Find Academic Supervisors

• Computer Security
• Formal Verification
• Networking Protocols
• +3 more

Dr. Christoph Sprenger is a Lecturer at the Department of Computer Science at ETH Zürich, specializing in formal verification of security protocols and networking systems. His work focuses on ensuring the correctness and security of distributed systems, databases, and network infrastructure through rigorous mathematical methods. His research addresses challenges such as verified isolation guarantees for database transactions, formal verification of router implementations, and secure data plane protocols in next-generation internet architectures. He has contributed to frameworks like IsaNet and N-Tube, emphasizing practical applications of formal methods in real-world systems. Key themes in his publications include protocol design, cryptographic security, and compositional verification techniques. Recent work explores the intersection of formal verification with path-aware networking and distributed system reliability. His research maintains a strong emphasis on bridging theoretical foundations with deployable solutions. Current projects involve advancing formal verification tools for critical infrastructure components, such as transactional memory managers and secure service architectures. His work consistently bridges gaps between abstract protocol specifications and their secure, interoperable implementations.

• Crystallography
• Organic Chemistry
• Inorganic Chemistry
• +3 more

Eduard Rusanov is a Senior Researcher at ETH Zurich's Department of Inorganic Functional Materials under Prof. Maxim Komalenko. He holds a PhD in Organoelement Chemistry from the National Academy of Science Ukraine (1997) and an M.S. in Chemistry from Taras Shevchenko National University of Kyiv (1993). His primary research focuses on small-molecule crystallography and inorganic materials synthesis. He concurrently serves as a part-time Visiting Professor at Taras Shevchenko University (2012–2022) and previously led the X-ray Single Crystal Diffraction Centre at the Institute of Organic Chemistry in Ukraine (2013–2022). His work spans over 330 publications, emphasizing structural chemistry and materials design, with applications in catalysis, medicinal chemistry, and nanotechnology. Key contributions include studies on heterocyclic compounds, quantum dot synthesis, and high-pressure crystal engineering. His research integrates experimental methods like X-ray diffraction with computational approaches (e.g., DFT), advancing understanding of molecular structures and their functional properties. His academic trajectory includes postdoctoral roles at York University, the University of Neuchâtel, and Martin-Luther-University Halle-Wittenberg, where he specialized in crystallography and quantum chemistry. His expertise bridges organic/inorganic chemistry with advanced materials development. Awards and grants are not explicitly listed, but his extensive publication record (3,851 citations, H-index 33) underscores his significant scholarly impact.

• Parallel Computing
• Java Virtual Machine (JVM) Optimization
• Performance Profiling
• +5 more

Walter Binder is a Full Professor in the Faculty of Informatics at the Università della Svizzera italiana (USI). He holds a MSc, PhD, and venia docendi from Vienna University of Technology. Previously, he was a senior researcher at the Artificial Intelligence Laboratory, EPFL. His research focuses on program transformations, virtual execution environments, aspect-oriented programming, profiling, and resource management. Education: MSc from Vienna University of Technology PhD from Vienna University of Technology Venia docendi (Habilitation) from Vienna University of Technology Research Interests: His work spans JVM optimization, parallel computing, and dynamic program analysis. Notable contributions include tools like Renaissance (a JVM benchmark suite), S2S (SQL-to-Stream translator), and Akkaprof (profiler for actor-based systems). He explores topics such as thread management, vectorization, and performance profiling in distributed systems. Articles Trends: Recent work emphasizes JVM performance (e.g., Java Vector API, Native Image optimizations), parallel execution policies (NAS benchmarks), and adaptive runtime systems (e.g., MPR framework). He also investigates big data systems (Spark, Node.js) and runtime verification tools. Grants & Labs: Leads projects on JVM profiling, polyglot runtimes, and large-scale program analysis. His lab develops tools like NodeMOP for Node.js and AccStream for stream processing systems.

• Cybersecurity
• Secure Software Development
• Concurrent programming
• +3 more

Associate Professor Michael Mäder at Haute école d'ingénierie et d'architecture de Fribourg holds a position within the iSIS Institute (Institut des systèmes intelligents et sécurisés). He teaches in the BSc HES-SO in Computer Science and MSc HES-SO in Engineering programs, focusing on Distributed Programming, Cybersecurity, and Secure Software Development. His research emphasizes vehicular cybersecurity, DevSecOps practices, and enterprise IT security frameworks. Recent work includes a 2024 study on secure connected mobility infrastructure, a 2019 analysis of DevSecOps training methodologies, and a 2015 contribution to IT security maturity models. No scientific awards are listed in the provided materials. He advises students in computer science and engineering disciplines from his office at HEIA_C10.09, and his work contributes to both academic programs and industry partnerships through the iSIS research institute.

Alena MiftakhovaView profile

Lecturer

• Environmental Economics
• Climate Change Economics
• Energy Economics
• +3 more

Dr. Alena Miftakhova serves as a Lecturer in the Department of Management, Technology, and Economics at ETH Zurich, Switzerland, and concurrently holds a Postdoctoral Researcher position at the Center for Economic Research since 2019. Her work bridges economic theory with climate policy analysis, focusing on computational approaches to energy systems and climate change mitigation strategies. Her educational background includes: Ph.D. in Business Administration (Economics of Climate Change) from the University of Zurich (2014-2019), supervised by Karl Schmedders M.A. in Management and Economics from the University of Zurich (2011-2014) B.A. in Economics from Saint-Petersburg State University of Engineering and Economics, Russia (2004-2009) Dr. Miftakhova's research centers on the economics of climate change, with specialized expertise in integrated assessment modeling and computable general equilibrium frameworks. She employs advanced sensitivity analysis techniques to identify critical parameters in complex climate-economy systems, addressing fundamental questions about energy transitions, policy effectiveness, and economic impacts of climate change. Her methodological rigor combines econometric precision with computational innovation to model high-dimensional climate systems. Her publication record (2020-2024) reveals a cohesive research trajectory focused on climate policy design through quantitative modeling. Key contributions examine energy substitution dynamics between clean and dirty fuels, optimal climate policy formulation under uncertainty, and statistical methods for simplifying complex climate models. This body of work consistently applies computational economics to environmental challenges, demonstrating increasing sophistication in handling model complexity and policy relevance. No scientific awards or fellowships are documented in the available information. There is no public information regarding doctoral students supervised or research grants secured by Dr. Miftakhova. As part of ETH Zurich's Center for Economic Research, she collaborates within interdisciplinary teams focused on climate economics and energy systems modeling. Her work contributes to the Department of Management, Technology and Economics' strategic initiatives in sustainable development, particularly through computational approaches to policy analysis and economic forecasting in climate-vulnerable sectors.

Ilia LykovView profile

Researcher

• Nanophotonics
• Optics
• Metrology
• +3 more

Ilia Lykov is a Doctoral Assistant at the Nanophotonics and Metrology Laboratory (NAM) within the School of Engineering (STI) at EPFL. He is concurrently enrolled in the Doctoral Program in Photonics under the École Doctorale de Physique (EDPO). His research focuses on advanced photonics technologies including quantum sensing, optical metrology, and laser stabilization. Lykov is affiliated with the Institute of Microengineering (IEM) and contributes to cutting-edge experimental studies in nanophotonics. His work integrates interdisciplinary approaches such as AI-driven imaging techniques and precision sensor development. No scientific awards or grants are explicitly mentioned in the provided materials.

• Machine Learning
• Adversarial Machine Learning
• Computer Vision
• +4 more

Elias Abad Rocamora is a Researcher and Doctoral Assistant at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Laboratory for Information and Inference Systems (LIONS) under the Institute of Electrical Engineering (IEM) within the School of Engineering (STI) . He is concurrently pursuing a Doctoral Program in Electrical Engineering through EPFL's Doctoral School of Engineering (EDoc-EDEE). His research focuses on adversarial machine learning, robustness certification, and efficient neural network architectures. Key areas include adversarial attacks against vision-language models, certified defenses under bounded perturbations, and regularization techniques to prevent catastrophic overfitting. His work also extends to 3D pointcloud processing using graph-based methods and formal verification of polynomial networks. Rocamora has contributed to cutting-edge research in AI safety, language model security, and geometric deep learning. His recent work emphasizes dual-domain robustness in multimodal models and efficient single-pass detection mechanisms for LLM jailbreaking inputs. Articles span cybersecurity applications, optimization strategies, and foundational aspects of model robustness. No scientific awards are currently listed. He collaborates actively within the LIONS lab, focusing on interdisciplinary projects at the intersection of electrical engineering and computer science.

• Computational Biology
• Medical Physics
• Oncology
• +5 more

Mathias Weyland is a researcher at the Zurich University of Applied Sciences (ZHAW) School of Engineering, specializing in the Applied Complex Systems Science research focus. His work bridges computational modeling, medical physics, and oncology through interdisciplinary projects. Projects : Deputy project leader for Bio-HhOST (bio-hybrid tissue models), PHARAO (pandemic response), and SARS-CoV2 Intervention Modeling , among others. Research Interests : He focuses on computational biology, medical physics, and hyperthermia applications in cancer therapy. His work includes: 3D tissue engineering with live/artificial cell integration Thermoradiation synergy in veterinary oncology Artificial life and droplet-based programmable chemistries Radiation dose optimization for diagnostic imaging Mathematical modeling of biological repair dynamics Publication Trends : His recent work (2024-2020) spans CT scan optimization, thermoradiation effects, and droplet-based artificial life systems. Collaborative projects with institutions like MIT Press, Springer, and Springer Nature dominate his publication record. Methodology : Combines phantom studies, Monte Carlo simulations, and RNA sequencing with a strong emphasis on computational modeling for medical applications.

• Theoretical Computer Science
• Algorithms
• Computational Complexity
• +3 more

Davide Mazzali is a Doctoral Assistant at the Theory of Computation Laboratory (THL2 and THL4) within the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL). He is concurrently enrolled in the Doctoral Program in Computer and Communication Sciences (EDIC), reflecting his dual role as a researcher and PhD candidate. His research is centered in theoretical computer science, with a focus on foundational aspects of computation. Key areas include: Theory of computation Algorithms and complexity Automata and formal languages Mathematical logic in computing Given his affiliation with the Theory of Computation Laboratory, his work likely involves rigorous mathematical modeling of computational processes and systems. No scientific awards or publications are listed in the available data. However, his position suggests active engagement in high-level research within one of Europe's leading technical universities. He advises no students at this stage, as per current records. His work is supported through his doctoral assistantship at EPFL, which typically includes research and teaching responsibilities. He is based at office INJ 110 on the EPFL campus and is an integral member of the THL2 and THL4 research groups, contributing to the vibrant academic and research environment in theoretical computer science.

• Machine Learning
• Quantum Chemistry
• Electronic Structure Theory
• +4 more

Joseph William Abbott serves as a Doctoral Assistant at École Polytechnique Fédérale de Lausanne (EPFL) within the Laboratory of Computational Science and Modelling (COSMO) under the Institute of Materials in the School of Engineering. He joined EPFL in October 2022 and is concurrently enrolled in the Doctoral Program in Chemistry and Chemical Engineering. Abbott earned his MSci Master's degree in Chemistry from the University of Bristol (2016-2020), including a study-abroad year at the University of Washington where he researched noble gas-doped nanodiamonds under Xiaosong Li. His undergraduate work also included a summer position at STFC neutron facilities near Oxford developing scientific software for neutron scattering data analysis, followed by a Master's thesis on quantum dynamics of photosynthetic energy transfer with Fred Manby at Bristol. His research focuses on machine learning applications for electron density modeling using physics-inspired molecular representations, spanning quantum chemistry, electronic structure theory, molecular dynamics, and battery simulation. Abbott emphasizes open-source scientific software development, with industrial experience from a year-long algorithm development role at BIOVIA (Dassault Systèmes) in Cambridge focused on solid electrolyte interphase growth modeling for lithium-ion batteries. As part of COSMO laboratory operations, Abbott contributes to computational science infrastructure while advancing his doctoral work at the intersection of quantum mechanics and machine learning. His technical profile includes active presence on GitHub, ORCID, and Google Scholar, with research outputs centered on atomistic modeling methodologies.

• Statistical Physics
• Machine Learning
• Discrete Optimisation
• +3 more

Vittorio Erba is a Lecturer at the Department of Physics within the School of Basic Sciences at École Polytechnique Fédérale de Lausanne (EPFL), with concurrent Scientist appointments across three laboratories: Statistical Physics of Computation Laboratory (SPOC1/SPOC2) and Information, Learning & Physics Laboratory (IDEPHICS2). His research integrates statistical physics methodologies with computational challenges, focusing on disordered systems applied to: Machine learning optimization Graph theory analysis Statistical inference frameworks Discrete computational problem-solving He teaches the graduate course 'Statistical physics of computation', training students in applying physics-derived tools to computational and statistical problems. Laboratory affiliations span both the School of Basic Sciences (IPHYS institute) and School of Computer and Communication Sciences (IINFCOM institute), reflecting interdisciplinary work at the physics-computation interface. Contact details remain active with office BSP 514 at Cubotron UNIL, Lausanne.

Denis RibeaudView profile

Researcher

• Criminology
• Developmental Psychology
• Sociology of Violence
• +5 more

Denis Ribeaud serves as Senior Research Associate and Co-Project Director of the Zurich Project on the Social Development from Childhood to Adulthood (z-proso) at the University of Zurich's Faculty of Arts and Social Sciences. Since 2006, he has directed the Zurich Youth Surveys (ZYS), which track youth violence trends in Zurich canton using representative student samples. The z-proso project, ongoing since 2003 with over 1,300 participants, examines longitudinal development of violence and problem behaviors through repeated surveys. His educational background includes: Sociology and Social Psychology studies at the University of Zurich PhD in Criminology from the University of Lausanne, where he worked at the Criminological Institute for several years Ribeaud's research focuses on criminology and developmental psychology, specifically investigating how peer victimization, parenting behaviors, socio-emotional skills, and harsh environments influence violence perpetration, mental health, and substance use across adolescence. His work integrates biological measures (e.g., hair cortisol analysis), ecological momentary assessment, and advanced statistical modeling to map causal pathways in youth development. Key specialties include longitudinal cohort design, transdiagnostic mental health analysis, and validation of behavioral instruments. Recent publications reveal heavy emphasis on multi-method approaches combining biological data with psychological assessments. He explores gene expression changes from victimization, hormonal correlates of aggression, and machine learning applications in EMA data, while consistently addressing Zurich-specific youth cohorts. His articles highlight Switzerland-focused violence research, substance use patterns in immigrant vs. native adolescents, and pandemic impacts on young adult coping mechanisms. No scientific awards were documented in the provided materials. Ribeaud's project leadership implies grant management and student supervision, though specific advisees or funding details are absent. His z-proso role involves coordinating cross-disciplinary teams across 13+ years of data collection, suggesting substantial advisory responsibilities in research design and execution. He directs the z-proso project and Zurich Youth Surveys (ZYS), major longitudinal initiatives based at the University of Zurich. These projects maintain archives of data collections from 2004-2022 and employ interdisciplinary teams for analyzing youth violence, mental health, and social decision-making through combined survey and biomarker approaches.

• Biostatistics
• Statistical Modeling
• Mathematical Statistics
• +3 more

Gellért Géza Perényi serves as a Doctoral Assistant at the Chair of Biostatistics within the Department of Mathematics, School of Basic Sciences at the Swiss Federal Institute of Technology Lausanne (EPFL). Concurrently, he is enrolled as a doctoral student in EPFL's Mathematics Doctoral Program (EDMA), maintaining active academic status through both research and study roles. His research centers on biostatistical methodology development for biological and medical applications, emphasizing mathematical rigor in statistical inference. Key focus areas include high-dimensional data analysis, probabilistic modeling of biological systems, and computational techniques for genomic datasets. This work bridges theoretical statistics with practical healthcare challenges, particularly in epidemiological study design and clinical trial analytics. Perényi operates within EPFL's Biostatistics research ecosystem, contributing to the Chair's mission of advancing statistical theory for life sciences. The group maintains strong collaborative ties with medical institutions and participates in interdisciplinary projects spanning public health surveillance, personalized medicine, and biomarker discovery initiatives across European research networks.

Sven HelmerView profile

Professor

• Database Systems
• Big Data Analytics
• Semantic Computing
• +2 more

Prof. Dr. Sven Helmer is a Professor in the Department of Informatics at the University of Zurich. Previously held positions include Associate Professor at the Free University of Bozen-Bolzano and Senior Lecturer at Birkbeck, University of London. He obtained his PhD from the University of Mannheim. Research Focus: Database technology, big data analytics, query optimization, and distributed systems. Key interests include scalable indexing, time series analysis, and semantic computing. Recent Publications: Work spans query optimization, graph data structures, and educational methodologies in data science. Dominant themes include scalability in database systems and algorithmic innovations for dynamic data. Awards: Distinguished Reviewer Award, ICDE'20 Best Paper Award, ADBIS'17 Best Teacher Award 2013 Contact: Binzmühlestrasse 14, CH-8050 Zürich. Office BIN 2.E.09. Email: helmer@ifi.uzh.ch. Phone: +41 44 635 67 28.

Michal FriedmanView profile

Assistant Professor

• Systems
• Concurrent Computing
• Programming Languages
• +3 more

Michal Friedman is an Assistant Professor at the Department of Computer Science, ETH Zurich, specializing in systems, concurrent computing, programming languages, and sustainable computing. He leads research on designing system fundamentals across software and hardware to enhance performance and efficiency in next-generation computing platforms. Prior to ETH, he completed a postdoc at the same institution and earned his Ph.D. from the Technion under Prof. Erez Petrank, focusing on concurrent data structures for non-volatile memories. Education: Ph.D. in Computer Science (Technion, advised by Erez Petrank), BSc Summa Cum Laude (Technion). Awards include the Eric and Wendy Schmidt Postdoctoral Award (2022), Blavatnik Prize (2021), and Azrieli Fellowship (2018–2021). His work spans persistent memory systems, concurrent algorithms, and energy-efficient computing. Key contributions include PCcheck (ML checkpointing), Dirigent (serverless orchestration), and foundational research on non-volatile memory correctness conditions. He has authored over 15 papers in top conferences like ASPLOS, SOSP, and VLDB, and serves on program committees for systems and programming languages venues.