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Prof. Dr. Olena Palko is a historian specializing in Eastern Europe, the Soviet Union, and Ukraine. She holds the SNSF Professorship at the University of Basel's Department of History, focusing on East European History. Her research emphasizes Soviet minority policies, cultural politics, and national identity formation in interwar Ukraine. She is a leading scholar with notable works including Making Ukraine Soviet (2021), awarded the 2023 Alexander Nove Prize. Her current SNF-funded project, Red Tower of Babel , examines Soviet minority experiments in Ukraine. Education: PhD from University of East Anglia (2017); Kandydat nauk from National Academy of Sciences of Ukraine (2013). Research Interests: Soviet nationality policy, minority history, Ukrainian twentieth-century history, transnational border dynamics. Her work bridges archival analysis with transnational perspectives, addressing contested borderlands between Poland and the USSR. Key publications include co-edited volumes like Making Ukraine (2022) and Ukraine's Many Faces (2023). She actively contributes to academic governance roles, including co-convening the BASEES Study Group for Minority History and serving on the Scientific Advisory Council of the Council of Europe's history observatory.

• Soviet Nationality Policy
• Minority History in Eastern Europe
• Ukrainian History (20th Century)
• +3 more

Prof. Michael Moor is a tenure-track Assistant Professor for Medical AI at ETH Zurich's Department of Biosystems Science and Engineering in Basel. Previously, he conducted postdoctoral research at Stanford University under Prof. Jure Leskovec, focusing on medical foundation models. His work spans causal learning, multimodal AI, and sepsis prediction. Moor holds an MD from the University of Basel and a PhD from ETH Zurich's Machine Learning and Computational Biology Lab under Prof. Karsten Borgwardt. Research Interests: Generalist medical AI models Multimodal medical reasoning Zero-shot and few-shot learning Clinical causal inference Retrieval-augmented language models Sepsis prediction systems Key Achievements: Published foundational work in Nature (2023) on generalist medical AI Developed Med-Flamingo multimodal model (2023) Zero-shot causal learning framework accepted to NeurIPS 2023 (Spotlight) International sepsis prediction study with 156k ICU patients (2023) Lab Activities: Leads ETH's Medical Foundation Models group, collaborating with Stanford HAI and NASA Ames. Active in creating medical AI benchmarks like AgentClinic and developing retrieval-augmented systems like Almanac.

• Medical AI
• Machine Learning in Healthcare
• Causal Learning
• +3 more

Hoda Heidari is the K&L Gates Career Development Assistant Professor in Ethics and Computational Technologies at Carnegie Mellon University (CMU), with joint appointments in the Machine Learning Department and the Institute for Software, Systems, and Society. She is affiliated with the Human-Computer Interaction Institute and the Heinz College of Information Systems and Public Policy, and co-leads the university-wide Responsible AI Initiative and K&L Gates Initiative for Ethics and Computational Technologies. Education: PhD in Computer and Information Science (University of Pennsylvania), MSc in Statistics (Wharton School) Her research focuses on the Ethical, Societal, and Policy Implications of AI , particularly fairness and accountability in high-stakes domains. Her work includes evaluating risks/benefits of general-purpose AI, human-AI decision-making systems, and AI governance frameworks. She has received multiple awards, including best paper honors at AIES, FAccT, and SAT-ML. Her research is supported by the NSF Program on Fairness in AI, PwC, CyLab, Meta, and J. P. Morgan. Recent Publications examine generative AI safety, fairness measurement, AI incident documentation, and ethical governance. Her teaching includes courses on Responsible AI, ML Ethics, and Societal Decision-Making, with a focus on preparing students to critically analyze AI's societal impact. Scientific Awards: Best Paper (AIES 2024, FAccT 2021, SAT-ML 2023), Exemplary Track Award (EC 2021) Grants: NSF, PwC, CyLab, Meta, J. P. Morgan She advises doctoral students and postdocs across CMU departments and collaborates with interdisciplinary teams. Her service includes organizing AI safety workshops and advising on NIST guidelines for AI red-teaming.

• Ethical Implications of Artificial Intelligence
• Societal Implications of Artificial Intelligence
• Policy Implications of Artificial Intelligence
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Manuel Kaufmann is a Lecturer in the Department of Computer Science at ETH Zürich. His work focuses on advanced 3D human motion capture, sensor-based systems, and computer vision applications. He is affiliated with the Institute of Informatics (inf.ethz.ch) and contributes to research in real-time motion tracking, dataset development, and machine learning integration for human-robot interaction. Research interests include holistic human-scene reconstruction from monocular videos, gaze estimation using EEG signals, and expressive avatar creation. His projects emphasize practical applications in robotics, sports analytics, and biomedical engineering, often leveraging electromagnetic and inertial sensors for high-precision data acquisition. His publications reflect a trend toward multi-modal data fusion, real-world dataset creation (e.g., WorldPose, ARCTIC), and addressing challenges in loose garment modeling (Reloo). These efforts aim to improve markerless motion capture, crowd analysis, and human-robot collaboration. No scientific awards or grants are explicitly listed. He has no documented advisees, though his research may involve collaborations with students or teams. His office is located at OAT X 23, Andreasstrasse 5, Zürich, Switzerland, and contact details include a phone number and professional email.

• 3D Human Motion Capture
• Computer Vision
• Sensor Data Processing
• +3 more

Gerold Schneider is an Associate Professor at the University of Zurich , affiliated with the Department of Computational Linguistics under the Faculty of Arts and Social Sciences and Faculty of Business, Economics and Informatics . He leads the Text Crunching Center (TCC) , focusing on interdisciplinary research at the intersection of NLP, Digital Humanities, and Health Data Science. Research Interests His work spans Text Analytics , Digital Humanities , Corpus Linguistics , and Health Data Science , with applications in: Biomedical NLP (e.g., Alzheimer’s detection, clinical trials) Digital Humanities projects (e.g., analyzing Charles Dickens, UN archives) Migration discourse framing across languages Adversarial data collection for hate speech detection Interdisciplinary methodologies for digital unstructured data Recent Publications 2025–2024 research highlights include annotated corpora for preclinical and neurological studies, AI-driven analysis of historical linguistic variation, and innovative tools for language learners. His NLP applications address health diagnostics, ethical AI, and cross-lingual political discourse. Labs & Teams As TCC leader, he spearheads collaborative projects within the Digital Society Initiative (DSI) communities (AI & Law, Health, Ethics, etc.), integrating computational methods with humanities and health research.

• Computational Linguistics
• Digital Humanities
• Corpus Linguistics
• +3 more

Elaine M. Huang is an Associate Professor of Human-Computer Interaction at the Department of Informatics, University of Zurich, where she has served since 2010. She also leads the People and Computing Lab, focusing on the dynamic interplay between human practices and technological advancements. Her academic background includes: PhD in Computer Science, Georgia Institute of Technology (2006) Dr. Huang's research centers on human-computer interaction, examining the bidirectional relationship between technology and human practices. She is particularly known for her work on gender equality in technology, challenging assumptions about innate gender differences and investigating how AI systems may perpetuate biases. Her research also spans sustainable interaction design, mental health technologies, and chronic disease management, always emphasizing empirical data over intuition. Analysis of her recent publications (2023-2025) reveals a strong trajectory toward socially impactful HCI, with significant focus on health technologies (diabetes management, mental health), cultural sensitivity in design, and the ethical challenges of AI. Her methodology often involves field studies to understand real-world technology use, countering the industry's reliance on intuition. As head of the People and Computing Lab, Dr. Huang oversees a research group dedicated to designing and evaluating technologies that address complex human needs. The lab's work frequently involves co-design with diverse user communities to ensure relevance and inclusivity in technological solutions.

• Human-Computer Interaction
• Gender Equality in Technology
• AI and Society
• +3 more

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.

• Cartography
• Geoinformatics
• Geographic Information Systems (GIS)
• +4 more

Prof. April Wang is an Assistant Professor in the Department of Computer Science at ETH Zurich. Her work focuses on Educational Technology, Human-Computer Interaction, and AI-driven tools for programming education. She is affiliated with the Professur Educational Technology group and teaches courses such as Human Computer Interaction and Ethics in Computing. Her research explores interactive learning environments, collaborative data science workflows, and AI-augmented educational systems. Her research interests span computational notebooks, live coding interfaces, and human-AI collaboration in software development. Notable contributions include frameworks like DBox for algorithm learning and EDBooks for interactive programming narratives. She also investigates challenges in real-time collaboration tools and automated documentation systems for data scientists. Recent work emphasizes understanding user needs in automated copilot systems and resolving conflicts in collaborative notebook environments. Her projects often bridge theoretical HCI principles with practical educational tools, aiming to enhance both instructor efficacy and student engagement. Prof. Wang’s teaching portfolio includes courses on user-centered interface design and ethical scientific practices. She actively contributes to advancing interdisciplinary computational literacy through initiatives like datAR, which uses everyday objects to teach data concepts.

• Educational Technology
• Human-Computer Interaction
• Data Science
• +4 more

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.

• Contract Law
• Corporate Law
• Mergers and Acquisitions
• +5 more

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.

• Digital Humanities
• Computational History
• Historical Map Analysis
• +4 more

Marion Schulze is an Assistant Professor of Gender Studies and Cultural Anthropology at the University of Basel, serving as Co-Chair of the Center for Gender Studies. Her academic journey includes a joint professorship with Prof. Alain Müller and prior roles as Senior Lecturer at the University of Neuchâtel and doctoral researcher at the University of Basel. She holds a PhD in Sociology from Basel and a degree in Arts and English from the University of Osnabrück, Germany. Her research intersects feminist epistemology, sociology of social worlds, and knowledge materialities. Key projects include studying verbs-as-concepts in feminist theory (earning an SNSF Spark Grant), analyzing hardcore-punk's gender knowledge systems, and investigating digital infrastructures through K-Drama viewer studies. She also explores analog design practices and non-human entities in social world ecologies. Notable achievements include founding a EU-COFUND graduate school at the Swiss School of Public Health, authoring the monograph Hardcore & Gender , and curating an 1980s hardcore graphic design blog series. Her work bridges theory and practice through participatory ethnography and innovative archival methods. Key Research Themes: Feminist material theory, social world ecologies, hyphenation in feminist texts, multi-reality frameworks Methodological Innovations: Figure-ground archiving, organo-graphic approaches, translocal ethnography Prior professional milestones include building interdisciplinary academic programs and advancing queer methodologies in subcultural studies. Her current projects explore the intersection of plants and social worlds through material feminist frameworks.

• Gender Studies
• Cultural Anthropology
• Feminist Theory
• +6 more

Manfred Einsiedler is a Professor in the Department of Mathematics at ETH Zurich, Switzerland, with office HG G 64.2 at Rämistrasse 101, 8092 Zurich. He teaches undergraduate and graduate courses including Linear Algebra (HS 2019), Analysis I/II, and Functional Analysis I/II, using his co-authored textbook Functional Analysis, Spectral Theory, and Applications . His research centers on dynamical and equidistribution problems in homogeneous spaces, with focus on closed horocycle orbits, geodesic orbits on the modular surface, and measure rigidity. Key contributions include work on effective equidistribution, entropy methods, and connections between ergodic theory and number theory. He has co-authored foundational texts: Ergodic Theory with a view towards Number Theory and Functional Analysis, Spectral Theory, and Applications in Springer's Graduate Texts in Mathematics series, alongside multiple in-progress volumes on entropy, homogeneous dynamics, and unitary representations. Recent publications explore integer points on spheres, rigidity of invariant measures, and Diophantine approximation on fractals, emphasizing collaborations with Lindenstrauss, Ward, Margulis, and Venkatesh. His work demonstrates consistent focus on homogeneous dynamics with applications to arithmetic problems, particularly through effective methods and measure classification theorems. While no specific awards or student lists are documented in the source, his extensive publication record and textbook authorship establish significant scholarly impact.

• Dynamical systems
• Ergodic theory
• Homogeneous spaces
• +4 more

Matej Varga is a Scientific Assistant and Postdoctoral Researcher at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering, working in the Geosensors and Engineering Geodesy group under Prof. Andreas Wieser since 2021. His research spans geometrical geodesy, physical geodesy, and satellite geodesy, with applications in both theoretical and practical domains. Dr. Varga's research interests focus on spatial, temporal and spectral analysis of geodetic data, with particular expertise in geodetic reference systems and frames, gravity and geomagnetic field modeling at all temporal and spatial scales, and multi-GNSS multi-frequency positioning and monitoring. His work integrates geometrical and physical aspects of geodesy to address complex Earth observation challenges, particularly in infrastructure monitoring and geophysical applications. His recent publications demonstrate a strong trend toward high-precision geodetic applications for major scientific infrastructure, most notably the Future Circular Collider project, alongside important contributions to earthquake impact analysis, geomagnetic network development, and gravity field modeling. His research bridges traditional geodetic methods with modern computational approaches, including machine learning applications for point cloud registration. Dr. Varga is actively involved in the GSEG research group at ETH Zurich, contributing to the development of geodetic infrastructure and reference systems. His work has practical applications in infrastructure monitoring, earthquake analysis, and scientific projects requiring extreme geodetic precision.

• Geodesy
• Geomatics
• Physical Geodesy
• +7 more

Martin Volk is a Full Professor of Computational Linguistics at the University of Zurich, with a dual affiliation to the Department of Informatics since 2019. He holds a PhD from the University of Koblenz and has held academic positions at institutions including Stockholm University (part-time from 2008-2011), Zurich University of Applied Sciences, and the University of Georgia. His research focuses on grammar engineering, machine translation evaluation, multilingual text analysis, and cross-language information retrieval. Education : Born in Cochem, Germany Studied Computer Science and Computational Linguistics at EWH University, Koblenz Master's in Artificial Intelligence at the University of Georgia (Fulbright Scholar) PhD in Computational Linguistics from the University of Koblenz Research Interests : His work emphasizes data-driven NLP methods, including corpus-based approaches, parsing technologies, and the application of machine learning to historical and multilingual texts. Key focuses include: Machine translation systems and evaluation frameworks Grammar testing environments (e.g., GTU) OCR and digitization of historical documents (e.g., Gothic script) Development of parallel corpora for linguistic research Projects : SMULTRON: Multilingual parallel treebank project Bullinger Digital: Historical document digitization initiative Text+Berg: Digital Humanities project for alpine textual heritage EU-funded MuchMore (cross-language medical IR) Grants & Collaborations : Recipient of grants from the Swiss National Science Foundation, EU projects, and industry partnerships (e.g., Siemens, Xerox). His work integrates academic and industrial perspectives in NLP tool development. Labs & Teams : Leads research teams in the Institute of Computational Linguistics at UZH, focusing on projects like the Zurich Parallel Corpus Collection and MODERN (modeling discourse for MT).

• Computational Linguistics
• Machine Translation
• Natural Language Processing
• +5 more

Christoph Stadtfeld is Associate Professor of Social Networks at ETH Zurich's Department of Humanities, Social and Political Sciences and co-director of the ETH Social Networks Lab. His research examines social network dynamics, focusing on tie formation processes, network effects on individuals, and advanced statistical methodologies for longitudinal network analysis. Education: PhD from Karlsruhe Institute of Technology (2011) Postdoctoral researcher and Marie-Curie fellow at University of Groningen, University of Lugano, and MIT Media Lab (2011-2014) His work bridges sociology, statistics, and computer science to address fundamental questions about how social structures evolve and influence behavior. Key interests include relational event modeling, co-evolution of networks and attributes, and applications in mental health, political polarization, and scientific collaboration. He develops innovative methods for analyzing dynamic networks using cutting-edge computational approaches. Recent publications reveal strong emphasis on methodological rigor in temporal network analysis, with significant contributions to relational event modeling and dynamic network actor frameworks. His work increasingly addresses societal challenges including political polarization, mental health impacts of social isolation, and innovation dynamics in healthcare. Scientific awards: Raymond Boudon Award of the European Academy of Sociology (2017) Freeman Award of the International Network for Social Network Analysis (2021) As co-director of the ETH Social Networks Lab, Stadtfeld leads interdisciplinary research teams developing novel network methodologies. His work has been supported by prestigious fellowships including Marie-Curie funding, and he actively mentors graduate students in network science methodology and applications across diverse domains. The ETH Social Networks Lab serves as a hub for advancing network theory and methodology, with ongoing projects examining student networks during crises, scientific collaboration dynamics, and innovation ecosystems through the lens of network science.

• Social Network Analysis
• Dynamics of Social Networks
• Statistical Methods for Network Data
• +2 more