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Marek PyciaView profile

Professor

• Market Design
• Organizational Economics
• Economics
• +3 more

Marek Pycia is a Professor of Organizational Economics at the University of Zurich and Co-Director of the Zurich Center for Market Design. His research focuses on market design, organizational economics, and their applications to public policy, including the development of kidney transplant voucher programs and improvements to US school systems. He holds an ERC Consolidator Grant and has contributed to leading journals like the American Economic Review and Econometrica. Education: Ph.D. in Economics, Massachusetts Institute of Technology (MIT) Research Contributions: His work combines theoretical rigor with practical applications, such as designing efficient mechanisms for resource allocation and addressing market failures. Notable projects include the kidney voucher system, which has significantly expanded transplant opportunities in the US, and foundational studies on auction theory, matching markets, and pseudomarkets. Awards and Affiliations: ERC Consolidator Grant Best Paper Award at ACM Conference on Economics and Computation (EC'19) Research Fellow at CEPR Editorial roles at journals like Theoretical Economics and Journal of Economic Theory Grants and Labs: Marek Pycia leads the Zurich Center for Market Design, a hub for interdisciplinary research on market mechanisms. His work is supported by major grants and collaborations with institutions like Princeton University and the National Kidney Registry.

• Software Engineering
• Cybersecurity
• Internet of Things (IoT)
• +4 more

Jacques Pasquier is a Professor in the Department of Informatics at the University of Fribourg, Switzerland, and Head of the Software Engineering Group. His academic affiliation falls under the Interfaculty Informatics unit, emphasizing interdisciplinary research and education in computer science. His research and teaching focus on software engineering, cybersecurity, IoT systems, and agile methodologies. Research interests include IoT security, blockchain applications in decentralized networks, and privacy-preserving technologies. He has contributed to frameworks for secure IoT middleware, lightweight communication protocols, and trusted execution environments. His work bridges theoretical advancements with practical implementations, such as the ImputeGAP library for time series imputation and the Universal Explorer for Web of Things interoperability. Publications span topics like secure IoT infrastructure, blockchain-enabled LPWAN systems, and agile development metrics. His articles often address challenges in privacy, scalability, and resilience within distributed systems. While no specific awards are mentioned, his prolific publication record highlights sustained contributions to computer science and engineering. Led the Software Engineering Group, focusing on advancing methodologies for modern software systems. Collaborates on projects involving industry and academic partners to address real-world challenges in IoT and cybersecurity.

• Formal Verification
• Programming Languages
• Cybersecurity
• +3 more

Dr. Marco Eilers is a **Lecturer** in the **Department of Computer Science** at **ETH Zürich**, Switzerland. His research focuses on formal verification, programming languages, and cybersecurity, with particular expertise in smart contract verification for blockchain systems like Ethereum and Libra’s Move language. He has contributed to tools such as Viper’s symbolic execution backend and frameworks for modular program verification. His work emphasizes practical applications of formal methods to ensure security and correctness in concurrent, distributed, and GPU-based systems. Key research areas include static analysis for information flow security, product program models, and SMT-based type inference for languages like Python. He is affiliated with the Professur für Software Technology at ETH Zürich’s CAB H 89 laboratory. Publications highlight advancements in verifying real-world systems such as internet routers, GPU kernels, and blockchain smart contracts. Though no awards are explicitly listed, his contributions reflect significant impact in formal verification and programming language research. Eilers’ advising and grants are not detailed here, but his involvement in cutting-edge projects like Igloo and modular product programs indicates active collaboration in distributed system verification and secure software development.

• Quantum Transport
• Nanoelectronics
• Thermoelectric Materials
• +3 more

Dr. Jiang Cao is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zürich. His research focuses on quantum transport phenomena in nanoscale devices, with an emphasis on ab initio simulations of electronic and optoelectronic systems. Key areas include nanoelectronics, thermoelectric materials, and 2D material-based devices. He specializes in advanced computational methods such as the GW approximation and non-equilibrium Green's functions for modeling quantum transport and device performance. Dr. Cao’s work spans topics like spin-charge qubits in van der Waals heterostructures, electron-electron interactions in nanodevices, and exascale simulations for nanoelectronics. His contributions include developing the Jiezi open-source Python framework for quantum transport simulations. His research addresses challenges in next-generation transistors, photovoltaic effects, and ultrafast material characterization. His recent articles highlight advancements in strained FinFET quantum devices, bulk photovoltaic effects in centrosymmetric materials, and the role of carrier-carrier interactions in sub-threshold transistor behavior. These studies bridge fundamental physics with practical device engineering, targeting applications in high-performance electronics and energy-efficient technologies.

• Tissue Engineering
• Biofabrication
• Biomechanics
• +3 more

Dr. Patrick Weber is a researcher at the Institute for Biomechanics (ETH Zürich) specializing in Tissue Engineering and Biofabrication . His work focuses on developing zwitterionic hydrogels for cartilage regeneration and osteoarthritis treatment, with recent studies evaluating their anti-inflammatory and lubricating properties in vivo and ex vivo models. Research Highlights: Zwitterionic polymer conjugates, cartilage surface damage quantification via micro-CT, bioprinting of cartilaginous constructs, immune response modulation via biomaterials Labs: Affiliated with the Tissue Engineering and Biofabrication group at ETH Zürich His publications demonstrate a trend toward zwitterionic hydrogels for osteoarthritis therapy, bioprinting techniques for tissue engineering, and novel diagnostic tools (e.g., Cartilage Roughness Score 2D). No scientific awards or student advisement details are mentioned in the provided texts.

• Systems Neuroscience
• Vocal Learning
• Neural Networks
• +4 more

Prof. Richard Hahnloser is a Full Professor at ETH Zürich's Department of Information Technology and Electrical Engineering, affiliated with the Institute for Neuroinformatics. He holds a PhD in Physics from ETH Zurich (1999, awarded the ETH Medal) and conducted postdoctoral research at MIT, Howard Hughes Medical Institute, and Bell Labs. His research focuses on neural mechanisms underlying vocal learning in songbirds, particularly auditory-motor signal processing and synaptic plasticity in neural networks. Education: Physics studies at ETH Lausanne and Zurich (Diploma 1996, PhD 1999). Career highlights include roles as a Swiss National Science Foundation Professor (2004–2007) before becoming a Full Professor at ETH Zurich in 2007. He explores interdisciplinary approaches combining experimental neuroscience, theoretical modeling, and bioimaging. Research interests include decoding neural networks of song systems, studying motor control via X-ray CT and Neuropixels recordings, and applying machine learning to vocal behavior analysis. Recent work highlights vocal plasticity, sleep-related neural dynamics, and neurotechnology for chronic neural recording. Notable achievements include the ETH Medal for his PhD and contributions to understanding syrinx anatomy and sensorimotor adaptation. His lab develops tools like MODOC for scientific text analysis and employs correlative microscopy techniques to study neural circuits.

• Cryptography
• Cryptographic Protocols
• Information Security
• +3 more

Dr. Michael Reichle is a Researcher at the Department of Computer Science, ETH Zürich, Switzerland. His work focuses on advanced cryptographic protocols, with particular emphasis on threshold signatures, blind signatures, and privacy-preserving technologies. He is affiliated with the Professur für Informatik (Computer Science Professorship) and contributes to cutting-edge research in cryptography and information security. Reichle's research interests include lattice-based cryptography, cryptographic protocol design, and secure computation. His recent work explores efficient blind signature schemes, cryptanalysis of isogeny-based systems, and forward-secure searchable encryption. His publications span topics like threshold cryptography, zero-knowledge proofs, and privacy-preserving authentication mechanisms. He has developed innovative cryptographic primitives such as Hermes for I/O-efficient searchable encryption and the TRaccoon threshold signature framework. His contributions emphasize practicality and security under standard assumptions, often avoiding reliance on cryptographic pairings or complex algebraic structures. No scientific awards or grants are explicitly mentioned in the provided texts. His contact information includes an email address at ETH Zurich's Computer Science Institute.

Thomas StastnyView profile

Researcher

• Unmanned Aerial Vehicles (UAVs)
• Autonomous Systems
• Control Theory
• +3 more

Dr. Thomas Stastny is affiliated with ETH Zürich's Autonomous Systems Department as a Researcher. His work focuses on advancing unmanned aerial vehicle (UAV) technologies, particularly in control systems, environmental monitoring, and autonomous navigation. Key research areas include fixed-wing UAV dynamics, solar-powered UAVs, wind-aware path optimization, and multi-agent robotic systems. His contributions span theoretical frameworks and experimental validations, with field applications in glacier monitoring and long-endurance aerial sensing. Research Highlights: Developed real-time wind prediction systems for UAVs (WindSeer project) Pioneered hybrid UAV designs like Soliro and Dipper for multimodal mobility Advanced control methodologies for high-angle-of-attack flight and VTOL transitions Explored solar-powered UAVs achieving multi-day endurance records Technical Expertise: Nonlinear model predictive control (MPC) Sensor fusion (radar/vision integration) Aerodynamic modeling and system identification Autonomous navigation algorithms His research integrates robotics, aerospace engineering, and environmental science to create robust airborne systems for challenging operational environments.

• Autonomous Systems
• Robotics
• Aerial Robotics
• +3 more

Dr. Michael Pantic is a Researcher in the Professorship for Autonomous Systems at ETH Zürich , affiliated with the Department of Mechanical and Process Engineering. His work focuses on advancing autonomous systems , particularly in aerial robotics , control systems , and sensor fusion . He specializes in developing innovative solutions for obstacle avoidance, navigation algorithms, and robotic manipulation in complex environments. His research emphasizes omnidirectional micro aerial vehicles (OMAVs) , reactive planning, and real-time obstacle avoidance techniques. Recent projects include corrosion inspection of infrastructure using autonomous robots and integrating radar with vision for robust depth prediction. Dr. Pantic's contributions bridge theoretical advancements with practical applications in industrial robotics and structural monitoring. Publications highlight trends in reactive navigation strategies , multi-resolution mapping , and physical interaction control . His work addresses challenges like local minima escape in path planning and minimizing actuator complexity in aerial manipulators. No scientific awards or student advisees are listed in the provided materials. Collaborative efforts include contributions to the MBZ International Robotics Challenge and the CleanSpace One Mission .

Fuda van DiggelenView profile

Researcher

• Swarm Robotics
• Robot Learning
• Machine Learning
• +4 more

Fuda van Diggelen is a Postdoctoral Researcher at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI) and the Institute of Microengineering (IGM). Their primary research focuses on the intersection of robotics and artificial intelligence, particularly in robot learning and emergent behaviors in swarms. They are part of the Laboratory of Intelligent Systems (LIS), where they investigate adaptive neural networks for distributed learning in robot swarms. Van Diggelen holds a PhD in Evolutionary Robotics from Vrije Universiteit Amsterdam (2024), supervised by Guszti Eiben and Eliseo Ferrante. Their doctoral work explored robot learning algorithms in evolving populations. They also earned two Master’s degrees: Human Movement Science (cum laude) from VU Amsterdam and Mechanical Engineering (Bio-Robotics) from TU Delft. Research interests include embodied intelligence, complex systems, control theory, and applications in healthcare such as ICU data analysis during the COVID-19 pandemic. Notable achievements include a nomination for the Best Master’s Thesis Award at VU Amsterdam and 3rd place in the IEEE RAS Multi Robot Systems (MRS) competition. They have contributed to projects like the Revolve software framework for robot evolution and the Dutch ICU Data Warehouse collaboration. Their work bridges robotics, AI, and healthcare, with a focus on developing adaptive systems for real-world challenges.

Arne SeitzView profile

Lecturer

• Bioimage Informatics
• Advanced Microscopy Techniques
• Biomedical Image Analysis
• +3 more

Arne Seitz is a Lecturer at EPFL's School of Engineering (SV), holding academic roles in the departments of Life Sciences Engineering and Bioimaging Technology. As Unit Manager of the Bioimaging and Optical Imaging Technology Platform (PTBIOP), he oversees advanced microscopy infrastructure and supports research in biological imaging. His teaching spans courses like Bioimage informatics , Advanced Microscopy for Life Science , and Image Processing for Life Science , emphasizing practical computational tools for biological data analysis. Research focuses on developing open-source software tools for microscopy and bioimage analysis, including ABBA+, MarrowQuant, and QUAREP-LiMi initiatives. These projects address challenges in image registration, diagnostic workflows, and reproducibility standards in microscopy. His work bridges basic science and clinical applications, such as automated bone marrow analysis and molecular diagnostics for heart transplants. Active in multi-department collaborations, Seitz contributes to educational programs across SV-SSV, EDPO, EDMS, and EDMX engineering schools. His labs and platforms provide cutting-edge imaging solutions for EPFL researchers, emphasizing open-access methodologies and community-driven scientific standards.

• Human Computer Interaction
• Digital Transformation
• User Experience Design (UX)
• +7 more

Maurizio Caon is a Full Professor and Head of Institute at the Fribourg School of Management (HES-SO), specializing in Human-Computer Interaction and Digital Transformation. His research focuses on health technology interventions for aging populations and adolescents, with a particular emphasis on e-coaching systems, wearable devices, and participatory design. He leads EU-funded projects like NESTORE (2017-2021), developing virtual coaches for older adults' well-being, and PEGASO (2013-2017), targeting adolescent health through gamified mobile platforms. Education: Not explicitly stated in text, but expertise in Ergonomics and Information Systems is implied through research focus. Research Interests: Designing human-centered technologies for health promotion, including tangible interfaces, behavior change models, and cross-cultural co-design. Key areas include aging workforce strategies, digital self-tracking, and ethical data practices. His work bridges HCI, healthcare innovation, and social impact. Publications highlight innovations in e-coach systems (e.g., NESTORE's multi-domain pathway), wearable technology's psychological impact, and VR exergames for seniors. Projects involve partnerships with Politecnico di Milano, EIA HumanTech Institute, and international teams. Grants: Principal investigator and co-investigator on EU H2020 and FP7 grants totaling over 890,000 CHF. Team: Collaborates with researchers like Leonardo Angelini, Elena Mugellini, and Omar Abou Khaled on interdisciplinary projects. Labs/Teams: Leading the NESTORE and PEGASO teams, focusing on digital health solutions for aging and youth populations. Involved in design processes for inclusive public spaces and ergonomic interfaces for cyclists.

• Optimization Methods
• Computational Mechanics
• Partial Differential Equations
• +3 more

Hardik Kothari is a Lecturer at the Faculty of Informatics of the Università della Svizzera italiana (USI). His research focuses on developing efficient numerical methods for optimization problems in partial differential equations, computational mechanics, constrained optimization, and machine learning. He works at the East Campus in Lugano, specifically in Office D5.16 (Level P5). His research interests emphasize advanced numerical techniques such as multigrid methods, preconditioning strategies, and their integration with machine learning approaches. Key areas include nonlinear optimization, phase-field modeling of fracture mechanics, and unfitted finite element methods for complex geometries. Recent publications highlight contributions to physics-informed neural networks, domain decomposition preconditioning, and scalable solvers for large-scale systems. His work bridges computational mathematics with engineering applications, addressing challenges in computational mechanics and high-performance computing. Kothari holds no explicitly mentioned scientific awards or grants but maintains active involvement in academic collaborations. His advising activities are not detailed here.

• Marketing Technology
• Artificial Intelligence
• Natural Language Processing
• +3 more

Dr. Guang Lu is a Lecturer at the Lucerne School of Business, affiliated with the Institute of Communication and Marketing (IKM) and its CC Communication & Marketing Technologies division. He holds a Ph.D. in Energy Science and Engineering from ETH Zurich (2016), an M.Sc. in Mechatronics from Southeast University (2010), and a B.Sc. in Mechanical Design from Southeast University (2007). His work bridges computational mechanics, marketing technologies, and AI-driven solutions for societal challenges. Dr. Lu’s research focuses on AI applications in elder care (e.g., emotion-aware chatbots), NLP for corporate culture analysis, and sustainability in e-commerce. He has pioneered studies on sharing economy dynamics, algorithmic nudging for eco-friendly consumer behavior, and greenwashing detection via ESG report analysis. His technical expertise spans computational fluid dynamics, granular mechanics (e.g., rockfall simulations), and multimodal emotion recognition systems. His career includes roles as a Computational Mechanics Engineer at WSL SLF (2017–2019), Researcher/Teaching Assistant at ETH Zurich (2010–2016), and Engineer at Southeast University’s Robotics Center (2007–2010). He has published over 39 peer-reviewed articles, with recent work emphasizing AI ethics in elder care technology and data-driven marketing strategies. Dr. Lu collaborates with industry partners like GPTW Switzerland AG and has conducted projects on corporate culture assessment, chatbot localization for German-speaking elderly populations, and algorithmic solutions for sustainable consumer choices. His research often integrates interdisciplinary methods, merging natural language processing with engineering systems to address modern business and societal challenges.

Marc PoulyView profile

Professor

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +6 more

Marc Pouly is a Professor of Artificial Intelligence at Lucerne University of Applied Sciences and Arts (HSLU), where he also serves as Co-Head of the Applied AI Research Lab. He holds a PhD in Artificial Intelligence from the University of Fribourg (2008) and has extensive industry experience as a Chief Data Scientist at Jaywalker AG and Scientific Advisor for Alpine AI and Artificialy SA. His research focuses on AI-driven solutions for healthcare, computer vision, natural language processing, and industrial optimization. Education: PhD in Artificial Intelligence (2004–2008), University of Fribourg MSc in Computer Science & Mathematics (2002–2004), University of Fribourg BSc in Computer Science (1999–2002), University of Fribourg Research Interests: His work spans Medical AI (e.g., dermatology diagnostics via computer vision), Generative Models , Recommender Systems , and AI Ethics . He co-developed the SkinApp for automated skin analysis and pioneered projects like CleanPatrick for image data quality audits. His expertise in self-supervised learning addresses data scarcity challenges in healthcare. Key Achievements: 2023: Best Paper Awards (IARIA, MICCAI) 2021: Research Mosaic recognition by swissuniversities 2017: Aha! Award for the SkinApp project Labs & Collaboration: He leads the Applied AI Lab and collaborates with institutions like ETH Zurich (co-supervising PhDs) and industry partners such as Prepress Media AG and the Swiss Allergy Centre. His work bridges academia and industry, emphasizing AI’s practical applications in healthcare, marketing, and cybersecurity.