Prof. Eleni Chatzi is a Full Professor and Chair of Structural Mechanics at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. She holds a PhD from Columbia University (2010) and has held roles from Assistant to Full Professor at ETH since 2010. Her research focuses on intelligent structural monitoring and data-driven asset management, emphasizing nonlinear dynamics and sensor integration. Affiliations : Institute of Structural Engineering, European Academy of Wind Energy (EAWE President), Swiss Community for Computational Methods (SWICCOMAS Chair) Research interests include Structural Health Monitoring (SHM), system identification, and advanced simulation tools. She pioneered work on data-driven diagnostics and self-aware infrastructure, supported by grants like the ERC Starting Grant (2015). Awards include the 2020 Walter L. Huber Prize and 2024 SHM Person of the Year Award. Her work spans wind energy infrastructure, metamaterials for vibration control, and AI-driven structural analytics. Over 600 publications and 200k+ citations highlight her impact. She teaches computational science and structural dynamics in ETH's programs and collaborates globally on sustainable infrastructure projects.
Prof. Dr. Melanie Zeilinger is an Associate Professor at the Department of Mechanical and Process Engineering at ETH Zurich, leading the Intelligent Control Systems group at the Institute for Dynamic Systems and Control. She holds a diploma in Engineering Cybernetics from the University of Stuttgart (2006) and a Ph.D. in Electrical Engineering from ETH Zurich (2011). Her postdoctoral research included stints at EPFL (2011–2012), a Marie Curie fellowship at UC Berkeley and the Max Planck Institute (2012–2015), and a professorship at the University of Freiburg (2018–2019). Her research focuses on learning-based control, distributed control systems, and robotics , with applications to medical devices (e.g., hydrocephalus shunts) and human-in-the-loop systems. She organizes the Conference on Learning for Dynamics and Control (L4DC) and contributes to initiatives like the "Algorithm on My Team" project. Her awards include the ETH Medal for her PhD thesis, a Marie-Curie IO Fellowship , and an SNF Assistant Professorship grant . She serves as an Associate Editor for IEEE Control Systems Letters and actively reviews for top journals/conferences like IEEE TAC, Automatica, and NeurIPS. Key projects include: VIEshunt: A smart ventricular shunt for hydrocephalus treatment, combining control systems and medical engineering. Autonomous Racing: Contextual tuning and safety-certified learning-based MPC for real-time obstacle avoidance. Data-Driven Control: Integrating Gaussian processes and state-space models into MPC frameworks for uncertain systems. Her work bridges control theory, machine learning, and robotics, addressing societal challenges such as healthcare and energy efficiency.
Josie Hughes is a Tenure Track Assistant Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) within the School of Engineering's Institute of Mechanical Engineering. She leads the Computer Robot Design and Fabrication Laboratory (CREATE Lab) and serves on the doctoral program committee for Robotics, Control and Intelligent Systems. Her roles include teaching courses in product development, engineering design, and data-driven manufacturing methods while maintaining active research and student supervision. Her research centers on soft robotics with emphasis on adaptive design, fabrication techniques, and real-world applications. Key areas include agricultural robotics (exemplified by the GraspBerry raspberry harvester), biomimetic materials like self-healing e-skins, and developmental robotics (BabyBot project). She pioneers approaches integrating morphological computation, variable stiffness mechanisms, and machine learning for robotic control, while championing open-source principles and diversity in robotics through accessible educational initiatives like balloon robot kits. Analysis of her recent publications reveals dominant trends in soft robotics adaptability, particularly in variable-stiffness structures, sensor integration, and task-specific optimization. Her work bridges fundamental material science with practical applications in agriculture, food science, and human-robot interaction, frequently employing computational methods like Bayesian optimization and neural networks for design and control. Scientific awards: No specific awards were mentioned in the source materials. Dr. Hughes actively supervises 16 doctoral students across diverse projects including soft grippers for agriculture, biomimetic locomotion, and robotic manipulation systems. Her advising portfolio shows strong alignment with her research themes, with current students working on topics like modular soft arms, agricultural automation, and developmental robotics. While grant details weren't specified, her high publication volume indicates robust research funding. The CREATE Lab under her leadership focuses on holistic co-design of hardware and software for soft robotic systems, with notable projects including the GraspBerry agricultural harvester and BabyBot developmental platform. The lab emphasizes open-source development and educational outreach, maintaining strong industry and academic collaborations while pushing boundaries in reconfigurable robotics and human-centered applications.
Olga Fink is a Tenure Track Assistant Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Department of Intelligent Maintenance and Operations Systems (IMOS) within the School of Architecture, Civil and Environmental Engineering (ENAC). She also holds roles in PhD program committees for Civil and Environmental Engineering (EDCE) and Robotics, Control, and Intelligent Systems (EDRS). Her research focuses on machine learning for infrastructure monitoring, predictive maintenance, and physics-informed AI models. She teaches courses on machine learning, data science for infrastructure, and advanced deep learning topics. Fink advises multiple PhD students and is involved in interdisciplinary projects such as ThermoNeRF (multimodal 3D thermal modeling) and physics-informed neural networks for fault diagnostics. Her work bridges AI and engineering with applications in smart infrastructure, energy systems, and industrial IoT. Education: PhD in Engineering (inferred from role) Affiliations: IMOS Lab, ENAC-SGC, EPFL PhD Committees (EDCE, EDRS) Key Research Themes: Explainable AI, Digital Twins, Structural Health Monitoring, Domain Adaptation Her publications (2023–2025) emphasize robust AI for industrial systems, including fault detection in high-voltage equipment, multimodal data fusion, and physics-consistent models. She collaborates on EU and industry-funded projects, focusing on real-world applications like predictive maintenance and energy efficiency.
Prof. Dr. Stefanie Hellweg serves as a Full Professor for Ecological Systems Design at the ETH Zürich , Department of Civil, Environmental and Geomatic Engineering. She is Deputy Head of the Institute of Environmental Engineering and leads groundbreaking research at the intersection of industrial ecology, life cycle assessment, and circular economy systems. PhD in Environmental Engineering (ETH Zürich, 2000) Industrial Engineering Degree (Karlsruhe University, 1996) Her research develops advanced methodologies for environmental impact assessment of products and technologies, focusing on: Life Cycle Assessment (LCA) with correlated uncertainty modeling Circular economy implementation in chemical and energy sectors Industrial symbiosis optimization for heat and nutrient flows Urban wastewater systems redesign for resource recovery Chemical pollution analysis in plastic materials Key publication trends reveal expertise in: Hybrid wastewater treatment systems Energy-efficient greenhouse cultivation Exergy analysis for sustainability metrics Machine learning applications in environmental modeling Policy-relevant industrial ecology studies She actively participates in global sustainability initiatives as: President of the International Society of Industrial Ecology (ISIE) Member of UN Environment's International Resource Panel Editorial board member for leading environmental journals
Devis Tuia serves as Associate Professor at the Swiss Federal Institute of Technology Lausanne (EPFL), holding appointments in the Institute of Environmental Engineering (IIE) within the School of Architecture, Civil and Environmental Engineering (ENAC). He leads the Environmental Computational Science and Earth Observation Laboratory (ECEO) since 2020 and contributes to EPFL's Doctoral Program in Civil and Environmental Engineering. His academic journey began in Lausanne with studies at UNIL and EPFL, culminating in a PhD in remote sensing from UNIL. Postdoctoral research followed at institutions in Valencia, Boulder, and EPFL, focusing on machine learning model adaptation. He progressed from Research Assistant Professor at University of Zurich to Associate and Full Professor at Wageningen University before joining EPFL. Tuia's research bridges Earth observation with artificial intelligence, specializing in interpretable deep learning for environmental applications. His lab develops algorithms for making remote sensing accessible, with particular emphasis on digital wildlife conservation through automated censuses using drone and satellite imagery. Current projects tackle the 'black box' problem in environmental modeling while advancing spatial intelligence for sustainable urban development. His 2023-2025 publication portfolio reveals three dominant trends: (1) species distribution modeling using incomplete observations, (2) multimodal fusion of satellite/drone data with textual descriptions, and (3) interpretable AI frameworks for environmental decision-making. This work consistently addresses real-world challenges like wildfire forecasting and biodiversity monitoring. As an educator, Tuia supervises 12 current PhD students and has graduated 4 former EPFL doctoral candidates. His teaching portfolio includes Frontiers of Deep Learning for Engineers , Sensing and Spatial Modeling for Earth Observation , and Image Processing for Earth Observation courses. The ECEO laboratory maintains active collaborations with ESA-NASA initiatives and conservation organizations globally.
Dr. Andrea Martinelli is a Lecturer and Postdoctoral Researcher at the Automatic Control Laboratory (IfA), ETH Zurich. He holds a PhD in Automatic Control from ETH Zurich (2024) under Prof. John Lygeros, an MSc in Control Engineering (2017) from Politecnico di Milano, and a BSc in Management Engineering (2015). His research focuses on optimal control, reinforcement learning, and decentralized control strategies for large-scale systems, emphasizing scalability and applicability to renewable energy systems. He received the ETH Medal for his doctoral thesis on data-driven control methods. Education: BSc in Management Engineering, Politecnico di Milano (2015) MSc in Control Engineering with Honours, Politechnico di Milano (2017) PhD in Automatic Control, ETH Zurich (2024) Research Interests: Optimal control and reinforcement learning Data-driven methods for control systems Decentralized control of interconnected systems Dissipativity theory and passivity-based approaches Applications in renewable energy systems (DC microgrids) Teaching & Outreach: Program Manager for the CAS ETH in Automation Teaching a post-graduate course on automation in 2025 Professional Activities: Worked at Laboratoire d'Automatique (EPFL) during MSc thesis (2017) Research Assistant with Prof. R. Scattolini, Politecnico di Milano (2018)
Mennatallah El-Assady serves as Assistant Professor at ETH Zurich's Department of Computer Science, where she leads the Interactive Visualization and Intelligence Augmentation Lab (IVIA). Her academic trajectory includes research fellowships at ETH's AI Center and doctoral work at University of Konstanz and OntarioTech University, establishing her expertise at the intersection of visualization and artificial intelligence. Her research focuses on advancing responsible data-driven decision-making through human-centered analytics, with particular emphasis on explainable machine learning systems. Dr. El-Assady combines data mining techniques with visual interfaces to create transparent AI workflows, specializing in text data analysis. Her work bridges computational linguistics, digital humanities, and information visualization to develop tools that make complex AI processes interpretable for end users. Recent publications demonstrate growing focus on generative AI's impact on visualization practices and sophisticated frameworks for interactive machine learning. Her research consistently addresses the challenge of maintaining human agency in increasingly automated systems, with applications spanning political debate analysis, musicology, and healthcare data interpretation. The trend shows increasing sophistication in evaluation methodologies for visual analytics systems. Best Paper Award: Honorable Mention for 'Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework' Dr. El-Assady actively shapes her field through workshop leadership including ArgVis (Argument Visualization), Vis4DH (Visualization for Digital Humanities), and VISxAI (Visualization for AI Explainability). Her teaching includes 'Interactive Machine Learning- Visualization and Explainability' at ETH Zurich, training next-generation researchers in human-centered AI development. She maintains strong industry connections with coverage in Forbes and ETH News regarding human-AI collaboration frameworks. The Interactive Visualization and Intelligence Augmentation Lab (IVIA) develops cutting-edge tools including explAIner for transparent machine learning, LingVis for linguistic analysis, VisArgue for debate structure visualization, and VALIDA for political deliberation analysis. These projects share a common thread of enhancing human understanding through carefully designed visual interfaces that expose AI decision processes.
Emilio Frazzoli is a Full Professor at ETH Zurich’s Department of Mechanical and Process Engineering. He leads the Institute for Dynamic Systems and Control and the Center for Sustainable Future Mobility, focusing on autonomous systems, robotics, and socio-technical control frameworks. Current affiliations: ETH Zurich (Dynamic Systems and Control, Sustainable Future Mobility) Research: Autonomous mobility-on-demand, game theory for resource allocation, and safety verification in multi-agent systems His work bridges robotics, control theory, and economics, with projects like the open-source AMoDeus simulation framework for autonomous taxis and karma-based resource allocation systems. Recent publications emphasize trustworthy AI, reproducibility in autonomous vehicle control, and human-robot interaction challenges. Notable projects include nuReality (VR-based pedestrian interaction studies) and CARSI II (context-driven vehicle interfaces).
Gustavo Valverde Mora is a Lecturer at ETH Zurich's Power Systems Laboratory in the Department of Information Technology and Electrical Engineering. His research focuses on distributed energy resources, smart grid technologies, and power system control, with expertise in behind-the-meter DER integration and hosting capacity analysis. His recent work addresses key challenges in renewable energy integration, including voltage control coordination between transmission and distribution networks, data-driven local control schemes for active distribution grids, and unsupervised load disaggregation techniques using smart meter data. He has developed novel methods for DER modeling, GIS-based system analysis, and distribution network planning. Recognized with multiple awards including the 2022 Costa Rican National Technology Award, he actively contributes to IEEE Task Forces on DER integration. His research demonstrates strong emphasis on practical grid applications, combining theoretical power systems knowledge with advanced data analytics. Dr. Valverde teaches Power System Analysis (227-0526-00L) and maintains collaborations with utilities worldwide on renewable integration challenges.
Prof. Stefan Wiemer is the Director of the Swiss Seismological Service (SED) and holds the Chair of Seismology at ETH Zurich's Department of Earth and Planetary Science. He obtained a geophysics diploma from Ruhr University Bochum (1992) and a PhD from the University of Alaska Fairbanks (1997). His research focuses on earthquake processes, probabilistic hazard assessments, induced seismicity, and geothermal energy applications. He has published over 200 articles and supervised 30 PhD students, while also lecturing at the University of Bern. Key Roles: Member of ERC Grants Evaluation Panel (2015–present) Scientific Advisor to GFZ German Research Center for Geosciences (2021–present) President of Swiss Geophysical Commission Projects: Leader of Switzerland's national earthquake risk model Coordinator of EU-funded RISE (risk assessments) and DEEP (geothermal de-risking) projects Principal Investigator for ERC Synergy grant FEAR (BedrettoLab fault experiments) His research spans operational earthquake forecasting, CO2 storage monitoring, and the BedrettoLab underground experiments. He has won the Humboldt Foundation Fellowship (1997) and contributed to international initiatives like the Dutch Mining Effects Panel. Teaching includes ETH's Geophysics I course. Scientific contributions include developing seismic hazard models (ERM-CH23), real-time induced seismicity forecasting frameworks, and innovative techniques for fault dynamics analysis. His work integrates field data, laboratory experiments, and computational modeling to address both natural and human-induced seismic risks.
Prof. Dr. Matthias A. Tietz is an Assistant Professor and leads the Competence Center for Entrepreneurship at the St.Gallen Institute of Management in Asia (SGI-HSG), part of the University of St.Gallen in Singapore. He holds affiliate positions at IE Business School (Madrid), INDEG ISCTE (Lisbon), and the Mediterranean School of Business (Tunis). His academic journey includes degrees from Ivey Business School (Ph.D. in Entrepreneurship), Universidad del Pacífico (Peru), and Nanyang Business School (MBA, Singapore). Research focuses on entrepreneurial decision making, corporate innovation in SMEs and MNCs, and business model copycats. He regularly presents at global conferences like the Babson College Entrepreneurship Research Conference and Academy of Management Annual Meetings. Prior to academia, he consulted for companies like DHL, Henkel, and Sulzer Engineering, focusing on HR and turnaround management. He teaches courses on business consulting, social entrepreneurship in Southeast Asia, and executive education programs globally. Awarded multiple Best Paper Awards (2012, 2014, 2020) and Best Lecturer Awards across IE University programs (2019-2020). Engaged in startups as an advisor and investor, emphasizing cultural diversity in entrepreneurial contexts. Active in pro bono projects, such as supporting rural entrepreneurs in Peru.
Dr. Cesar Dario Cadena Lerma is a Lecturer at the Department of Mechanical and Process Engineering and a tenured Senior Scientist at the Institute of Robotics and Intelligent Systems (IRIS) at ETH Zurich. He leads the Perception, Mapping and Navigation team within the Robotics Systems Lab (RSL), co-founded and directs the ETH RobotX initiative focusing on educational robotics, and previously held roles at ETH Zurich's Autonomous Systems Lab, University of Adelaide, and George Mason University. His research focuses on robotics perception, particularly in SLAM (Simultaneous Localization and Mapping), semantic scene understanding, and robust perception systems for dynamic environments. Education: PhD in Computer Science and System Engineering from the University of Zaragoza, followed by postdoctoral research at George Mason University and The University of Adelaide. Professional roles include managing director of ETH RobotX and leadership in multi-modal mapping frameworks like maplab 2.0. Research interests emphasize integrating perception and learning in robotics, with a focus on semantic mapping, data association, place recognition, and navigation in unstructured environments. His work bridges traditional SLAM techniques with modern deep learning approaches to create robust, modular systems. Key contributions include the PHASER registration algorithm, SCIM obstacle avoidance framework, and C-Blox dense mapping system. Awards include the Best Paper Award at the 2017 IEEE International Symposium on Safety, Security, and Rescue Robotics. His articles span topics like semantic pointcloud filtering, volumetric mapping, and embodied domain adaptation. He collaborates widely, with over 50 peer-reviewed publications in top venues such as IEEE Robotics and Automation Letters and International Journal of Robotics Research.
Dr. Elisa Donati is a researcher and independent group leader at the Institute of Neuroinformatics , affiliated with both the University of Zurich and the Swiss Federal Institute of Technology Zurich . Her work bridges neuromorphic engineering, biomedical signal processing, and wearable healthcare technologies, with a focus on creating brain-inspired systems for neuroprosthetics and rehabilitation. Affiliation: Institute of Neuroinformatics, University of Zurich & ETH Zurich Email: elisa@ini.uzh.ch Elisa’s research emphasizes developing neuromorphic signal processing strategies for wearable and embedded systems, enabling real-time closed-loop interactions with the nervous system. She specializes in translating neuroscience insights into energy-efficient technologies for digital health applications, including neuroprosthetics and personalized biomedical devices using neuromorphic hardware. Her recent publications (2024–2025) highlight advancements in gesture recognition via EMG and event-based systems, neuromorphic heart rate monitoring , and spiking neural network architectures . These works span biomedical signal processing, low-power computing, and adaptive algorithms, reflecting her commitment to robust, real-time, and brain-inspired solutions for healthcare. Elisa’s contributions to neuromorphic computing are evident in her exploration of heterogeneous population encoding , event-driven processing , and ultra-low-power microcontrollers . Her projects often integrate wearable systems with neuroscience, aiming to improve prosthetic control and rehabilitation technologies .
Paolo Tonella is a Full Professor and Director of the Software Institute at the Faculty of Informatics, Università della Svizzera italiana (USI) in Lugano, Switzerland. He also holds an Honorary Professorship at University College London (UK) and previously led the Software Engineering group at Fondazione Bruno Kessler (Italy). His research focuses on software testing, analysis, and AI-driven systems. He has authored over 200 peer-reviewed papers and 100 journal articles, with an H-index of 72. He teaches courses in Data and Software Engineering and Informatics, including Information Modeling, Probability & Statistics, and Knowledge Search. Key contributions include foundational work on web application testing (ICSE MIP award), evolutionary testing techniques (eToc/EvoSuite tools), and reverse engineering of object-oriented systems. He led the ERC-funded PRECRIME project on anticipatory testing. His recent work addresses AI dependability, autonomous systems testing, and deep learning fault analysis. Scientific awards include the ICSE MIP Award (2001) and ERC Advanced Grant (2018). He has served on editorial boards for major journals like IEEE Transactions on Software Engineering and ACM TOSEM. Current roles include leadership in the Software Institute and organizing the SIESTA summer school.
