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اطلاعات پروفایل‌ها از صفحات عمومی دانشگاه‌ها گرفته شده و ممکن است به‌روز نباشد.

Elliott Ashمشاهده پروفایل

دانشیار

ETH ZurichSwitzerland

Elliott Ash is an Associate Professor of Law, Economics, and Data Science at ETH Zurich's Center for Law & Economics. He holds a Ph.D. in Economics and J.D. from Columbia University, a B.A. in Economics, Government, and Philosophy from the University of Texas at Austin, and an LL.M. in International Criminal Law from the University of Amsterdam. His research focuses on empirical legal studies using econometrics, NLP, and ML, examining topics like judicial behavior, legislative impact, and AI-driven governance. He has been funded by the ERC, Swiss NSF, and others. Research Interests: Elliott explores automation of legal decisions, text-as-data analysis in law, and the intersection of AI with legal systems. He develops tools like BallotBot and LePaRD to enhance legal transparency and public understanding. His work bridges law, economics, and computer science, with publications in top journals like the American Economic Journal and Review of Economics and Statistics . Teaching: Courses include Building a Robot Judge , Natural Language Processing for Law , and Big Data for Public Policy . He co-organizes the Zurich Workshop in AI+Economics and Monash-Warwick-Zurich Text-as-Data Workshops. Awards: European Research Council Starting Grant, Swiss National Science Foundation Grant, and multiple grants from U.S. and Swiss institutions. His work has been featured in NPR , VoxEU , and Georgetown Law Journal . Labs/Teams: Leads the Swiss AI Initiative's Human-AI Alignment team, collaborates with the CEPR on Political Economy research, and serves as an Economic Journal Associate Editor.

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Sidi Wuمشاهده پروفایل

پژوهشگر

ETH ZurichSwitzerland

Sidi Wu is a Researcher affiliated with ETH Zürich's Institute of Cartography and Geoinformatics. Their primary role is as Staff of the Professorship for Cartography, contributing to academic research and technical operations within the department. They are based at HIL G 23.2, Stefano-Franscini-Platz 5 in Zürich, Switzerland, and can be reached at sidiwu@ethz.ch. Research interests center on advancing AI-driven cartographic methods, historical map analysis, and environmental spatial dynamics. Specific focuses include generative AI applications in map-making, semantic segmentation of historical documents, and leveraging digitized maps for ecosystem studies. They also explore steganography in image translation and cross-domain adaptation techniques for geospatial data. Recent work emphasizes innovations in automated map storytelling systems, spatio-temporal context modeling using transformers, and weakly supervised learning approaches for map segmentation. Their studies frequently bridge cartography with environmental science disciplines like hydrology and urban morphology. No scientific awards or grants are explicitly listed in the provided information. While no advisees are documented here, their research collaborations likely involve student contributions. They are part of the core team at the Institute of Cartography and Geoinformatics, contributing to cutting-edge projects in geomatics and computational cartography.

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Nick Chaterمشاهده پروفایل

استاد

Swiss Federal Institute of Technology in LausanneSwitzerland

Professor Nick Chater is a leading figure in the field of Behavioural Science, affiliated with the University of Warwick at Warwick Business School since 2010. He has held previous chairs in psychology at Warwick and UCL. His research spans cognitive and social foundations of rationality, with applications to business and public policy, and he has authored over 200 papers and six books. He is a fellow of the British Academy, Cognitive Science Society, and Association for Psychological Science. His research interests include cognitive science, behavioral economics, decision making, and computational psychology, with a focus on reasoning, language, and mathematical modeling of mental processes. He has been recognized with prestigious awards such as the Spearman Medal, Experimental Psychology Society Prize, and the David E Rumelhart Prize for lifetime achievement in cognitive science. His work extends to practical applications through co-founding Decision Technology and advising the UK government's Climate Change Committee and the Behavioural Insight Team. Recent publications highlight his interdisciplinary approach, bridging economics, cognitive science, computational modeling, and behavioral public policy. Topics include thermal macroeconomic theory, Bayesian sampling, paradoxes in cognition, and language emergence via social interaction. These works emphasize probability judgments, moral cognition, and computational limitations in human inference. British Psychological Society's Spearman Medal (1996) Experimental Psychology Society Prize (1997) David E Rumelhart Prize (2023) PROSE Award (2019) Chater's academic contributions include collaborations with researchers like Adam N. Sanborn, Hossam Zeitoun, and Morten H. Christiansen, focusing on Bayesian inference, behavioral public policy, and cognitive modeling. He has also been a resident scientist on BBC Radio 4's The Human Zoo.

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Adam B. Badawiمشاهده پروفایل

استاد

University of ZurichSwitzerland

Adam B. Badawi is a Professor of Law at the University of California, Berkeley - School of Law, where he maintains an active research agenda at the intersection of law, finance, and corporate governance. His scholarly work has established him as a leading expert in contract law, M&A transactions, securities litigation, and ESG compliance. Professor Badawi's research interests span multiple dimensions of corporate law and legal theory. His work on contractual complexity, particularly in debt agreements and M&A transactions, has provided significant insights into how legal drafting affects economic outcomes. He has extensively examined the business judgment rule, board authority, and the role of courts in corporate governance. More recently, his research has expanded into ESG-related topics, analyzing how environmental, social, and governance considerations intersect with traditional corporate law frameworks. His methodological approach often combines legal analysis with empirical techniques, including text analysis of legal documents and event studies of litigation outcomes. Professor Badawi's scholarly output demonstrates consistent high-impact research across multiple domains of corporate law. His early work focused on foundational aspects of contract theory and interpretation, while his more recent publications reflect growing interest in ESG metrics, executive compensation structures tied to sustainability goals, and the evolving regulatory landscape. The trajectory of his research shows a progression from theoretical legal analysis toward increasingly empirical and interdisciplinary approaches that bridge law with finance and data science. Professor Badawi has collaborated with numerous scholars across different institutions, including Duke University, Stanford Law School, and the University of Chicago Law School, reflecting the interdisciplinary nature of his work and its relevance to multiple academic communities.

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Frédéric Kaplanمشاهده پروفایل

دانشیار

Swiss Federal Institute of Technology in LausanneSwitzerland

Frédéric Kaplan serves as Director of the College of Humanities at École Polytechnique Fédérale de Lausanne (EPFL), where he holds the Chair of Digital Humanities. He also serves as President of the Time Machine Organisation, a nonprofit entity comprising over 600 institutions. His academic appointments span multiple departments including the Digital Humanities Laboratory (DHLAB), School of Architecture (SAR), and School of Humanities (SODH), demonstrating his interdisciplinary leadership across EPFL's academic structure. Dr. Kaplan's research focuses on the intersection of computational methods and humanities, particularly in historical urban analysis, cultural heritage digitization, and the development of the Mirror World concept. His work bridges computational techniques with historical scholarship, creating new methodologies for analyzing historical documents, maps, and urban structures through advanced digital tools. His research has significant implications for how we understand and reconstruct historical urban environments and cultural heritage. His publication record reveals a strong emphasis on computational approaches to historical data, with recent work focusing on LLM applications for historical cadastre navigation, historical map analysis through deformation patterns, 4D city modeling, and language technology applications for historical document processing. This research trajectory demonstrates an evolving focus from basic digitization toward sophisticated analytical frameworks that extract deeper historical insights from digital representations. Kaplan has supervised numerous doctoral students whose work spans digital heritage applications, historical document analysis, computational cartography, and language technology. His research has been supported through multiple institutional frameworks at EPFL and has resulted in practical applications demonstrated through exhibitions at major institutions including the Venice Architecture Biennale, Grand Palais, Centre Pompidou in Paris, and the Museum of Modern Art in New York. He leads the Digital Humanities Laboratory (DHLAB) which serves as a nexus for computational approaches to humanities research. The lab focuses on developing methodologies for historical data analysis, creating digital tools for cultural heritage institutions, and exploring the theoretical implications of computational approaches to historical scholarship. The lab's work with the Time Machine Organisation represents one of the most ambitious efforts to create comprehensive digital reconstructions of historical urban environments.

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Thomas Demeesterمشاهده پروفایل

دانشیار

Swiss Federal Institute of Technology in LausanneSwitzerland

Thomas Demeester is an Associate Professor at the Internet Technology and Data Science Lab (IDLab), Ghent University - imec, Belgium. Appointed as Assistant Professor in 2019, he leads an AI research group focused on health applications and drug design, co-directing the Text-to-Knowledge research cluster with Prof. Chris Develder. His educational background includes: M.Sc. in Electrical Engineering from Ghent University (2005), completed with thesis work at ETH Zurich Ph.D. in Computational Electromagnetics from Ghent University (2009), funded by Research Foundation - Flanders (FWO) Demeester's research spans artificial intelligence with emphasis on deep learning and neuro-symbolic methods. Current tracks include energy-based models (Hopfield Networks, Deep Equilibrium Models), diffusion models for drug design, and clinical reasoning systems. His work bridges NLP, healthcare informatics, and generative AI with strong industry partnerships. Recent publications (2023-2025) reveal strategic expansion from NLP into health-centric AI: BioLORD biomedical encoders (2023), synthetic medical data frameworks (UAI/NeurIPS 2024), and novel diffusion model guidance (ICLR 2025). This evolution demonstrates convergence of generative modeling, clinical data analysis, and protein design. He actively mentors 24 PhD students across diverse AI domains: Current Research: Conversational agents, emotion analysis, clinical reasoning, antibody design, and diffusion model optimization Recent Graduates: Interpretable language models, biomedical semantics, task-oriented dialogue, and social media knowledge extraction Research is supported by imec funding and collaborations with Flemish biotech companies, building on his post-doctoral experience securing media-sector projects. Within IDLab, he co-leads the Text-to-Knowledge cluster driving NLP innovations for healthcare, legal, and economic applications.

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Michael Gastparمشاهده پروفایل

استاد

Swiss Federal Institute of Technology in LausanneSwitzerland

Michael Gastpar is a full Professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences, where he leads the Laboratory for Information in Networked Systems (LINX). He previously held faculty positions at the University of California, Berkeley (2003-2011, earning tenure in 2008) and Delft University of Technology. His research spans information theory, signal processing, communications, and systems neuroscience. His research interests focus on network information theory and related coding and signal processing techniques, with applications to sensor networks and neuroscience. Recent work demonstrates a strong shift toward exploring the theoretical foundations of modern machine learning, particularly investigating transformer architectures from an information-theoretic perspective. His research group at EPFL explores how information theory principles can provide fundamental limits and novel approaches for contemporary machine learning problems. His recent publications reveal a clear trend toward bridging classical information theory with modern machine learning. The 15 most recent papers show increasing focus on theoretical analysis of transformers, rate-distortion frameworks for language models, universal prediction methods, and applications of information measures to machine learning theory. This represents a strategic evolution from his earlier work on sensor networks and physical-layer network coding toward foundational questions in artificial intelligence. Scientific Awards: IEEE Fellow 2013 Communications Society & Information Theory Society Joint Paper Award Information Theory Society Distinguished Lecturer (2009-2011) ERC Starting Grant (2010) Okawa Foundation Research Grant (2008) NSF CAREER award (2004) 2002 EPFL Best Thesis Award Professor Gastpar has advised over 20 PhD students who have gone on to successful careers in both academia and industry. His research has been generously supported by major grants including an ERC Starting Grant "ComCom" (2011-2016) and ongoing support from the Swiss National Science Foundation. He has served in significant editorial roles, including as Associate Editor for Shannon Theory for the IEEE Transactions on Information Theory (2008-11) and as Technical Program Committee Co-Chair for the IEEE International Symposium on Information Theory in 2010 and 2021. He leads the Laboratory for Information in Networked Systems (LINX) at EPFL, which brings together researchers working at the intersection of information theory, machine learning, and networked systems. The lab maintains strong connections with both theoretical research communities and practical applications in communications and neuroscience.

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Juergen Schmidhuberمشاهده پروفایل

دانشیار

University of Italian SwitzerlandSwitzerland

Juergen Schmidhuber is Associate Professor at the Faculty of Informatics of Università della Svizzera italiana and a leading researcher at the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI). He is also Chief Scientist at NNAISENSE, a company dedicated to building practical general-purpose AI. His work has profoundly influenced modern artificial intelligence, particularly through the development of Long Short-Term Memory (LSTM) networks in 1991, now deployed across billions of devices for speech recognition, machine translation, and virtual assistants. His research interests span Artificial Intelligence, Deep Learning, Recurrent Neural Networks, Universal AI, Meta-Learning, Algorithmic Information Theory, Artificial Curiosity, Robotics , and Low-Complexity Art . He has pioneered mathematically rigorous frameworks for self-improving AI systems and formal theories of creativity and beauty. His work bridges theoretical foundations with real-world applications in computer vision, natural language processing, and autonomous robotics. The recent articles reflect a consistent trajectory of innovation, combining deep theoretical insights with scalable machine learning architectures. His publications emphasize sequence modeling, universal learning, intrinsic motivation, and computational creativity , demonstrating both foundational contributions and industrial impact. From LSTM to Goedel machines, his work consistently targets the long-term goal of self-improving general AI. Scientific Awards: Numerous awards in AI and machine learning (specific names not listed) Schmidhuber leads a research group at IDSIA, where he mentors students and researchers in advancing the frontiers of AI. His lab has secured significant recognition and industrial collaboration, though specific grants are not detailed. He promotes the 'New AI'—general, sound, and relevant to physics—and continues to explore the convergence of intelligence, computation, and the universe. Labs and Teams: Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI) NNAISENSE (as Chief Scientist)

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Milad Abediمشاهده پروفایل

مدرس

University of ZurichSwitzerland

Milad Abedi is a PhD candidate in Linguistics at the University of Zurich and Institut national des langues et civilisations orientales (INALCO), Paris, focusing on the cultural history of Sino-Iranian lexical contacts. He has taught Zoroastrian Middle Persian and Middle Iranian languages at the University of Zurich while conducting research on topics including language contact mechanisms and historical Persian grammar. PhD in Linguistics (2020–Present), University of Zurich & INALCO, Paris MA in Ancient Languages and Cultures of Iran (2015–2019), Allameh Tabataba'i University (Highest Distinction) BSc in Cellular-Molecular Biology (2010–2015), Islamic Azad University His research spans ancient Iranian language contact (Elamite-Iranian, Sino-Iranian, Arabic-Iranian), historical grammar of Persian, and Classical Persian literature. He has published on topics such as kinship term evolution, cuneiform epigraphy, and metonymic phrases in Achaemenid Elamite. Recent publications highlight his focus on lexical diffusion across Eurasia, with key works on donkey terminology in cross-cultural contexts and the origins of felt words in Iranian languages. His collaborative research with Wolfgang Behr and Samira Müller demonstrates interdisciplinary approaches combining linguistics and archaeology. 2021 Travel grant, University of Zurich 2016 Travel grant, Allameh Tabataba'i University 2016 Top student award, Allameh Tabataba'i University As a Lecturer at the University of Zurich, he has taught courses on Zoroastrian Middle Persian and historical linguistics. His digital humanities expertise includes ELAN software, GIS, and SQL for language documentation.

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Harald C. Gallمشاهده پروفایل

استاد

University of ZurichSwitzerland

Harald C. Gall is a Professor of Software Engineering and Dean of the Faculty of Business, Economics, and Informatics at the University of Zurich (UZH). He leads the Software Evolution and Architecture Lab, focusing on software evolution analysis, mining software repositories, and cloud-based software engineering. His research emphasizes improving software development productivity through data-driven insights. He has held visiting positions at Microsoft Research and the University of Washington. Education: PhD (Dr. techn.) and Master's (Dipl.-Ing.) in Informatics from TU Vienna Research Interests: Software evolution, mining software archives, cloud-based tools, developer productivity, and empirical software engineering. Notable contributions include the Evolizer , ChangeDistiller , and SOFAS systems. Key Contributions: Established the Mining Software Repositories (MSR) research area, program chair for ICSE 2011 and ESEC/FSE 2005, associate editor of leading journals like Empirical Software Engineering and IEEE Software. Awards: Most Influential Paper Award, Test of Time Award, and multiple Best Paper Awards. Recognized for contributions to SE research methodologies and tool development. Professional Activities: ACM SIGSOFT awards chair, board member of Informatics Europe, and executive committee member of CHOOSE (Swiss SIG for OO Systems). Labs/Teams: Director of the Software Evolution and Architecture Lab at UZH, leading projects like SURF-MobileAppsData (SNSF-funded) and DevCloud (Hasler Foundation).

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Sebastijan Dumancicمشاهده پروفایل

استادیار

Swiss Federal Institute of Technology in LausanneSwitzerland

Sebastijan Dumancic is an Assistant Professor at Delft University of Technology, focusing on neuro-symbolic AI through program synthesis and probabilistic programming. He leads the RAIL lab and collaborates with institutions like Harvard, MIT, and CNRS. His research bridges symbolic AI and machine learning, applying program synthesis to scientific discovery, transportation, and robotics. He holds an FWO-funded PhD from KU Leuven and has participated in initiatives like ELLIS and the Symbolic Computation and Machine Learning Initiative. Program synthesis Probabilistic programming Neuro-symbolic AI Constraint-based learning His recent articles highlight advancements in program synthesis, neuro-symbolic integration, and constraint satisfaction. Projects like Find2Fix and Intelligent Greenhouse Horticulture (funded by NWO) demonstrate practical applications. ELLIS Membership University Teaching Qualification He supervises numerous MSc and PhD students in projects involving logic programming, program synthesis, and probabilistic modeling. Active in workshops and symposia, he contributes to neuro-symbolic AI and scientific discovery.

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Lorenzo Baraldiمشاهده پروفایل

دانشیار

Swiss Federal Institute of Technology in LausanneSwitzerland

Lorenzo Baraldi is an Associate Professor at the University of Modena and Reggio Emilia, where he leads research in deep learning, vision-language integration, and multimodal AI systems. He serves as an ELLIS Scholar and Coordinator of the Modena ELLIS Unit, and has held the position of deputy director at the Interdepartmental Center on Digital Humanities since 2021. Previously, he worked at Facebook AI Research laboratory in Paris in 2017, developing video-matching algorithms for content moderation. His research spans multiple areas including Vision-and-Language integration, Multimodal Retrieval, Image and Video Captioning, Visual-Semantic alignment, Large-Scale model development, High Performance Computing, and Embodied AI. With over 120 publications in international journals and conferences, his work demonstrates consistent contributions to advancing multimodal AI capabilities. He has served as an Associate Editor for Computer Vision and Image Understanding and Pattern Recognition, and as Area Chair for major conferences including ICCV, WACV 2026, and ACM Multimedia 2025. His recent publication record shows significant impact in the field, with multiple papers accepted to top-tier conferences in 2024-2025 including CVPR, ICCV, BMVC, ICLR, ECCV, and NeurIPS. Notably, his paper "Hyperbolic Safety-Aware Vision-Language Models" was selected as a highlight paper at CVPR 2025. His research often involves collaboration with Rita Cucchiara and other researchers at his institution. ELLIS Scholar and Coordinator of the Modena ELLIS Unit Associate Editor for Computer Vision and Image Understanding Area Chair for ICCV and major multimedia conferences Highlight paper at CVPR 2025 Professor Baraldi teaches courses in Computer Vision and Cognitive Systems, Scalable AI, and Computer Architecture for the Artificial Intelligence Engineering and Computer Engineering programs. His teaching spans both undergraduate and graduate levels, with a focus on providing students with both theoretical foundations and practical implementation skills. He has developed educational materials including Deep Learning tutorials for classroom instruction.

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Yuval Noah Harariمشاهده پروفایل

مدرس

Swiss Federal Institute of Technology in LausanneSwitzerland

Yuval Noah Harari is a historian, philosopher, and lecturer at the Department of History at the Hebrew University of Jerusalem. Born in Haifa, Israel in 1976, he received his PhD from the University of Oxford in 2002. He is best known as the author of the internationally acclaimed books Sapiens: A Brief History of Humankind (2014), Homo Deus: A Brief History of Tomorrow (2016), 21 Lessons for the 21st Century (2018), Nexus: A Brief History of Information Networks from the Stone Age to Artificial Intelligence , and the Unstoppable Us children's series. Harari's research focuses on macro-historical questions including the relationship between history and biology, the essential difference between Homo sapiens and other animals, justice in history, historical directionality, human happiness throughout history, and the ethical questions raised by science and technology in the 21st century. His work bridges history, biology, philosophy, and economics, taking both macro and micro perspectives to understand not only what happened and why, but also how it felt for individuals. His books have sold over 45 million copies in 65 languages, with Sapiens alone selling 25 million copies since its publication. He is considered one of the world's most influential public intellectuals today. Harari has given keynote speeches at major international forums including the World Economic Forum in Davos and has presented as a digital avatar in a TED talk. Sapiens spent 96 consecutive weeks in the top 3 of the Sunday Times bestseller list Co-founded Sapienship, an international social impact company focused on education and storytelling, with his husband Itzik Yahav Regularly speaks at major international events on topics of technology, history, and the future of humanity Harari's recent work focuses on the challenges of the information age, particularly the crisis of truth and trust in an era of disinformation and artificial intelligence. He explores how humans can navigate the complex ethical questions raised by emerging technologies while maintaining democratic values and human dignity.

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Hugo Subtilمشاهده پروفایل

پژوهشگر

University of ZurichSwitzerland

Hugo Subtil is a postdoctoral researcher at the Department of Political Science, Faculty of Arts and Social Sciences, University of Zurich, affiliated with the Chair of Comparative Politics in Political Institutions and European Politics. He is an active member of the University's Digital Society Initiative (DSI), particularly engaged with the DSI Community AI & Law and multiple other interdisciplinary communities including Cybersecurity, Digital Humanities, and Ethics. His academic background includes: Economics studies at École Polytechnique (France) PhD from École des Mines and École Polytechnique (France) Subtil's research program integrates Political Economy, Political Science, and Computational Social Science to investigate European political dynamics through quantitative text analysis. He specializes in extracting political ideologies from large-scale text corpora using machine learning algorithms and social media data, with dual research foci: (1) how institutional design shapes social norms and behaviors, and (2) longitudinal evolution of political ideologies. His methodological approach bridges traditional political science with cutting-edge computational techniques for analyzing legislative discourse and public communication. Analysis of his 12 publications (2020-2025) reveals a clear trajectory from historical economic analysis toward contemporary computational political science. Early work (2020-2021) examined Marxian economics and pandemic-era urban migration patterns, while recent research (2023-2025) increasingly focuses on European Parliament discourse, populism, and emotional rhetoric using advanced text mining techniques. This evolution demonstrates growing specialization in computational analysis of political communication within European institutions. No scientific awards or major honors are documented in the available information. While no formal advisees or grant funding details are specified, Subtil's collaborative work within the DSI framework suggests engagement with interdisciplinary research teams addressing digital society challenges. His position within the Chair of Comparative Politics indicates involvement in departmental research initiatives related to European governance. Subtil operates at the nexus of multiple research ecosystems: the Department of Political Science's European Politics research group, the university-wide Digital Society Initiative, and specialized DSI communities exploring AI-law intersections. His work contributes to the DSI's mission of addressing societal challenges through digitalization research, particularly in computational analysis of political discourse and institutional behavior.

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Jinhan Kimمشاهده پروفایل

پژوهشگر

University of Italian SwitzerlandSwitzerland

Jinhan Kim is a Postdoctoral Researcher at the Università della Svizzera italiana (USI) in the Faculty of Informatics, working in the TAU lab under Prof. Paolo Tonella. He earned his Ph.D. from KAIST under Prof. Shin Yoo, focusing on software engineering research in mutation testing, fault localization, and deep learning system testing. His work bridges traditional software engineering techniques with AI-driven methodologies, emphasizing AI4SE and SE4AI paradigms. Education: Ph.D. in Software Engineering, KAIST, 2023 Research Interests: Mutation Testing Deep Learning System Testing Autonomous Systems Testing Adversarial Attack Detection Empirical Software Engineering Service and Leadership: Organized SBFT 2026 and DeepTest 2026 (co-located with ICSE 2026) Program Committee Member for ASE, ISSTA, Mutation, and DeMeSSAI Board of Distinguished Reviewers for TOSEM (2024–2025) Labs and Teams: Active contributor to the TAU Lab at USI, focusing on advanced software testing and AI integration.

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