جست‌وجوی استاد و پژوهشگر

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.

Vasileios Koulocherisمشاهده پروفایل

پژوهشگر

• Cryptography
• Cybersecurity
• Trusted Platform Modules (TPM)
• +۳ مورد دیگر

Dr. Vasileios Koulocheris is a Researcher affiliated with the Department of Energy and Process Systems Engineering at ETH Zürich. His work focuses on cryptographic protocols and cybersecurity, particularly in the context of anonymous authentication and trusted platform modules (TPM). He has contributed to extending Direct Anonymous Attestation (DAA) schemes to integrate TPM 2.0 functionalities, emphasizing formal security analysis and practical implementations. Affiliation: ETH Zürich, Department of Energy and Process Systems Engineering His research explores the intersection of cryptographic primitives and hardware security, including remote attestation mechanisms and the integration of TPMs for enhanced security. He has developed an open-source implementation of a DAA scheme supporting both hardware and software TPM environments, with performance benchmarking. No articles or awards were explicitly listed in the provided texts, though his technical contributions align with advancements in cryptographic protocol design and formal verification.

• Computational Neuroscience
• Neuroethology
• Neural Data Analysis
• +۳ مورد دیگر

Dr. Corinna Lorenz is a researcher at the Institute of Neuroinformatics, ETH Zürich, Switzerland, where she investigates neural mechanisms underlying behavior through computational and experimental approaches. Her work bridges neuroscience, machine learning, and animal behavior studies, primarily utilizing songbird models and advanced neurotechnologies. Her research focuses on computational neuroscience and neuroethology, with emphasis on vocal circuit dynamics in zebra finches. She develops innovative machine learning tools for neural data analysis, including vocal unit extraction from embedding spaces and chronic Neuropixels recordings. Additional interests span sensory processing (serotonin modulation in visual cortex) and body representation studies (rubber hand illusion), reflecting interdisciplinary expertise in neural coding and behavior. Analysis of her 12 recent publications (2012-2025) reveals three dominant themes: (1) Songbird vocal circuit dynamics during sleep/wake states and behavioral contexts, (2) Machine learning applications for unsupervised vocal analysis, and (3) Cross-species investigations of neural modulation in sensory systems. Her work consistently integrates custom hardware/software solutions with ethological paradigms. Dr. Lorenz maintains active research operations at ETH Zürich's Institute of Neuroinformatics (Y55 G 72), utilizing chronic recording methodologies and interactive data analysis frameworks. Her team develops open-source tools for vocal unit extraction and neural population analysis, contributing to reproducible neuroethology research.

• Immigration Studies
• Religious Communities
• Social Integration
• +۴ مورد دیگر

Prof. Martin Baumann is a Full Professor of Religious Studies at the University of Lucerne’s Faculty of Humanities and Social Sciences, serving as Head of the Department for the Study of Religions. He holds a PhD from the University of Hannover (1993) and a habilitation from Leipzig University (1999). His research focuses on migration, religious communities, social integration, diaspora studies, and Hindu/Buddhist traditions in Western societies. He previously held roles as Dean (2007–2009) and Vice-Chancellor for Research (2010–2018) at the University of Lucerne. His research explores the interplay between migration and religion, particularly analyzing how religious practices adapt in diaspora contexts. Notable areas include Tamil Hindu communities in Germany, Buddhist communities in Europe, and the role of religious institutions in Swiss civil society. He has contributed to debates on religious pluralism, interfaith dialogue, and the social functions of religious buildings in multicultural societies. Prof. Baumann’s work bridges theoretical religious studies with empirical fieldwork, often collaborating on interdisciplinary projects. His publications span academic monographs, edited volumes, and peer-reviewed articles addressing both historical and contemporary religious phenomena. He actively engages in policy discussions about the legal status of non-recognized religious groups in Switzerland and their societal integration. His recent projects include studies on the adaptation of Eastern religions in Europe, the sociology of religious youth identity formation, and the role of religious organizations in post-migrant societies. He has also contributed to digital humanities initiatives, such as heiMAP (a collaborative spatio-temporal research platform) and scientific data infrastructure projects like heiARCHIVE. Prof. Baumann advises doctoral candidates in religious studies and migration sociology. His work frequently intersects with questions of cultural preservation, religious policy, and the societal impacts of globalization.

Stefano Baliettiمشاهده پروفایل

پژوهشگر

• Computational Social Science
• Blockchain Governance
• Experimental Economics
• +۳ مورد دیگر

Stefano Balietti is a postdoctoral researcher at the University of Mannheim's chair of Data Science in Economic and Social Sciences. Previously affiliated with institutions like ETH Zurich, Harvard, and Microsoft Research, his work spans computational social science, blockchain governance, and experimental design. He is the creator of the open-source nodeGame platform for real-time behavioral experiments and co-founder of the State of Crypto initiative. He leads EduCERT, a project advancing digital teaching through blockchain. Affiliations: University of Mannheim (current), Heidelberg University, MZES, Microsoft Research, Northeastern University, Harvard IQSS, ETH Zurich Roles: Academic researcher, software developer, project leader His research focuses on consensus formation, peer review systems, blockchain governance, and optimal experimental designs. He has pioneered methodologies combining simulations, data analytics, and online experiments. His work on DAO governance and cryptocurrency markets has been widely cited. Key contributions include the nodeGame platform and the State of Crypto network. Awards include a special mention in the 2017 Exeter Prize and a Best Lightening Talk Award for his work on market structures. He teaches courses on blockchain economics, computational social science, and experimental design at Mannheim and Heidelberg. His interdisciplinary approach bridges computer science, sociology, and economics, with over 20 peer-reviewed publications since 2011.

• Experimental Psychology
• Neuroscience
• Rehabilitation Science
• +۳ مورد دیگر

Prof. Matthias Ertl is an Associate Professor of Experimental Rehabilitation Science at the University of Lucerne. He holds a PhD from Ludwig Maximilian University of Munich (2016) and completed his habilitation in Psychology at the University of Bern (2022). Currently, he serves as Head of Physiotherapy Development at Lucerne Cantonal Hospital. His research focuses on the interplay between sensorimotor skills and cognition, including neural correlates of balance processing, perceptual learning (e.g., fall prevention training), spatial memory, and navigation. Methodological expertise includes EEG, fMRI, and VR technologies. He contributes to open-source software projects such as PlatformCommander. Academic Journey: Postdoctoral Fellow at LMU Munich (2016–2018) Researcher at University Hospital Hamburg-Eppendorf (2013–2016) Joined University of Bern’s Institute of Psychology (2018–2024) Research Interests: Neural mechanisms underlying sensorimotor-cognitive interactions Perceptual learning paradigms for clinical applications Virtual reality for rehabilitation and spatial cognition studies Advising & Grants: No explicitly listed advisees or grant details in provided text Labs/Teams: Associated with the LIFE Forum Rehabilitation initiative Co-developer of PlatformCommander software

Gabriele Bavotaمشاهده پروفایل

استاد

• Software Engineering
• Artificial Intelligence
• Data Mining
• +۷ مورد دیگر

Gabriele Bavota is a Full Professor in the Faculty of Informatics at the Università della Svizzera italiana (USI). He holds a Laurea (cum laude) and PhD in Computer Science from the University of Salerno (2013). Before joining USI in 2016, he was an Assistant Professor at the Free University of Bolzano-Bozen (2014–2016) and a research fellow at the University of Sannio (2013–2014). Research Focus: Software maintenance, mining software repositories, empirical software engineering, and AI-driven code analysis. Awarded the 2018 ACM Sigsoft Early Career Researcher Award and leads the ERC Starting Grant project DEVINTA, exploring deep learning applications in software engineering. Authored over 180 publications in top venues like ICSE, FSE, and TOSEM, with multiple best/distinguished paper awards. His work bridges empirical studies, AI tools, and developer-centric solutions, addressing challenges in code quality, refactoring, and automated testing. He has served as program chair for ICPC 2016, SANER 2017, and ICSME 2023, and holds editorial roles in TSE, EMSE, and JSS. Labs/Teams: Principal Investigator of the DEVINTA project and part of the Software Institute at USI, fostering collaborations in AI, software engineering, and empirical research.

• Condensed Matter Physics
• Ultrafast Physics
• Spintronics
• +۳ مورد دیگر

Yves Marc Acremann is a Privatdozent at the Department of Physics, ETH Zürich, affiliated with the Laboratorium für Festkörperphysik. His research focuses on ultrafast processes in solids, magnetization dynamics, spintronics, and time-resolved photoemission techniques. He has contributed to experimental methodologies for studying femtosecond-scale phenomena in materials. Research Interests: Acremann’s work bridges fundamental physics with applications in spintronics and ultrafast magnetism. He explores how ultrafast laser pulses manipulate magnetization and electronic states, with a focus on time-resolved imaging and novel detector technologies. Recent studies include magnetization dynamics, spin injection mechanisms, and graphene electronic properties. Grants & Collaborations: His collaborations involve advanced spectroscopy and spin dynamics projects at ETH Zürich and other institutions. No specific grants are listed in the provided information. Labs/Teams: Active in the Laboratorium für Festkörperphysik, collaborating with teams on multidimensional photoemission and ultrafast electron microscopy techniques.

Adrian Bilandمشاهده پروفایل

مدرس

• Particle Physics
• Astrophysics
• High-Energy Gamma-Ray Detection
• +۳ مورد دیگر

Prof. Dr. Adrian Biland is a Lecturer at the Department of Physics at ETH Zürich, specifically affiliated with the Institute for Particle and Astrophysics. His research focuses on high-energy astrophysics, including studies of blazars, dark matter, gamma-ray detection techniques, and cosmic-ray acceleration mechanisms. He contributes to major observatories like the MAGIC telescopes and the Cherenkov Telescope Array (CTA). Key research areas include multiwavelength observations of active galactic nuclei, supernova remnants, and transient phenomena. Biland collaborates on instrumental advancements such as data standardization and open-source analysis tools for gamma-ray telescopes. His work bridges particle physics and astrophysics, emphasizing observational methods and theoretical modeling of high-energy phenomena.

Nicholas Bokulichمشاهده پروفایل

استادیار

• Microbiome Research
• Food Biotechnology
• Bioinformatics
• +۳ مورد دیگر

Prof. Nicholas Bokulich is an Assistant Professor at the Department of Health Sciences and Technology, ETH Zürich. His research focuses on microbiome dynamics in food systems, human health, and environmental contexts. Key areas include microbial diversity preservation, oral and gut microbiome associations with health outcomes, and the development of reproducible bioinformatics tools for analyzing microbiome data. Education details are not explicitly listed in the provided text. His work spans interdisciplinary projects such as the Microbiota Vault Initiative (conserving microbial biodiversity) and the HealthFerm initiative (exploring fermented foods for health and sustainability). He leads efforts in standardizing microbiome analysis pipelines, including contributions to QIIME 2, a widely used bioinformatics framework. Recent publications highlight his focus on food biotechnology, microbial forensics, and the interplay between microbiota and human physiology. He collaborates on projects involving vineyard microbiomes, maternal-infant microbial transfer, and the impact of environmental factors on microbial communities. His research bridges basic science and applied solutions in public health, agriculture, and technology.

Ingo Scholtesمشاهده پروفایل

استاد

• Machine Learning
• Network Science
• Graph Mining
• +۵ مورد دیگر

Prof. Ingo Scholtes is a Full Professor of Machine Learning for Complex Networks at Julius-Maximilians-Universität Würzburg's Center for Artificial Intelligence and Data Science (CAIDAS). He holds a doctorate in computer science and mathematics from the University of Trier and has held roles including SNSF Professor at the University of Zurich, Full Professor at Bergische Universität Wuppertal, and Senior Assistant at ETH Zürich. His research focuses on higher-order graph analytics for temporal networks, machine learning, and computational social science. Education: PhD in Computer Science (University of Trier, Germany), Postdoctoral Research at ETH Zürich (2011–2016), and prior roles at Karlsruhe Institute of Technology and CERN. Research Interests: Machine learning on graphs, temporal network analysis, higher-order network models, and their applications in software engineering and social systems. He develops open-source tools like pathpy and git2net for network analysis. Recent Work: Focuses on causality-aware graph neural networks, temporal graph isomorphism, and network science applications in AI. Recent articles include studies on temporal network dynamics, path prediction, and Bayesian inference of network transitions. Awards: SNSF Professorship (2018), Junior-Fellowship (2014), and German Academic Scholarship Foundation (2004-2005). Active in editorial roles for EPJ Data Science and leadership in GI's Computational Social Science working group.

• Combinatorial Optimization
• Artificial Intelligence
• Algorithms and Heuristics
• +۳ مورد دیگر

Eric Taillard is a Full Professor and Head of the Cross-functional Skills Group 'Optimization & Sustainability' at the School of Engineering and Management of the Canton of Vaud (HES-SO), part of the University of Applied Sciences and Arts Western Switzerland (HES-SO). He holds degrees in Computer Science, Engineering, and Production Management from HES-SO institutions. His research focuses on combinatorial optimization, metaheuristics, and algorithm design, with notable contributions to the Travelling Salesman Problem (TSP) and automated map labeling. Education: BSc in Computer Science and Communication Systems MSc in Engineering (Algorithms and Data Structures) MA in Production and Logistics Management Key Projects: Big Data in Combinatorial Optimization (2017–2020): Explored optimization techniques for large-scale problems. Parallel Computing on GPU Clusters (2010–2012): Enhanced combinatorial optimization via GPU parallelization. Automated Label Placement (2007–2008): Developed the PAL library for efficient cartographic labeling. Research Interests: Metaheuristics, TSP algorithms, POPMUSIC framework, algorithmic efficiency, and applications in logistics and cartography. His work has been published in journals like the EURO Journal of Operational Research and presented at Metaheuristics International Conferences. He leads interdisciplinary teams and collaborates with academic and industrial partners globally.

• Applied Microeconomics
• Microeconometrics
• Labor Economics
• +۸ مورد دیگر

Mattia Albertini is a Post-Doctoral Researcher at the Institute for Economic Research (IRE) within the Faculty of Economics at Università della Svizzera italiana (USI). He previously completed his Ph.D. at the Institute of Economics (IdEP), USI, and participated in the Swiss Program for Beginning Doctoral Students in Economics. He holds a Master of Science in Economics with a minor in Data Science from USI and a Bachelor in Economics from the University of Pavia. Bachelor in Economics, University of Pavia Master of Science in Economics (minor in Data Science), Università della Svizzera italiana Ph.D. in Economics, Università della Svizzera italiana Swiss Program for Beginning Doctoral Students in Economics, Swiss National Bank His research focuses on applied microeconometrics with applications in health, labor, public, urban, and environmental economics. A recurring theme in his work is the spatial dimension of economic outcomes, including residential integration, real estate market dynamics, and geographic proximity to borders or hazards. He integrates data science techniques, particularly programming in Python and STATA, to develop tools for empirical analysis and reproducible research. The collection of articles reflects a strong trend in applied econometrics, causal inference, and spatial analysis. His work spans health economics (e.g., benzodiazepine prescribing), labor and urban economics (e.g., migration, job accessibility), and environmental and insurance economics (e.g., natural hazard impacts). Methodologically, he engages with difference-in-differences, event study designs, spatial modeling, and text analysis, often building or applying computational tools to address research questions. He has contributed to teaching at both the Bachelor's and Master's levels, particularly in microeconomics, macroeconomics, and data-intensive courses such as Textual Analysis and Spatial Data for Economists. Teaching Assistant, Microeconomics A (Bachelor) Teaching Assistant, Macroeconomics B (Bachelor) Teaching Assistant, Textual Analysis and Spatial Data for Economists (Master) Mattia Albertini is actively involved in open science, sharing code for econometric methods, data visualization, and application development (e.g., a gluten-checking app) on GitHub. His interdisciplinary approach combines economic theory, statistical modeling, and computational tools to investigate real-world policy-relevant questions.

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.

Juan Carlos Farahمشاهده پروفایل

پژوهشگر

• Educational Technology
• Artificial Intelligence in Education
• Learning Analytics
• +۴ مورد دیگر

Juan Carlos Farah is a Researcher at the École Polytechnique Fédérale de Lausanne (EPFL), holding dual appointments in the Fondation Bertarelli Chair in Neuroprosthétique Cognitive (School of Life Sciences/SV) and the SCI-STI-DG group (School of Engineering/STI). His work bridges neuroscience, artificial intelligence, and educational technology, focusing on innovative applications of AI in learning environments and neuroprosthetics research. Research Interests: Farah’s research spans educational chatbot design, AI-enhanced learning analytics, neuroprosthetic systems, and the ethical integration of technology in education. He has pioneered frameworks for task-oriented conversational agents, blockchain-based learning trace repositories, and gamified computational thinking tools. Key Projects: He contributed to the Graasp Desktop initiative for underconnected African schools and developed the TRACE model for educational chatbots. His work on code review notebooks and bot-mediated software engineering education has influenced pedagogical practices globally. Awards & Recognition: No specific awards listed, but his publications reflect high-impact contributions to IEEE, ACM, and Elsevier journals/conferences. Active in global initiatives like UNESCO’s Unequal World Conference on education equity. Technical Expertise: Proficient in Python, JavaScript, and AI toolkits. Specializes in building scalable educational platforms, learning analytics pipelines, and neuroimaging analysis for cognitive studies.