Research keywords include robotics, numerical optimization, and machine learning, with sub-fields like MPC for dynamic systems, humanoid control, and terrain adaptation. As an educator, he teaches advanced courses on: Optimization and Learning for Robot Control (48-hour master's course) Optimization-based Control of Legged Robots (12-hour PhD course) Task-Space Inverse Dynamics (3-hour PhD course) Current PhD advisees include Mohammad Hasan Yeganegi (generalization bounds for imitation learning), Pietro Noah Crestaz (numerically-efficient RL), Veronica Campana (ergodic control for defect detection), Elisa Alboni (data-efficient model-based RL), and Gianni Lunardi (MPC for legged locomotion).
Bozidar Stojadinovic is a Full Professor and Chair of Structural Dynamics and Earthquake Engineering at ETH Zürich's Department of Civil, Environmental and Geomatic Engineering. He leads the Institute of Structural Engineering and previously held professorships at UC Berkeley and the University of Michigan. His research focuses on community disaster resilience, seismic design, and experimental methods like hybrid simulation. Education: PhD in Civil Engineering, UC Berkeley (1995) MS in Civil Engineering, Carnegie-Mellon University (1990) BS in Civil Engineering, University of Belgrade (1988) Research Interests: Performance-based probabilistic resilience evaluation of civil infrastructure. Earthquake engineering, including seismic isolation and response modification techniques. Development of experimental testing methods, such as hybrid simulations for dynamic structural analysis. Awards: ICE Journal John Henry Garrood King Medal (2023) ACI Chester Paul Siess Award (2017) NSF CAREER Award (1999) Teaching & Advising: Teaches courses on seismic design and structural dynamics at ETH. Advised 49 doctoral students to date. His work integrates advanced methodologies to enhance structural resilience against natural hazards. Labs/Teams: Leads ETH's Institute of Structural Engineering, advancing research in seismic protection and infrastructure resilience through experimental and computational innovations.
Robert Katzschmann is an Assistant Professor of Robotics (tenure-track) at ETH Zurich's Department of Mechanical and Process Engineering , leading the Soft Robotics Laboratory . He is also the co-founder and scientific advisor of Mimic Robotics , focused on dexterous manipulation solutions. His research spans Soft Robotics , Musculoskeletal Robotics , Biohybrid Systems , and Underwater Robotics , with breakthroughs like the autonomous soft robotic fish SoFi and biohybrid actuators. He holds a PhD from MIT (2018), a Master's from Stanford (2013), and a Diplom-Ingenieur from KIT (2013). Research Interests: His work emphasizes compliant, bioinspired robots capable of safe human interaction and complex environmental navigation. Key areas include soft material fabrication, biohybrid tissue integration, and dynamic control algorithms. Recent innovations include electrohydraulic actuators and vision-controlled printing for robotic components. Grants & Recognition: Secured funding from SNSF, NSF, and industry partners. Recognitions include a TED Fellowship (2022), Outstanding Paper Award (IEEE RoboSoft 2019), and Redtenbacher-Prize (2014). He serves on editorial boards for Advanced Robotics Research and npj Robotics , and chairs conference workshops globally. Labs & Teams: Directs the Soft Robotics Lab with 17 PhD students and 2 postdocs. Collaborates with leading institutions like MIT, Harvard, and the Weizmann Institute on biohybrid systems and robotic actuation.
Christopher Onder is a Lecturer at the Department of Mechanical and Process Engineering at ETH Zürich, where he serves as Deputy Head of the Institute for Dynamic Systems and Control. His research focuses on control engineering, energy systems, and sustainable transportation solutions. Role : Lecturer, Deputy Head of Institute Department : Mechanical and Process Engineering Institute : Dynamic Systems and Control University : ETH Zürich His research interests include: Control systems for hybrid and electric vehicles Energy management optimization Thermal comfort in public transport Co-design of mechanical and racing strategies Nonlinear control in aerospace applications Model-based calibration for diesel engines Contact: onder@idsc.mavt.ethz.ch
