Alberto Dassatti is a Full Professor at HES-SO University of Applied Sciences Western Switzerland and Director of the Reconfigurable & Embedded Digital Systems (REDS) Institute. He is affiliated with the School of Engineering and Management of the Canton of Vaud. His work focuses on embedded systems, FPGA applications, high-performance computing, and topological data analysis. He has led and collaborated on numerous projects funded by institutions like Innosuisse and HES-SO Rectorat, totaling over CHF 1.2 million in grants. His research spans computational storage systems, medical sensor technologies, and signal processing frameworks for wireless communication. Key projects include developing the CarbonViz energy visualization tool, advancing topological methods for AI reliability, and creating the BB-Sensors system for neonatal vital monitoring. He has contributed to open-source frameworks like giotto-tda and gr-dnn, emphasizing interdisciplinary collaboration between hardware and software domains. His publications span topics such as FPGA-GPU communication, real-time embedded systems optimization, and heterogeneous computing architectures. He actively participates in conferences like NeurIPS and IEEE SOC, showcasing innovations in reconfigurable computing and energy-efficient systems.
Overview Manfredo Atzori serves as a Scientific Assistant (Adjoint-e scientifique HES A) at HES-SO Valais-Wallis's Haute Ecole de Gestion. His work focuses on advancing machine learning applications in biomedical engineering, digital pathology, and neuroimaging. He leads development of open-source tools like BIDSAlign for EEG standardization and SelfEEG for self-supervised learning in biomedical signals. Research Interests Atzori's research bridges AI and healthcare, emphasizing: Medical Imaging : Histopathology WSI analysis, artifact correction, and cross-modal fusion Prosthetics Control : sEMG-based gesture recognition and adaptive neural interfaces Deep Learning Methodology : Transfer learning optimization, self-supervised pretraining, and reproducibility frameworks Key Contributions 2024 highlights include: Developed RegWSI - winning ACROBAT 2023 challenge for WSI registration Pioneered multimodal WSI-report integration to halve annotation needs Published benchmark studies on Gleason grading deep learning methods Collaborations Active in international projects with institutions like DeeperHistReg group and OpenNeuro. Tools developed are open-source (GitHub: @manfredoatzori) to advance reproducible research practices.
Prof. Timo Kehrer is a Professor and Head of the Software Engineering Group (SEG) at the Institute of Computer Science, University of Bern. He also serves as Deputy Director of Studies, overseeing academic programs in software engineering. His research focuses on variability modeling, model-based systems engineering, simulation-based testing of autonomous systems, and empirical studies in software development practices. Key areas include software product lines, cyber-physical systems, and the application of formal methods in industrial contexts. Notable contributions include work on Community-driven variability management in open-source software, Automated testing tools like ScoutSL and TEASER , Simulation-based frameworks for self-driving cars (e.g., Sensodat datasets), and Empirical analyses of GitHub Actions workflows and merge conflict resolution. His research bridges theory and practice, addressing challenges in software sustainability, AI-driven development, and the integration of formal verification tools like TLA+. He actively participates in conferences such as VaMoS (Variability Modelling) and contributes to open-source projects in model-driven engineering. Prof. Kehrer collaborates with industry partners to advance tools for model repositories, vulnerability detection (e.g., VUDENC ), and semantic analysis of software changes. His work emphasizes reproducibility, tool support for developers, and educational initiatives to modernize software engineering curricula.
Petr Listov is a former researcher at the Swiss Federal Institute of Technology in Lausanne (EPFL), affiliated with the School of Engineering. His work focuses on advanced control systems, particularly Model Predictive Control (MPC) for autonomous systems, robotics, and mechatronics. Listov contributed to developing the PolyMPC software framework, enhancing real-time embedded optimization for applications like rocket control and autonomous driving. His research emphasizes nonlinear control, stochastic systems, and optimization under uncertainty. Education: Completed a doctoral thesis titled Real-Time Nonlinear Model Predictive Control for Fast Mechatronic Systems under supervision at EPFL. Research Interests: Development of MPC algorithms for high-speed systems Applications in autonomous vehicles and robotics Stochastic control and uncertainty quantification Optimization-based control strategies Key Contributions: His publications address real-time MPC implementations, thrust vector control for rockets, and stochastic trajectory planning. Experimental validations include indoor/outdoor rocket testing and automotive hardware-in-the-loop systems. Labs/Teams: Collaborated with the Laboratoire d’Automatique (LA) and contributed to the PolyMPC open-source library.
Nada Amin is an Assistant Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS). She holds a PhD from École Polytechnique Fédérale de Lausanne (EPFL) and degrees from MIT. Her research spans programming language theory, metaprogramming, semantics, and functional programming. Her educational background includes a Doctoral Program in Computer, Communication and Information Sciences from EPFL (2011–2016) and a Master of Engineering and Bachelor of Science from MIT. She has held research positions at TU Darmstadt, University of Cambridge, EPFL, Microsoft Research, and MIT CSAIL. Nada Amin's research focuses on foundational and practical aspects of programming languages. She investigates type systems, staged computation, generative programming, program synthesis, and the semantics of programming languages. Her work often bridges theory and implementation, with applications in verification, compiler construction, and language design. She is particularly known for her contributions to the DOT calculus, collapsing towers of interpreters, and relational programming with miniKanren. Her recent publications reveal a strong trend in advancing programming language foundations, especially in type systems and semantics (e.g., Persimmon, Dolorem, Extensible Metatheory). She integrates functional and logic programming paradigms, explores staged and generative techniques for efficiency and abstraction, and applies these to domains like probabilistic programming and biomedical reasoning. Recipient of the first Michigan Cambridge Research Initiative Grant (with Baris Kasikci, May 2018) 6.170 Letter of Commendation from Prof. Michael Ernst (2005) Peer Bonus at Google for enabling Gmail's CSS compiler for Android Peer Bonus at Google for benefiting numerous projects including Google Apps Nada Amin actively mentors students and collaborates widely in the programming languages community. She has served on numerous program committees (POPL, PLDI, ICFP, OOPSLA, etc.) and organized workshops. Her work is supported by academic and industrial collaborations, and she has contributed to open-source projects. She leads research involving interpreters, compilers, and program transformation systems, often developing tools and frameworks like LMS and Pink.
Francesco Mondada is an Adjunct Professor at École Polytechnique Fédérale de Lausanne (EPFL) with multiple affiliations across the university. He holds positions in the School of Engineering (STI) within the Institute of Microengineering (IEM) as part of the FMO1 group, in the School of Computer and Communication Sciences (IC) with the FMO2 group, and serves as Academic Director of the Centre for Learning Science. His work spans robotics research, educational innovation, and interdisciplinary collaborations connecting engineering with biology, art, and education. Dr. Mondada received his M.Sc. in micro-engineering in 1991 and his Doctoral degree in 1997, both from EPFL. During his doctoral studies, he co-founded K-Team, serving as CEO and president for approximately five years. He is one of the three principal developers of the Khepera robot, which became a standard platform in bio-inspired robotics and was adopted by over 1,000 universities and research centers worldwide. After returning to research in 2000, he participated in the EU's SWARM-BOTS project as the main developer of the s-bot robot platform, which was ranked 39th in Wired Journal's "The 50 Best Robots Ever" list in 2006. His research focuses on the mechatronic design of miniature mobile robots, serving as an excellent example of interdisciplinary mechatronics that engages EPFL students across mechanical design, electronic design, software development, system integration, signal processing, embedded programming, and artificial intelligence. His work enables interdisciplinary research connecting mechanics, electronics, computer science, and communication with biology, psychology, design, and art. His primary research areas include swarm robotics, animal-robot interaction, biohybrid systems, and educational robotics. Analysis of his recent publications (2022-2024) reveals a strong focus on biohybrid robotics, particularly robot-fish and robot-bee interactions, alongside significant contributions to educational robotics and computer science education. His work demonstrates a clear trajectory toward integrating robotics with biological systems and advancing pedagogical approaches for teaching computational thinking and computer science from primary through secondary education. EPFL Latsis University prize (2005) for contributions to bio-inspired robotics Crédit Suisse Award for Best Teaching (2011) from EPFL polysphère award (2012) from students as best teacher in the School of Engineering Dr. Mondada has been actively involved in advising and educational initiatives, particularly through the Centre for Learning Science where he serves as Academic Director. His work on educational robotics platforms like Thymio has significantly impacted computer science education, with numerous publications on teacher training models, curriculum implementation, and computational thinking assessment. He leads the MOBOTS research group, which develops innovative mechatronic solutions for mobile and modular robots while making robot platforms more accessible for education, research, and industrial development. As leader of the MOBOTS group, Dr. Mondada oversees research on miniature mobile robots for swarm robotics, animal-robot interaction, and educational applications. His team has developed several robotic platforms including the Thymio educational robot, which has become widely adopted in educational settings. The group's work bridges theoretical robotics research with practical applications in education and biological studies, creating a unique interdisciplinary environment that connects engineering with biology, psychology, and pedagogy.
Barbara Jobstmann is a Lecturer at the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL), where she is also affiliated with the SIN - Administration unit (SIN-GE). She contributes to teaching and organizes outreach initiatives such as the IC Declic Summer School. Additionally, she works for Cadence Design Systems, indicating a strong industry-academia connection in her professional profile. Her research focuses on the development of reliable computer systems through formal methods. Key interests include the synthesis and repair of reactive programs, quantitative verification and synthesis, and the use of temporal logics for system specifications. She investigates the analysis and verification of hardware designs, transactional memories, business process models, and embedded systems. Her theoretical work extends to interface theory, infinite games, and automata theory, which underpin robust system design and verification. While no recent publications or awards are listed in the provided text, her expertise lies at the intersection of theoretical computer science and practical system reliability. She plays an active role in education and outreach within EPFL's computer science community. Barbara Jobstmann has no listed scientific awards or recognitions in the provided information. She advises or has advised no students listed in the current data. There is no mention of research grants or funding sources. She is involved in organizing the IC Declic Summer School, contributing to EPFL’s educational outreach. She is associated with the SIN (Systems, Architecture, Software) research group at EPFL’s School of Computer and Communication Sciences, where she conducts research and contributes to academic and outreach activities.
Yichen Xu is a Doctoral Assistant at the Programming Methods Laboratory (LAMP1) within the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL). He is currently pursuing his Ph.D. in Computer Science under the supervision of Professor Martin Odersky, the creator of Scala. Bachelor of Engineering in Computer Science, Beijing University of Posts and Telecommunications (2018–2022) Doctor of Philosophy in Computer Science, EPFL (2022–present) Yichen's research bridges programming language theory and machine learning. His primary focus lies in advancing Scala's type system, particularly through work on Capture Calculus and Generalized Algebraic Data Types (GADTs), aiming to achieve safe and efficient effect tracking. He has also made significant contributions to graph representation learning, especially in contrastive learning frameworks for graphs. His work spans both theoretical foundations and practical implementations in compilers and open-source libraries. His recent publications reveal a strong trend in formal methods for programming languages and self-supervised learning on graphs. Key themes include data race prevention via flexible type systems, formalization of inference rules in type calculi, and empirical studies on contrastive learning with adaptive augmentation and structure-aware mining. These works have been published in venues such as IWACO, NeurIPS, WWW, and Scala Symposium. First Prize in NSCSCC 2020 competition (EasterMIPS CPU project) Yichen has been actively involved in mentoring and collaborative research, contributing to major projects like CodeGeeX and the Scala 3 compiler (dotty). He has worked closely with researchers including Prof. Shu Wu, Prof. Zhilin Yang, Dr. Aleksander Boruch-Gruszecki, and Yanqiao Zhu. His open-source contributions include tools like PyGCL, fscala2c, and meow, reflecting a strong commitment to practical software development and community engagement. He is part of the Programming Methods Laboratory at EPFL and has previously been affiliated with research groups at CRIPAC (CASIA) and IIIS (Tsinghua University), forming a broad collaborative network in programming languages and machine learning.
Viktor Kuncak is an Associate Professor at the École polytechnique fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences (IC) , affiliated with the Laboratory for Automated Reasoning and Analysis (LARA) . His work bridges programming languages, formal verification, and automated reasoning. Email: viktor.kuncak@epfl.ch Office: INR 318, EPFL, Lausanne, Switzerland Research Interests: Viktor specializes in formal verification , theorem proving , and program synthesis , focusing on languages, algorithms, and systems for automated reasoning. His research addresses verification of functional programs, constraint solving, and symbolic computation. Recent Publications Trends: His work includes mechanized HOL reasoning, algebraic array theories, interpolation in ortholattices, and symbolic automata complexity. Keywords span automated reasoning, formal methods, and functional programming. Scientific Awards: 2012: 5-year ERC grant (1.5M EUR) ACM SIGSOFT Distinguished Paper Award Invited talks at Lambda Days, Scala Days, and CACM Research Highlights Advising & Grants: Viktor has supervised 15+ PhD students and led a European COST network in automated reasoning. He served as Associate Editor for TOPLAS and co-chaired CAV, FMCAD, and VMCAI conferences. Labs & Teams: He leads LARA , which develops tools like Leon and Stainless for program verification and synthesis. The group focuses on scalable formal methods for reliable software.
Prof. Bryan Alexander Ford is an Associate Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he leads the Decentralized and Distributed Systems (DEDIS) lab within the School of Computer and Communication Sciences, Department of Computer Science. He also holds teaching positions in SIN (Systems and Networking) and SSC (Security and Software Composition) at EPFL, and serves on the Open Science Strategic Committee. His academic journey includes faculty positions at Yale University following his Ph.D. at MIT. Dr. Ford's research spans multiple domains with a primary focus on building secure decentralized systems. His work encompasses privacy and anonymous communication systems like Dissent, systems security, blockchain technology, and novel approaches to operating systems for deterministic parallel computing such as Determinator. He has made seminal contributions to parsing theory through his development of Parsing Expression Grammars (PEGs) and packrat parsing algorithms, which provide linear-time parsing with backtracking capabilities. His research also extends to networking protocols including the Unmanaged Internet Architecture and Structured Stream Transport, as well as virtualization technologies like VX32. Ford's publication record demonstrates a remarkable evolution from foundational work in parsing and programming languages to cutting-edge research in decentralized systems and security. His early career focused on operating systems theory, parsing algorithms, and language design, culminating in influential papers on packrat parsing and PEGs. More recently, his work has shifted toward practical decentralized systems, blockchain technology, and security architectures, while maintaining connections to programming language theory through projects like Matchertext and MinML. This trajectory reflects both continuity in his interest in system architecture and a strategic pivot toward emerging challenges in decentralized computing. As an educator and mentor, Ford advises multiple PhD students at EPFL through the EDIC program and welcomes prospective students and researchers to join his lab. His teaching includes courses on decentralized systems engineering and technologies for democratic society, reflecting his commitment to both technical rigor and societal impact of computing technologies.
Rishabh Iyer is an Assistant Professor in the Electrical Engineering and Computer Sciences department at the University of California, Berkeley. His research bridges computer systems, networking, and formal methods with a focus on performance predictability and reliability. Prior to Berkeley, he completed his PhD at EPFL and undergraduate studies at IIT Bombay. His educational background includes: PhD in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL) Bachelor's degree from Indian Institute of Technology Bombay (IIT Bombay) Iyer's research centers on performance interfaces for computer systems – creating succinct abstractions that allow engineers to reason about system performance without understanding implementation details. His work spans three major directions: (1) Extracting performance interfaces from implementations, (2) Designing systems with predictable performance, and (3) Formally verifying performance claims. This research combines operating systems, networking, computer architecture, and formal verification techniques to address performance unpredictability in modern systems. His group develops tools like PIX for network functions, KFlex for kernel extensions, and Software LPN for hardware accelerators. His publications reveal strong focus on performance modeling for network functions, kernel extensions, and hardware accelerators, with recent work expanding into real-time systems and SD-WAN validation. The research consistently targets practical impact, with deployments at companies like Meta and Alibaba. Scientific recognition includes: ACM SIGOPS Dennis M. Ritchie Award Eurosys Roger Needham PhD Award Dimitris N. Chorafas Award Best Paper at VDAT 2019 Iyer actively advises students at UC Berkeley and teaches courses including CS 294-262 (Performance Analysis) and CS 168 (Internet Architecture). Previously at EPFL, he taught Principles of Computer Systems, Software Engineering, and Vector Calculus. His group seeks talented students interested in building reliable, high-performance systems. Current research directions include performance interfaces for distributed applications, next-generation kernel extensions, and formally verified network systems. He leads research within UC Berkeley's systems community and maintains strong connections with EPFL's Dependable Systems Lab where he completed his PhD.
Markus Reiher is a Full Professor at the Department of Chemistry and Applied Biosciences, ETH Zurich, where he leads a research group focused on theoretical chemistry since 2006. His work bridges quantum mechanics and computational chemistry, emphasizing electronic structure theory and algorithm development for chemical reaction exploration. BSc in Chemistry (University of Bielefeld, 1995) PhD in Chemistry (University of Bielefeld, 1998) Habilitation in Chemistry (University of Erlangen, 2002) His research spans quantum computing applications in chemistry, machine learning potentials, and advanced methods for reaction networks. Recent publications highlight quantum-classical hybrid models, vibronic structure simulations, and solvent effects in chemical processes. Scientific awards include the ADUC Annual Prize (2004), Emmy Noether Habilitation Award (2003), Golden Owl Award for Teaching (2010), Löwdin Lecture (2018), and Heilbronn-Hückel Lectureship (2023). He was elected to the International Academy of Quantum Molecular Science in 2022.
Sereina Riniker is a Full Professor of Computational Chemistry at the Department of Chemistry and Applied Biosciences , ETH Zurich. Her career at ETH Zurich began in June 2014 as Assistant Professor (tenure track), followed by promotions to Associate Professor (April 2020) and Full Professor (April 2025). The group focuses on developing advanced computational methods combining molecular dynamics simulations with cheminformatics techniques . Born in Switzerland (1985) MSc in Chemistry (ETH Zurich, 2008) PhD in Molecular Dynamics (ETH Zurich, 2013) Research interests include: QM/MM hybrid simulations Machine learning for molecular modeling Free energy calculations Implicit solvent models Conformational analysis Drug discovery applications Recent publications show strong trends in combining quantum mechanical accuracy with machine learning efficiency , including novel approaches like neural network potentials and multiresolution modeling . The group has received multiple grants from the Swiss National Science Foundation (SNF) for their work on free energy calculations and molecular modeling . Awards and honors include: 2024 Hansch Award 2018 ETH Latsis Prize 2017 OpenEye Outstanding Junior Faculty Award 2017 Silver Jubilee Award 2015 Ewald Wicke Prize The Computational Chemistry group maintains strong industrial collaborations, particularly with Novartis and Givaudan AG. Their research combines theoretical method development with practical applications in biological and chemical systems.
Prof. Hans Wernher van de Venn is a Professor at the ZHAW School of Engineering's Institute of Mechatronic Systems, Zurich, Switzerland. His work focuses on Industry 4.0, robotics, predictive maintenance, and human-robot collaboration. He leads and collaborates on projects such as SmartAssets, Cybathlon 2024, and Robo-Mate, aiming to enhance industrial automation and safety. Research Interests: His research spans robotics systems, digital twins, and sustainable manufacturing. Notable contributions include predictive maintenance algorithms using autoencoders and domain adaptation techniques, as well as advancements in human-robot interaction safety through deep learning. He has also pioneered wearable robotic exoskeletons for industrial applications. Projects & Awards: Over 20 projects highlight his leadership in Industry 4.0 innovation. Recent work includes testing frameworks for digital twins, generative SDK development, and applying ChatGPT for structured industrial data. His publications emphasize practical applications of AI in manufacturing and healthcare robotics. Grants & Labs: Active in collaborative grants focusing on smart factories, maintenance systems, and embedded systems. His team develops solutions at the intersection of mechatronics and software engineering, with a focus on real-world deployment.
Marcel Joss is a Lecturer at the Institute of Electrical Engineering (IET) within the Lucerne School of Engineering and Architecture at Hochschule Luzern, Technik & Architektur. He has held this position since 2003 and previously served as the Head of the Electrical Engineering Department (2005–2010) and project leader for Bologna reform implementation (2003–2005). His expertise spans telecommunications, microwave engineering, and autonomous systems. Education 1983–86: Diploma in Electrical Engineering, HTL Brugg/Windisch 1989–92: Advanced Diploma in System Technology, Neu-Technikum Buchs SG 1995–96: Master of Science in Communication Networks, EPF Lausanne 2000: International Executive Program (INSEAD) Research Interests Dr. Joss focuses on microwave engineering, satellite communication, wireless power transfer, and autonomous systems. His work includes projects like the CHESS CubeSat mission for atmospheric research, microwave-based medical monitoring, and innovative data communication solutions for cableway systems. He actively explores applications in industrial automation, sensor networks, and energy-efficient systems. Key Projects Satellite Tracking with Radio Detection Wireless Power Transmission at Millimeter Waves CHESS CubeSat Atmospheric Dynamics Measurement Multiband Sensor Networks (MBSnet) Professional Contributions Joss has led Swisscom Mobile AG teams in network development and technology integration. He is also a member of the Amateur Radio Club at HSLU, promoting hands-on technical education. His presentations on 5G technology, antenna design, and railway communication highlight his dual focus on academic and industrial innovation.
