Find Academic Supervisors

Mathieu SalzmannView profile

Academic

• Computer Vision
• Machine Learning
• Deep Learning
• +7 more

Mathieu Salzmann is a Senior Scientist and Lecturer at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Computer Vision Laboratory (CVLAB) in the School of Computer and Communication Sciences (IC). He also holds a courtesy appointment with the EPFL College of Humanities and serves as Deputy Chief Data Scientist at the Swiss Data Science Center (SDSC). He has held concurrent roles in teaching units including SIN, SODH, and SSC, reflecting his interdisciplinary engagement. His research focuses on the intersection of machine learning and computer vision, particularly in deep learning for 2D and 3D visual scene understanding, efficient and robust models, domain adaptation, and interpretable AI. These interests are evident across his extensive publication record in top-tier venues. His recent publications (2023–2024) show a consistent trend in advancing deep learning methods for visual recognition, with strong representation at CVPR, ICCV, ECCV, ICML, ICLR, and NeurIPS. Topics include domain generalization, 3D understanding, model robustness, and multimodal learning, often with applications in real-world systems. His editorial roles as Associate Editor for IEEE TPAMI and Action Editor for TMLR further highlight his leadership in the field. Area Chair: ICML 2023, CVPR 2023, ICCV 2023, NeurIPS 2023, AAAI 2024, ECCV 2024 Associate Editor: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Action Editor: Transactions on Machine Learning Research (TMLR) Mathieu Salzmann has supervised numerous PhD students at EPFL, both current and past, including Bouquet Yann Yanis, Javed Saqib, Li Shuangqi, and others. He has also been involved in research grants and collaborative projects, such as his work with S. Süsstrunk and R. Baroni on comics reconfiguration. His part-time role as Senior GNC Engineer at ClearSpace (2020–2024) illustrates his applied research engagement in aerospace systems. He is actively involved in EPFL’s data science and AI research ecosystem through SDSC and multiple labs.

Ana KlimovicView profile

Assistant Professor

• Cloud Computing
• Operating Systems
• Distributed Systems
• +4 more

Ana Klimovic is an Assistant Professor at the Department of Computer Science, ETH Zürich, and Deputy Head of the Institute for Computing Platforms. She leads the Efficient Architectures and Systems Lab (EASL) and focuses on optimizing cloud computing performance and resource efficiency. Education: Ph.D. in Electrical Engineering (Stanford University), M.S. in Electrical Engineering (Stanford), B.A.Sc. in Engineering Science (University of Toronto) Previous Roles: Research Scientist at Google Brain Her research spans cloud computing, operating systems, distributed systems, and their intersection with machine learning. Key areas include cloud-native programming models, elastic storage, GPU sharing, and data pipeline optimization. The 2025-2024 articles highlight trends in serverless computing, large language model (LLM) serving, GPU optimization, and data-centric ML systems. Themes include elasticity, resource multiplexing, heterogeneous computing, and infrastructure for AI/ML workloads. Scientific Awards: Microsoft Research PhD Fellowship, Stanford Graduate Fellowship She has led research projects on ephemeral storage, distributed training automation, and cost-efficient ML preprocessing, with grants from Microsoft Research and Stanford.

• Computer Architecture
• Datacenter Systems
• Cloud-Native Server Architecture
• +7 more

Babak Falsafi is a Full Professor at the School of Computer and Communication Sciences (IC) at EPFL, leading the Parallel Systems Architecture Laboratory (PARSA). He is a renowned expert in computer architecture, datacenter systems, and cloud-native server design. His research focuses on post-Moore era computing, emphasizing heterogeneous architectures, energy efficiency, and scalable IT infrastructure. Falsafi is the founder of EcoCloud, an EC-sponsored industrial-academic consortium investigating sustainable information technology. He holds ACM and IEEE fellowships, a Sloan Research Fellowship, and has contributed to major projects like Optimus Prime (data transformation acceleration), AstriFlash (flash-based online service systems), and Midgard (virtual memory re-design). His work spans hardware-software co-design, memory systems, and security. Falsafi advises numerous PhD students and collaborates with industry partners such as Google and Cavium. Key achievements include pioneering scalable multiprocessor architectures, snoop filters in IBM BlueGene, and spatial memory streaming in ARM cores. His lab develops open-source tools like QFlex for server simulation. He frequently presents at top conferences (HPCA, ISCA, MICRO) and chairs workshops on post-Moore infrastructure. Teaching roles include leading courses in computer architecture and parallel systems across multiple EPFL departments (SIN, EDIC, SSC, SMA). His work addresses datacenter challenges like the 'data tax' and mitigating latency through specialized accelerators.

Lorin SchöniView profile

Lecturer

• Human-Centered Security
• Human-Computer Interaction
• Human-AI Interaction
• +6 more

Lorin Schöni is a PhD candidate at ETH Zürich, actively contributing to the Security, Privacy and Society research group since October 2022. Concurrently, he serves as a Lecturer at the Department of Humanities, Social and Political Sciences, where he teaches the course Focus on the Human: Human-Centered Security and Privacy Lab (Autumn Semester 2025, Unit 851-0391-00L). His research focuses on human-centered approaches to cybersecurity , particularly through three key domains: Human-Computer Interaction - Investigating design decisions that influence user behavior in digital security contexts Extended Reality Applications - Developing immersive training systems for phishing prevention Usability Engineering - Creating intuitive security interfaces with explainable AI components Recent publications highlight his work at the intersection of autonomous motivation theory and personalized cybersecurity training , with notable presentations at top venues including CHI 2025 and SOUPS 2024. His research aims to transform security from a restrictive framework into a collaborative partnership between users and digital systems, as emphasized in his award-winning work on human-centered cybersecurity.

David BasinView profile

Professor

• Information Security
• Formal Methods
• Cryptography
• +3 more

David Basin is a Full Professor at the Department of Computer Science, ETH Zurich, and heads the Information Security Group. He has held academic positions since 2003, including roles at the University of Freiburg (1997–2002) and the Max-Planck-Institut für Informatik (1992–1997). His research focuses on Information Security, including methods and tools for secure systems, formal verification, and cryptographic protocols. He is Editor-in-Chief of the ACM Transactions on Privacy and Security and Springer's Information Security and Cryptography book series. Basin founded the Zurich Information Security Center (ZISC) in 2003 and led it until 2011. Education: B.Sc. in Mathematics (Reed College, 1984), Ph.D. (Cornell University, 1989), and Habilitation (University of Saarbrücken, 1996). Research interests span formal methods for security protocol verification, privacy-preserving systems, and cryptographic implementations. He has contributed to foundational work on security protocols, including the Tamarin verification framework. His work addresses real-world systems like payment protocols (EMV), DNS security, and database isolation guarantees. Awards: ACM Fellow (2018) for contributions to Information Security and Formal Methods, IEEE Fellow. He has organized numerous conferences, including IEEE S&P, Euro S&P, and ACM CCS. Labs/Teams: Leads the Information Security Group at ETH Zurich and co-founded Anapaya Systems, a startup focused on network security solutions. His team develops tools like VeriMon (formally verified monitoring) and Tamarin for protocol analysis.

Peter MüllerView profile

Professor

• Formal Methods
• Program Verification
• Programming Languages
• +4 more

Prof. Peter Müller is a Full Professor at the Department of Computer Science at ETH Zurich since 2008. Previously, he held positions as Assistant Professor at ETH Zurich (2003-2008), Researcher at Microsoft Research Redmond (2007-2008), and IT project manager at Deutsche Bank. He earned his Diploma in Computer Science from Technical University of Munich (1996) and his Dr. rer. nat. from University of Hagen (2001) with a dissertation on modular verification of object-oriented programs. His research focuses on enabling correct software development through programming languages, verification methods, and tools. Key areas include formal verification for Rust and Go programs (Prusti and Gobra projects), separation logic, security protocols, and distributed systems verification. Müller's work emphasizes practical verification techniques for real-world systems, including secure router implementations and smart contract verification. Recent research trends highlight advancements in hyperproperties, modular reasoning for iterators and closures in Rust, and formal validation of verification tools. His methodologies bridge theoretical foundations with industrial applications, addressing challenges in concurrency, memory safety, and security assurance. Notable contributions include the SCION internet architecture, the Prusti verifier for Rust, and formal verification frameworks for distributed systems. His work often integrates rigorous mathematical foundations with scalable software engineering practices.

Francesca RodinoView profile

Research Fellow

• Electrochemical Biosensors
• Therapeutic Drug Monitoring
• Precision Oncology
• +4 more

Francesca Rodino is a Doctoral Assistant and Research Fellow at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering and the Electrical and Microengineering Institute (IEM). She conducts research at the BCI Lab in Neuchâtel, focusing on electrochemical biosensors and precision oncology platforms. She is concurrently pursuing a PhD in Microsystems and Microelectronics (EDMI program) at EPFL. Education: B.Sc. in Biomedical Engineering, Politecnico di Torino (2019) M.Sc. in Biomedical Instrumentation, Politecnico di Torino (2022) Research Focus: Her work integrates electrochemical sensors, machine learning, and microsystems for therapeutic drug monitoring and biomedical diagnostics. Key areas include: (1) Multi-drug quantification using intelligent sensors for personalized cancer therapy, (2) Machine learning-driven optimization of electrochemical detection, (3) Microfluidic platforms for disease diagnosis (e.g., malaria), and (4) Wearable systems for neural prosthetics. Her research bridges biomedical engineering, electronics, and data science to advance precision medicine. Publication Trends: Recent articles (2022-2024) demonstrate strong emphasis on electrochemical sensors enhanced by machine learning for pharmaceutical monitoring, particularly in oncology. Secondary themes include microfluidic diagnostics, wearable medical devices, and environmental sensors. Over 85% of publications involve interdisciplinary collaborations, reflecting integration of engineering, computational methods, and clinical applications. Teaching & Leadership: Teaching Assistant for Bio-nano-chip design (EE-517) and MEMS practicals II (MICRO-503) EPFL team coach for international SensUs biotechnology competition

• Computational Linguistics
• Cognitive Science
• Machine Learning
• +3 more

Lena Jäger is a Professor in the Department of Computational Linguistics at the University of Zurich (UZH). Her research focuses on the intersection of linguistics, computational cognitive science, and machine learning, particularly analyzing cognitive mechanisms underlying human language processing through experimental psycholinguistics, computational modeling, and NLP methods. She holds an MA in Chinese Language and Culture, an MSc in Experimental and Clinical Linguistics, a PhD in Cognitive Science, and a BSc in Computer Science. Prior to UZH, she led a Machine Learning Junior Research Group funded by the German Federal Ministry of Education and Research (2020) and conducted postdoctoral research at the University of Potsdam. Her work emphasizes developing machine learning methods for analyzing eye-tracking data to uncover cognitive processes reflected in eye movements. Notable contributions include creating multilingual eye-tracking corpora (e.g., MultiplEYE, PoTeC) and advancing tools like pymovements for data processing. Her research spans applications in language comprehension, biometric identification, and clinical diagnostics (e.g., ADHD detection via eye movements). Education: BA/MA: Chinese Language and Culture (University of Freiburg, Tongji University, Beijing Language and Culture University, Université Paris 7) MSc: Experimental and Clinical Linguistics (University of Potsdam) PhD: Cognitive Science (University of Potsdam) BSc: Computer Science (concurrent with PhD) Awards: Machine Learning Junior Research Group Grant (2020). Labs/Teams: Leads computational linguistics and machine learning research groups at UZH, collaborating on projects like ScanDL and CoLAGaze. Her recent work bridges AI and cognitive science, exploring how language models emulate human reading behaviors and developing frameworks for ethical AI applications. Ongoing projects include improving fairness in biometric identification systems and analyzing individual differences in reading through synthetic data.

Rachid GuerraouiView profile

Professor

• Distributed Computing
• Concurrent Computing
• Byzantine Fault Tolerance
• +7 more

Rachid Guerraoui is a Full Professor at the École polytechnique fédérale de Lausanne (EPFL) where he leads the Distributed Computing Laboratory (DCL) within the School of Computer and Communication Sciences. He holds appointments in multiple departments including IC-SSC and IC-SIN for teaching, and serves on the IC Academic Evaluation Committee. A Moroccan/Swiss/French researcher, Guerraoui has previously been affiliated with Commissariat à l'Energie Atomique in Saclay, Hewlett-Packard Labs in Palo Alto, the Massachusetts Institute of Technology in Boston, and Collège de France in Paris. Guerraoui's research focuses on distributed and concurrent computing across various scales, from multiprocessors to wide-area networks. His work spans Byzantine fault tolerance, distributed machine learning, blockchain technologies, transactional memory, and consensus algorithms. His recent publications reveal a strong emphasis on Byzantine-resistant machine learning, decentralized learning systems, and the theoretical foundations of distributed consensus. The research demonstrates significant contributions to making distributed systems more robust, efficient, and secure against adversarial conditions. Guerraoui has received numerous prestigious awards including ACM Fellow (2012), Professor at College de France (2018), Nygaard-Dahl Award (2024), and Barroso Award (2025). His work has earned multiple best paper awards at top conferences including DISC, ICDCS, IPDPS, and ACM Middleware. He serves as Associate Editor of the Journal of the ACM (2010-2025) and has chaired program committees for major conferences such as PODC, DISC, and Middleware. As an educator, Guerraoui supervises numerous doctoral students and has mentored many successful researchers who now work at leading institutions and companies including Meta, Oracle Labs, Chainlink Labs, and Protocol Labs. He teaches courses on Distributed Algorithms and Concurrent Algorithms at EPFL, emphasizing both theoretical foundations and practical implementations. His educational initiatives include Wandida, a library of scientific e-synopses, and Zettabytes, projects aimed at making computer science accessible to broader audiences.

• Chemistry
• Chemical Engineering
• Artificial Intelligence in Chemistry
• +5 more

Daniel Paul Armstrong is a Doctoral Assistant at the Laboratory of Artificial Chemical Intelligence (LIAC) within the Institute of Chemical Sciences and Engineering (ISIC) at École polytechnique fédérale de Lausanne (EPFL). He is concurrently enrolled as a doctoral student in the Doctoral Program in Chemistry and Chemical Engineering (EDCH) at EPFL, indicating an active research and academic trajectory in the domain of chemistry and advanced materials. His academic training and research are situated within the School of Basic Sciences, focusing on the integration of artificial intelligence with chemical discovery and materials design. The interdisciplinary environment of LIAC suggests a strong emphasis on computational modeling, machine learning for molecular systems, and innovation in functional chemical materials. Although no publications authored by Daniel Paul Armstrong are listed in the provided data, the research output of the broader group includes significant contributions in organic semiconductors, perovskite materials, electrochemical transistors, and advanced polymer systems. These areas reflect the likely thematic context of his doctoral work, particularly at the intersection of AI-driven chemical design and electronic materials. No scientific awards or recognitions are mentioned in the available information. As a doctoral researcher, he is likely involved in collaborative projects, possibly advising or mentoring junior students indirectly, though no formal advisees are listed. There is no mention of independent grants, but he may be supported through institutional or group-level funding associated with the LIAC laboratory. The Laboratory of Artificial Chemical Intelligence (LIAC) serves as his primary research environment, promoting innovation in intelligent systems for chemical synthesis, materials optimization, and molecular engineering, aligning with EPFL’s leadership in interdisciplinary science and technology.

Valéry BezençonView profile

Professor

• Social Marketing
• Behavioral Change and Nudging
• Digital Consumer Behavior
• +3 more

Valéry Bezençon serves as an Ordinary Professor of Marketing at the University of Neuchâtel's Faculty of Economic Sciences, Institute of Management. He holds concurrent leadership roles including former dean and vice-dean of the faculty, director of the Institute of Management, and director of the Master of Science in International Business Development. Since 2017, he maintains a part-time academic position while conducting behavioral change consulting. His educational credentials include a PhD in Management from the University of Neuchâtel and a Master of Science from École Polytechnique Fédérale de Lausanne (EPFL). Prior to academia, he worked as a management consultant at McKinsey & Company. Bezençon's research centers on two interconnected domains: (1) social marketing and behavioral change (particularly nudging) applied to environmental, health, and well-being contexts; and (2) negative impacts of digital technologies on consumer vulnerability. His work examines how digital interfaces manipulate behavior through dark patterns while exploring solutions for consumer empowerment in data-driven environments. Recent publications reveal growing emphasis on social media's societal influence, AI ethics, and sustainable consumption paradoxes. Analysis of his 15 most recent publications (2022-2025) shows escalating focus on digital behavioral interventions, with 60% examining social media/AI impacts on consumer values and vulnerability. Key thematic clusters include digital nudging effectiveness (27%), consumer vulnerability frameworks (20%), and sustainable behavior consistency (13%), reflecting his dual expertise in behavioral science and digital consumer protection. No scientific awards or fellowships were documented in the source material. Bezençon directs the Certificate of Advanced Studies (CAS) in Social Marketing and Nudges while supervising doctoral students in the Health, Medicine, and Society program. His research is funded by three major Swiss National Science Foundation (SNSF) grants: FNS 100013_210123 (2023-2026): CHF 499,986 for pandemic communication analysis FNS CR00I5_235976 (2025-2029): CHF 842,080 for consumer empowerment against online dark patterns FNS 100013L_232040 (2026-2028): CHF 600,000 for digital platform consumer relationships He leads the Institute of Management and develops practical applications through continuous education programs on behavior change for well-being and productivity, bridging academic research with public policy implementation in behavioral insights.

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +6 more

Deniz Bayazit is a Doctoral Assistant at the Natural Language Processing Lab (NLP) within the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL). He is concurrently a doctoral student in the Doctoral Program in Computer and Communication Sciences (EDIC), part of the EDOC doctoral school at EPFL, indicating an active research and academic training role. His research interests are centered on Natural Language Processing and related areas in artificial intelligence and machine learning, aligning with the focus of his lab and department. These include computational linguistics, deep learning for language, text mining, speech processing, and information retrieval. No scientific awards or publications have been listed in the provided text. As a doctoral assistant, he is likely involved in research supervision and academic support, though no advisees are mentioned. He is based in office INR 218 at EPFL’s Station 14 campus in Lausanne, Switzerland.

Martin OderskyView profile

Professor

• Programming languages
• Object-oriented programming
• Functional programming
• +6 more

Martin Odersky is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences, where he heads the Programming Methods Laboratory (LAMP1). He maintains dual teaching appointments in the Systems and Software Engineering (SIN) and Software and Systems Engineering (SSC) sections. Education: Doctorate from ETH Zurich (1989) Odersky's research fundamentally explores the unification of object-oriented and functional programming paradigms. His work spans language design, type theory, compiler construction, and semantic foundations, driven by the thesis that these paradigms are complementary facets of a single computational model. This vision materialized in the Scala programming language, engineered for seamless Java/.NET interoperability while advancing type-safe abstractions for modern software development. His publication trajectory (1997-2005) reveals consistent innovation in bridging theoretical rigor with industrial applicability. Key themes include component-based modularity (Scalable Component Abstractions), dependent type systems for objects, and practical implementations of generics and functional constructs, all converging toward expressive yet safe programming models. Advising and Funding: Odersky has mentored 29 PhD students across his career, including 5 current candidates. His research sustains major funding from the Swiss National Science Foundation, European Commission, and Hasler Foundation, enabling foundational work in language design and implementation. Laboratory: He directs EPFL's Programming Methods Laboratory (LAMP), which drives Scala's evolution and investigates next-generation programming abstractions for concurrency, modularity, and type-driven development.

Angelika RomanouView profile

Research Fellow

• Distributed Information Systems
• Information Retrieval
• Data-Intensive Systems
• +4 more

Angelika Romanou is a Doctoral Assistant at the Distributed Information Systems Laboratory (LSIR) within the School of Computer and Communication Sciences (IC) at École polytechnique fédérale de Lausanne (EPFL). She is concurrently a PhD student in the Doctoral Program in Computer and Communication Sciences (EDIC), supported through her research assistantship. Her research focuses on distributed information systems, data-intensive computing, and information retrieval, with strong ties to web search technologies and scalable data processing. These interests align closely with the mission of LSIR, a leading lab in large-scale data and information systems. While no publications or scientific awards are listed in the current profile, her work is embedded in a high-impact research environment that emphasizes innovation in distributed systems and intelligent data access. Scientific Awards: No scientific awards listed. As a Doctoral Assistant, Angelika contributes to research projects within LSIR. She is not listed as an advisor to any students. Funding likely comes through EPFL and LSIR institutional support, though specific grants are not mentioned. She is actively involved in the LSIR (Distributed Information Systems Laboratory), a research group known for advancing scalable information systems, search engines, and machine learning for data science.

• Autonomous Driving
• Computer Vision
• Robotics
• +3 more

Markus Enzweiler serves as Professor of Computer Science and Autonomous Systems at Esslingen University of Applied Sciences within the Department of Computer Science and Engineering. He concurrently holds the leadership position of Director at the Institute for Intelligent Systems, where he oversees research initiatives focused on intelligent systems development for real-world autonomous applications. His research program centers on computer vision for autonomous systems , with specialized expertise in visual-inertial SLAM, collective perception, and neural rendering techniques. Key investigation areas include environmental robustness across agricultural and urban settings, real-time processing constraints for embedded systems, sensor fusion methodologies (particularly camera-radar integration), and the application of generative models for perception enhancement. His work consistently addresses practical implementation challenges such as computational efficiency and sensor calibration in unstructured environments. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) Advancement of lightweight perception systems through stixel-based representations and neural rendering; (2) Development of infrastructure-supported collective perception frameworks with datasets like CoopScenes and OPNV; and (3) Rigorous benchmarking of SLAM components in domain-specific contexts including agricultural robotics and multi-season navigation. His recent systematic review on LLM-based vulnerability detection also demonstrates expanding interest in software security for autonomous systems. As Director of the Institute for Intelligent Systems, Prof. Enzweiler leads a research ecosystem focused on translating theoretical advances into practical autonomous vehicle technologies. His team develops specialized datasets (Rover, OPNV) and software stacks for smart city environments, emphasizing the integration of novel perception approaches with vehicle dynamics modeling and real-time operational constraints.