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Philip MarmetView profile

Researcher

• Multiphysics Simulation
• Multiscale Modeling
• Microstructure Characterization
• +5 more

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.

• Computer Networking
• Network Security
• Software-Defined Networking
• +4 more

Laurent Vanbever is an Associate Professor at ETH Zürich's Department of Information Technology and Electrical Engineering and heads the Computer Engineering and Networks Lab. His research focuses on networking systems, with a strong emphasis on network security, routing protocols, software-defined networking (SDN), and distributed systems. He explores topics such as BGP convergence, energy-efficient router designs, and mitigating routing attacks on cryptocurrencies. His work bridges theoretical advancements with practical implementations, addressing challenges in network scalability, resilience, and sustainability. Key research areas include network verification, programmable packet processing (P4), and the security of decentralized systems like blockchain. Recent projects analyze transient forwarding anomalies, SDN-based network optimizations, and energy consumption in ISP networks. His contributions to network measurement and control plane innovations have significant implications for Internet architecture and operational practices. Vanbever actively publishes in top-tier conferences/journals and collaborates on open-source networking tools. His lab develops frameworks to enhance network performance and security, such as verifying link loads and mitigating BGP hijacks. Current efforts include exploring energy-efficient network designs and safeguarding cryptocurrency infrastructure against routing vulnerabilities.

• Embedded Sensors
• Sensor Networks
• Distributed Systems
• +3 more

Bruno Rodrigues is an Assistant Professor of Computer Science (Embedded Sensing Systems) at the University of St. Gallen (HSG). His research focuses on embedded sensors, sensor networks, distributed systems, and network security, with additional expertise in software-defined networks and distributed ledgers. He holds a PhD from the University of Zurich (2020), a Master's from the Polytechnic School of the University of São Paulo (2016), and a Bachelor's from the University of Santa Catarina, Brazil (2013). Prof. Rodrigues' professional career includes roles as a Senior Researcher (2020–2024) and Junior Researcher (2016–2020) at the University of Zurich, where he contributed to projects like the EU-funded CONCORDIA H2020 and collaborations with Swiss innovation agencies (KTI/Innosuisse). His work spans DDoS mitigation, blockchain applications in voting systems, and energy-efficient cloud networks. Notable projects include the 'Passive Wireless Intelligence Tracking System (PasWITS)' and 'Energy-Efficiency to Clouds (E2C)' with Ericsson Research. His research portfolio includes over 50 publications on topics such as secure IoT frameworks (SHIFT, WeTrace), blockchain-based voting systems (ProvotuMN, Æternum), and cybersecurity tools like SecGrid for traffic analysis. He has pioneered solutions for privacy-preserving mobile tracking (LaFlector), real-time medical device inventory systems (PMD-Track), and decentralized financial inclusion tools (AfriBit). Prof. Rodrigues' work bridges theoretical computer science with practical applications, emphasizing sustainability, security, and innovation in distributed systems. He has led interdisciplinary projects at the intersection of blockchain technology, sensor networks, and ethical AI, with a focus on real-world implementation challenges.

Thomas MaillartView profile

Senior Lecturer

• Collective Intelligence
• Complex Socio-Economic Systems
• Human Dynamics
• +12 more

Thomas Maillart is a Senior Lecturer and researcher at the Research Institute for Statistics and Information Science at the University of Geneva. His work bridges complex systems, collective intelligence, and cybersecurity, with a focus on modeling human dynamics and digital risks. Education: PhD in Science, ETH Zurich (2011) Master’s degree, EPFL (2005) His research centers on understanding how incentives, structures, and social interactions shape collective behavior in online and physical environments. He investigates topics such as cyber risks, privacy, resilience, and technological innovation. His work often applies statistical physics and data science to socio-technical systems, including open-source software development, cybersecurity policy, and human behavior modeling. His recent publications reflect a strong trend toward interdisciplinary research, combining insights from computer science, economics, psychology, and public policy. He explores how machine learning can forecast digitization labor needs, how collective action enhances cybersecurity, and how bio-sensors can aid in medical diagnosis. His work frequently appears in high-impact journals such as Science , PLOS ONE , and Physical Review . Scientific Awards: Zurich Dissertation Prize (2012) for pioneering work on cyber risks Thomas Maillart has advised and collaborated with numerous researchers and students, though specific names are not listed in the provided text. He has been involved in significant research grants and initiatives, including cybersecurity consulting for governmental and private organizations and co-founding a cybersecurity startup in 2005. His academic service includes organizing and presenting at international conferences such as WEIS and ACM conferences. He is associated with several research platforms, including ResearchGate, Google Scholar, LinkedIn, and Twitter, and has contributed to both peer-reviewed and practitioner-oriented publications. His recent editorial work includes co-editing a book on critical information infrastructure security.

Sébastien DoeraeneView profile

Lecturer

• Language design
• Compilers
• Virtual machines
• +4 more

Sébastien Doeraene is a Lecturer at the Swiss Federal Institute of Technology Lausanne (EPFL) , affiliated with the School of Computer and Communication Sciences and the Information Systems Laboratory . He is best known as the creator of Scala.js and serves as the Executive Director of the Scala Center . His research focuses on cross-platform language design, compiler optimization, and interoperability between statically and dynamically typed languages. PhD in Programming Languages (EPFL, 2018) Master of Science in Computer Science Engineering (Université catholique de Louvain, Belgium) His work bridges theoretical language design with practical implementations, particularly for JavaScript interoperability. Key projects include: Scala.js (compile Scala to JavaScript) Mozart 2 (Oz language implementation) Ozma (Scala extension with Oz concurrency) FunLabyrinthe (customizable maze game) Teaching contributions include courses on algorithmic thinking (C programming) and software development (Python, object-oriented design). As part of the LAMP laboratory , he advances Scala ecosystem tools and education initiatives.

Andrea CarronView profile

Senior Lecturer

• Model Predictive Control
• Learning-based Control
• Coverage Control
• +7 more

Dr. Andrea Carron is a Senior Lecturer at ETH Zürich, affiliated with the Intelligent Control Systems group under Professor M. Zeilinger at the Department of Mechanical and Process Engineering. He holds a PhD in Information Technology from the University of Padova (2016) and was a Postdoc at ETH Zurich from 2016 to 2020. Education: B.S. and M.Sc. in Control Engineering (University of Padova, 2010 and 2012) Professional Roles: Senior Lecturer (ETH Zurich, 2022–present), Postdoc Fellow (ETH Zurich, 2016–2020) Research Interests: Andrea Carron's work focuses on Model Predictive Control (MPC) and Learning-based Control with safety guarantees. His research addresses challenges in Distributed Safe Learning , Coverage Control , and Autonomous Racing , utilizing Gaussian Processes and Stochastic Control frameworks. He has developed safety filters for racing vehicles, scalable MPC for mobility-on-demand systems, and Kalman-filter-enhanced GP regression techniques. Article Trends: Recent publications emphasize Autonomous Racing (ForzaETH Race Stack), Safe Learning for distributed systems, Gaussian Process applications in control, and Robust MPC under uncertainty. His work bridges machine learning and classical control theory, with applications in robotics and real-time systems. Teaching Activities: He has taught courses such as Signals and Systems and Advanced Model Predictive Control at ETH Zurich and Ashesi University since 2017. Course content includes discrete-time signal processing, system identification, and control algorithms.

• Semantic technologies
• Ontology engineering
• Knowledge graphs
• +3 more

Vadym Yermolayev serves as a Professor at the Department of Computer Science and Information Technology within the Faculty of Applied Sciences at Ukrainian Catholic University (UCU). He leads UCU's PhD program in Intelligent Systems and holds an Honorary Professorship at Kherson State University. His academic work focuses on semantic technologies, ontology engineering, and knowledge graph construction, with active participation in international research projects and organizations like ACM and ELLIS. Professor of Semantic Technologies Head of PhD Program in Intelligent Systems Honorary Professor at Kherson State University Member of ACM and ELLIS Research Interests span semantic technologies, ontology engineering, and knowledge representation, with applications in education, industrial analytics, and anti-corruption systems. His work integrates machine learning with formal knowledge modeling and develops frameworks for knowledge ecosystem dynamics. Scientific Contributions include leading research groups at Zaporizhia National University and collaborating on European Commission-funded projects. He has published extensively in ICTERI conference proceedings and developed methodologies for terminology saturation analysis and ontology alignment. Honorary Professor at Kherson State University Member of ACM (Association for Computing Machinery) Member of ELLIS (European Laboratory for Learning and Intelligent Systems) Professional Involvement includes external expert roles for European Commission programs (FP6, FP7, H2020) and industrial consulting with Cadence Design Systems GmbH.

• Agile Methodologies
• Software Engineering
• DevOps
• +3 more

Prof. Martin Kropp is a Lecturer for Software Engineering and Programme Manager for the CAS Agile Organisation at FHNW University of Applied Sciences and Arts Northwestern Switzerland, within the School of Computer Science and FHNW Institute of Mobile and Distributed Systems. His research focuses on Agile Methodologies, Tool-supported Agile Collaboration, and Automated Software Construction/Testing. He actively contributes to the Swiss Agile Research Network (SARN) and Swiss Agile Study initiatives. Teaching responsibilities include courses on Software Construction, Testing & Quality Management, and .Net Framework/C# for the Bachelor of Computer Science, as well as the Master of Science in Engineering (MSE) in Software Engineering and Architecture. He has published extensively on Agile practices, DevOps metrics, and collaborative tools like aWall, emphasizing empirical studies and practical applications. Key research themes include Agile team dynamics, leadership in software development, and the integration of AI in testing and DevOps. His work bridges academic research and industrial practice, with notable contributions to conferences like ICSE, XP, and CHASE.

Alexander FuchsView profile

Researcher

• Power Grid Simulation
• Optimization
• Energy Networks
• +3 more

Dr. Alexander Fuchs serves as Principal Expert for power grid simulation at the Research Center for Energy Networks (FEN) at ETH Zurich, where he focuses on applications of optimization, simulation and geometric approaches for the planning and safe operation of power grids. His work spans European power grid modeling, renewable energy integration, and grid security analysis. Dr. Fuchs' research interests center on power grid optimization and simulation, with particular emphasis on the integration of renewable energy sources into existing grid infrastructure. His work addresses critical challenges in energy transition, including grid stability with high renewable penetration, optimal storage operation, and security analysis of power systems. He has developed specialized software for N-1 security analyses and secure load flow optimization, demonstrating his technical expertise in computational power system analysis. His publication record reveals a consistent focus on power system stability, HVDC transmission technologies, and renewable integration challenges. The research trajectory shows increasing attention to practical implementation challenges of energy transition policies, particularly evident in his more recent work on Swiss energy strategy and photovoltaic integration. His work bridges theoretical control systems with practical grid operation challenges. Dr. Fuchs has conducted significant research for the Swiss Federal Electricity Commission (ElCom), demonstrating his role as a trusted expert in national grid security matters. His projects span multiple European initiatives including ISCHESS, SCCER-FURIES, and ACSICON, indicating strong collaborative networks across the European energy research community. His work on the Energy Strategy 2050 simulation demonstrates direct policy relevance of his research.

Dimitar PetrovView profile

Associate Professor

• Static Analysis
• Cybersecurity
• Blockchain Smart Contracts
• +5 more

Dr. Dimitar Petrov is an Associate Professor in Computer Science at Ca’ Foscari University of Venice, specializing in static analysis and cybersecurity. He is affiliated with ETH Zürich's Institute of Pharmaceutical Sciences (IPW) as staff under Tit.-Prof. Jörg Scheuermann. His research focuses on applying abstract interpretation-based methods to detect security vulnerabilities in systems ranging from blockchain smart contracts to IoT devices. Education details are not explicitly provided in the text, but his extensive publication history indicates advanced expertise in formal methods. His research interests include software verification, privacy enforcement, and the application of static analysis tools like LiSA across diverse domains such as robotics, microservices, and mobile applications. Key research trends in his articles emphasize blockchain security (smart contract vulnerabilities, consensus protocols), IoT/IoMT security (device interactions, privacy policies), and the integration of machine learning with program analysis. His work bridges academic research with industry challenges, addressing compliance with regulations like GDPR and the EU Data Act. Prior to his current roles, he has contributed to open-source frameworks like LiSA and collaborated on projects involving automated policy extraction, cross-language analysis, and vulnerability detection in automotive systems. His research group at Ca’ Foscari actively engages in both theoretical advancements and practical tool development. Labs/Teams: Part of the Software and System Verification group at Ca’ Foscari, and collaborates with ETH Zürich's Institute of Pharmaceutical Sciences on interdisciplinary projects combining formal methods with healthcare technology.

• Embedded Systems
• Internet of Things (IoT)
• Smart Mobility
• +6 more

Vannel Fabien is a Full Professor at the Haute école du paysage, d'ingénierie et d'architecture de Genève (HEPIA), part of the HES-SO University of Applied Sciences and Arts. He is affiliated with the Technical and IT School and the Department of Computer Science and Communication Systems. His research focuses on embedded systems, IoT, FPGA-based architectures, neuromorphic computing, and quantum communication technologies. Education: PhD in Bio-inspired Computing (2007), École Polytechnique Fédérale de Lausanne (EPFL), supervised by Daniel Mange Research Interests: Development of self-organizing neuromorphic hardware architectures (SOMA project) High-performance FPGA-based platforms for IoT security and random number generation Cellular computing inspired by biological systems 3D Network-on-Chip (NoC) architectures and dynamic resource allocation Quantum key distribution (QKD) systems for secure communication His work combines hardware design with bio-inspired algorithms, aiming to create adaptive, energy-efficient computing systems. Recent projects include SCALPsim (a 3D NoC modeling tool) and FPGA-based validation platforms for TRNGs. Grants & Projects: Principal investigator for SOMA (2018-2021, SNSF-funded CHF 461,238) Co-applicant for iNUIT-2014 ArchSensor (2014-2015, HES-SO-funded CHF 220,000) Contributor to heterogeneous computing platforms (AcceleRation, 2013-2014) Labs & Teams: Lead researcher in the SOMA team at HES-SO, collaborating with institutions like Université de Nice and INRIA.

• 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.

Marcin CopikView profile

Researcher

• Parallel Computing
• High-Performance Computing (HPC)
• Serverless Systems
• +3 more

Dr. Marcin Copik is a Researcher in the Professorship for Scalable Parallel Computing at ETH Zürich, focusing on advancing high-performance computing (HPC), serverless systems, and cloud computing. His work emphasizes optimizing resource utilization, improving scalability, and enhancing performance in distributed and parallel environments. His research interests span parallel computing architectures, serverless benchmarking (e.g., SeBS suite), and sustainable HPC practices. He explores techniques like automatic loop scheduling, acceleration-as-a-service models, and fault-tolerant distributed systems (e.g., FaaSKeeper). His contributions address challenges in cloud elasticity, stateful services, and energy-efficient computing. Recent publications highlight innovations in serverless workflows, AI reasoning frameworks, and hardware-accelerated protocols. His work bridges theoretical foundations with practical implementations, such as Cppless for high-performance serverless programming and XaaS for HPC-cloud integration. While no formal awards or grants are listed, his contributions to open-source projects like STEllAR-GROUP/hpx and Extrapeak demonstrate active engagement in the HPC community. He collaborates closely with academic and industry partners to advance scalable computing solutions.

• 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.

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.