جستجوی استاد راهنمای دانشگاهی

Sankalp Gambhirمشاهده پروفایل

پژوهشگر

• Program Verification
• Proof Assistants
• Formal Logic
• +۷ مورد دیگر

Sankalp Gambhir is a Doctoral Assistant at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Laboratory for Automated Reasoning and Analysis (LARA) in the School of Computer and Communication Sciences (IC). He is pursuing his doctoral degree in Computer and Communication Sciences under the supervision of Prof. Viktor Kunčak. His role is both academic and research-oriented, contributing to foundational work in formal methods and verification. Education: Bachelor of Engineering in Engineering Physics, Indian Institute of Technology, Bombay Doctoral Program in Computer and Communication Sciences, EPFL (ongoing) His research centers on proof assistants and program verification , with a strong interest in related areas such as logic, program synthesis, and formal reasoning. He is actively developing and working with the LISA proof assistant, aiming to enhance the reliability and correctness of software through rigorous mathematical foundations. His work sits at the intersection of theoretical computer science and practical software engineering. Sankalp has a background in quantum information theory from his undergraduate thesis, indicating interdisciplinary depth. While no publications are listed in the provided text, his research trajectory suggests a focus on foundational tools for ensuring software correctness and advancing automated reasoning systems. Scientific Awards: He advises no students as per current information and there is no mention of grants or funding. However, as a doctoral assistant at EPFL, he is likely supported through institutional or project-based funding related to LARA’s research initiatives. Labs and Teams: He is an active member of the Laboratory for Automated Reasoning and Analysis (LARA) at EPFL, a research group dedicated to developing tools and theories for software correctness, verification, and synthesis. The lab focuses on building practical systems grounded in formal logic and programming language theory.

Tao Lyuمشاهده پروفایل

پژوهشگر

• Computer Science
• Systems Software
• Distributed Systems
• +۳ مورد دیگر

Tao Lyu serves as a Doctoral Assistant at the Robust Scalable Systems Software Lab (RS3LAB) within the Institute of Computer Science, School of Computer and Communication Sciences at the Swiss Federal Institute of Technology Lausanne (EPFL). His research concentrates on core systems software challenges, with specific expertise in scalable architectures, fault-tolerant design, and distributed computing frameworks. He investigates methodologies to enhance software reliability while maintaining performance at scale, addressing critical gaps in modern infrastructure resilience. As an active member of RS3LAB, he contributes to the group's mission of developing next-generation systems software solutions through rigorous theoretical analysis and practical implementation.

Alexandre Pinazzaمشاهده پروفایل

دانشگاهی

• Formal Verification
• Hardware-Software Co-Verification
• Computer Architecture
• +۴ مورد دیگر

Alexandre Pinazza is a Doctoral Assistant at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with both the Systems and Formalisms Lab (SYSTEMF) and the Verification and Computer Architecture Lab (VCA) within the School of Computer and Communication Sciences (IC). He is also a PhD candidate enrolled in the Doctoral Program in Computer and Communication Sciences (EDIC), reflecting his dual role as both a researcher and a doctoral student. His research centers on linking verification proofs across hardware and software components , aiming to enhance system correctness and reliability. This work lies at the intersection of formal methods, computer architecture, and systems engineering. His involvement in two prominent labs indicates a multidisciplinary approach, combining theoretical formalisms with practical architectural verification. Alexandre has not yet published articles listed in the provided text, so no trends can be inferred at this stage. However, his focus suggests future contributions in formal verification frameworks and integrated proof systems. Affiliation: Systems and Formalisms Lab (SYSTEMF), EPFL Affiliation: Verification and Computer Architecture Lab (VCA), EPFL Program: Doctoral Program in Computer and Communication Sciences (EDIC) He has not received any scientific awards mentioned in the text. He does not supervise any students listed. Alexandre is actively engaged in research and has no noted grants or advising roles at this time. He is part of two advanced research groups: the Systems and Formalisms Lab , which focuses on rigorous modeling and verification techniques, and the Verification and Computer Architecture Lab , which bridges low-level hardware design with high-assurance software verification. These labs provide a strong foundation for his interdisciplinary work.

Viktor Kuncakمشاهده پروفایل

دانشیار

• Formal Verification
• Theorem Proving
• Program Synthesis
• +۶ مورد دیگر

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.

Karl Reiner Lermerمشاهده پروفایل

پژوهشگر

• Safety-Critical Systems
• Software Engineering
• Systems Engineering
• +۱ مورد دیگر

Dr. Karl Reiner Lermer is a researcher at the Zurich University of Applied Sciences, affiliated with the School of Engineering. His work focuses on safety-critical systems and software reliability, with significant contributions to formal accident analysis and dynamic flowgraph modeling. His research projects include: Formal Analysis of Accidents Application of STPA (Systems-Theoretic Process Analysis) to digital control and reactor protection technology Software reliability and Dynamic Flowgraph Modeling These projects highlight his expertise in ensuring safety and robustness in complex technical systems.

Rishabh Iyerمشاهده پروفایل

استادیار

• Computer Systems
• Performance Analysis and Optimization
• Operating Systems
• +۵ مورد دیگر

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.

• Robotics
• Industry 4.0
• Predictive Maintenance
• +۵ مورد دیگر

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.

Bruno Sudretمشاهده پروفایل

استاد

• Uncertainty Quantification
• Reliability Analysis
• Sensitivity Analysis
• +۳ مورد دیگر

Prof. Bruno Sudret is a Full Professor of Risk, Safety, and Uncertainty Quantification at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. His research focuses on computational methods for uncertainty quantification, reliability analysis, and Bayesian approaches for model calibration. He has contributed to the development of the UQLab software framework and the UQWorld community platform. Before joining ETH Zurich in 2012, Sudret held roles at the University of Berkeley (postdoc), EDF R&D (researcher and group head), and Phimeca Engineering (Director of Research and Strategy). Education: Master's in Science from Ecole Polytechnique (1993), Master's and PhD in Civil Engineering from Ecole Nationale des Ponts et Chaussées (1996, 1999). His work emphasizes stochastic simulators, surrogate modeling, and reliability-based design optimization. He serves on editorial boards for journals like Reliability Engineering and Systems Safety and Structural Safety .

Lena A. Jägerمشاهده پروفایل

دانشیار

• Computational Linguistics
• Eye Tracking
• Machine Learning
• +۵ مورد دیگر

Lena A. Jäger is an Associate Professor in Digital Linguistics at the School for Transdisciplinary Studies, University of Potsdam. Her research focuses on computational linguistics, eye tracking, and machine learning applications in language processing. She leads the Digital Linguistics group, supervising 11 PhD students and contributing to interdisciplinary projects like the MultiplEYE corpus initiative. Her work bridges cognitive science and AI, with key contributions to eye movement analysis, biometric identification, and LLM interpretability. Her research interests span eye tracking in reading, linguistic predictability modeling, and the alignment of language models with human cognition. Notable achievements include developing the pymovements toolkit for eye movement data processing and pioneering studies on detecting alcohol inebriation via gaze analysis. Awards include best paper honors at ETRA 2023 and 2024. Recent work explores generative models (ScanDL) for synthetic eye movement generation, cross-lingual reading behavior analysis, and fairness in biometric systems. She advises on AI ethics through the DSI initiative and collaborates internationally on projects like the MECO corpus.

Laurent Donzéمشاهده پروفایل

استاد

• Applied Statistics
• Econometrics
• Survey Methodology
• +۷ مورد دیگر

Laurent Donzé is a Professor of Applied Statistics and Modelling at the Department of Informatics, Faculty of Economics and Social Sciences, University of Fribourg. He is also a Research Professor at KOF ETH Zurich and a Professor of Econometrics at the University of Neuchâtel. He leads the ASAM research group and has extensive experience in teaching mathematics, econometrics, and statistics. His educational background includes a Ph.D. in Econometrics from the University of Fribourg, followed by research roles at IRE and KOF ETH Zurich. His academic journey reflects deep engagement with statistical methodology and applied economic research. Donzé's primary research interests lie in applied statistics, particularly survey methodology, fuzzy statistics, imputation, causal inference, matching techniques, and wage discrimination analysis . He has made significant contributions to the development and application of fuzzy statistical tools, especially in defuzzification and fuzzy regression. His recent publications (2019–2025) demonstrate a consistent focus on fuzzy confidence intervals, fuzzy p-values, fuzzy ANOVA, and fuzzy regression models , often applied to real-world datasets like SHARE and Swiss SILC. These works emphasize robust statistical inference under uncertainty and contribute to both theoretical and applied advancements in fuzzy statistics. Among his scientific recognitions is the Best Student Paper Award at IJJCI 2020 . He has also edited special issues and contributed to leading journals and conferences in computational intelligence and fuzzy systems. Donzé has been involved in numerous research and teaching initiatives, including grants from the Swiss National Science Foundation, mentoring at the Swiss Study Foundation, and leadership in statistical societies. He has supervised research projects and collaborated with institutions such as Nestlé, the Swiss Federal Statistical Office, and pharmaSuisse. He is actively involved in academic and professional communities, serving as president of the Education and Research section of the Swiss Statistical Society and contributing to the development of statistical infrastructure in social sciences.

• Artificial Intelligence
• Semantic AI
• Decentralised Systems
• +۴ مورد دیگر

Prof. Giovanna Di Marzo Serugendo serves as Professor at the Geneva School of Social Sciences, University of Geneva since 2010 and Director of the Computer Science Center since 2016. Her career includes prior roles as Lecturer in the UK (5 years) and researcher at CERN (2 years), following her 1999 Ph.D. in Software Engineering from EPFL. Educational background: Ph.D. in Software Engineering, Swiss Federal Institute of Technology Lausanne (EPFL), 1999 Her research pioneers Semantic AI and engineering of decentralised software systems exhibiting self-organising and emergent behaviour . She bridges natural system studies with artificial collective system design, emphasizing reliability verification and trustworthiness in complex adaptive architectures across computing and social sciences domains. Key recognition: Nominated among Switzerland's 100 digital shapers (2018) She co-founded the IEEE International Conference on Self-Adaptive and Self-Organising Systems (SASO) and ACM Transactions on Autonomous Adaptive Systems (TAAS), serving as TAAS Editor-in-Chief (2005-2011). Current leadership includes the University of Geneva's Digital Innovation Hub (established 2019), fostering academic-industry collaboration for innovative service development.

• Wireless Communication
• Mobile Networks
• Wireless IoT Applications
• +۶ مورد دیگر

Prof. Dr. Luciano Sarperi is a Lecturer at the ZHAW School of Engineering ’s Institute of Signal Processing and Wireless Communications , focusing on applied R&D with industry partners. His work spans Wireless Communication Systems , Mobile Networks (NR, LTE, NB-IoT), and Software Defined Radio . Expertise in GNSS Localization , Wireless Time-Synchronization , and Interference Cancellation for MIMO systems. Active in UAV navigation, RFI detection, and LoRa/Wi-Fi applications. Research Trends (2025–2004): Peer-reviewed work on MIMO Pre-coding , GNSS for Drones , Blind Signal Processing , and Wireless Standards . Patents in Multi-Cell MIMO and Channel Feedback . Education : PhD in Digital Signal Processing for MIMO-OFDM from the University of Liverpool (2007), M.Sc. in Microelectronic Systems and Telecommunications (2002). Experience : 2010–2017 at Swisscom (Research Engineer), 2007–2010 at Fujitsu Laboratories (U.K.).