جست‌وجوی استاد و پژوهشگر

• Seismology
• Earthquake Dynamics
• Geophysics
• +۳ مورد دیگر

Dr. Kadek Hendrawan Palgunadi is a researcher at the Swiss Seismological Service (SED) under ETH Zurich. His work focuses on seismology, earthquake dynamics, and fault system analysis with a particular emphasis on Indonesia and Türkiye. He has contributed significantly to understanding cascading earthquake mechanisms, fault geometry characterization, and ground motion modeling. His recent studies include analysis of the 2023 Türkiye earthquake doublet, the 2022 Cianjur earthquake, and the newly identified Kalaotoa Fault system. Key research areas include multiscale seismicity patterns, fracture energy analysis in fault networks, and innovative methods for seismic waveform generation using machine learning. He has developed methodologies for hypocenter relocation and rupture dynamics modeling, contributing to improved seismic hazard assessments in active tectonic regions. His work also extends to interdisciplinary projects such as the Sea-VL dataset for Southeast Asia vision-language studies and sustainable agriculture systems. Notable contributions include insights into fault slip localization, stress regime analysis in complex fault systems, and applications of denoising diffusion models for high-resolution seismic data processing. Collaborations involve international institutions and fieldwork in regions like Sulawesi, Sumatra, and the East Anatolian Fault zone.

Markus Püschelمشاهده پروفایل

استاد

• Program Generation
• Fourier Analysis
• Signal Processing
• +۶ مورد دیگر

Markus Püschel is a Professor of Computer Science at ETH Zurich, leading the Advanced Computing Laboratory. He previously served as Head of the Department of Computer Science at ETH from 2013 to 2016. Before joining ETH in 2010, he was a Professor at Carnegie Mellon University (CMU) and retains adjunct status there. He holds a PhD in Computer Science (1998) and a Mathematics Diploma (1995) from the University of Karlsruhe. His research focuses on program generation for performance, Fourier analysis, signal processing, machine learning, and compiler optimization. He pioneered the SPIRAL system for generating optimized signal processing libraries and has contributed to algebraic signal processing theory. His work bridges mathematical foundations with practical high-performance computing, emphasizing automated code generation and domain-specific languages. Research trends in his articles include causal inference on directed acyclic graphs, quantized neural network inference, and efficient compiler techniques. His work on graph signal processing and causal analysis has led to novel methods in time-series data and DAG learning. Awards: IEEE Fellow (2020), Golden Owl Teaching Award (2015), NSF Discovery Grant (2008), and multiple best paper awards. Grants/Projects: Co-PI for Making Program Analysis Fast (SNF), SPIRAL GPU projects, and collaborations with industry partners like Intel and AMD. He advises over 40 PhD and master’s students, many of whom contribute to impactful projects in compilers, machine learning, and signal processing. His lab also co-founded the Swiss Data Science Center.

• Computational Linguistics
• Natural Language Processing (NLP)
• Language Model Interpretability
• +۴ مورد دیگر

Dr. Dan Jurafsky is a Professor at the Department of Linguistics within Stanford University's School of Humanities and Sciences. His work spans computational linguistics, natural language processing, and AI ethics, with a particular focus on language model behavior, speech recognition, and ethical implications of anthropomorphism in AI systems. His recent research explores HumT for measuring human-like tone in LLMs, AnthroScore for anthropomorphism detection, and methods for improving low-resource language support through data augmentation and multilingual representation learning. He has also developed open-source tools like string2string for string algorithms. Jurafsky's publications address critical issues in NLP, including grounding gaps in conversational models, causal interpretability in linguistic tasks, and representational biases in multilingual models. His work emphasizes interdisciplinary applications, from educational NLP tools to Sumerian transliteration datasets, while advocating for rigorous statistical power analysis and ethical model evaluation.

• Machine Learning
• Data Mining
• Artificial Intelligence
• +۷ مورد دیگر

Prof. Alexandros Kalousis holds the position of Ordinarius HES Professor at the Geneva School of Economics and Management (HES-SO). His primary affiliation is within the Department of Management Information Systems under the School of Economics and Services. His research focuses on machine learning, data mining, and their applications in biomedical systems, cybersecurity, and generative modeling. Key projects include SimGait (SNSF-funded), which develops neuromechanical models for pathological gait analysis using machine learning, and RAWFIE (EU-funded), creating a mixed network testbed for autonomous vehicle experimentation. He has also led projects on time series forecasting, olfactory modeling for perfume creation, and metric/kernel learning optimization. Notable contributions span graph generative models like DGAE and GLAD, cybersecurity implications of LLMs, and reproducible indoor positioning systems. His work integrates theory-driven models with deep learning, emphasizing interpretability and extrapolation capabilities. Research collaborations include EPFL's Biorobotics Lab, Geneva University Hospitals, and industry partners like Firmenich. Total funding exceeds CHF 3M across projects like SimGait (CHF 2.1M) and RAWFIE (CHF 623K).

Nina Kazaninaمشاهده پروفایل

استاد

• Neuroscience of Language
• Neural Mechanisms of Linguistic Computation
• Cognitive Neuroscience
• +۳ مورد دیگر

Prof. Nina Kazanina is a faculty member in the Department of Basic Neurosciences at the University of Geneva’s Faculty of Medicine. She co-directs the NCCR Evolving Language and previously served as an Associate Professor in Psychology and Cognitive Neuroscience of Language at the University of Bristol’s School of Psychological Science. Research focuses on the neural mechanisms underlying language, memory, and cognitive domains Lab employs EEG, MEG, fMRI, and behavioral methods Translational work targets language assessment in neurodegeneration and stroke Recent work explores grammatical abstraction in language models, neural oscillations in syntax, and reward-modulated memory. Her lab investigates how the brain encodes linguistic categories and hierarchical structures, bridging neuroscience and theoretical linguistics. Key translational applications include cognitive assessment across the lifespan. Lab members include postdocs (Theo Desbordes, Berk Gercek, Mamady Nabe, Itsaso Olasagasti) and PhD student Katarina Labancova. Contact: nina.kazanina@unige.ch

• Computational Linguistics
• Eye-tracking
• Machine Learning
• +۵ مورد دیگر

Lena Jaeger is an Associate Professor of Digital Linguistics at the University of Zurich, where she leads research at the intersection of linguistics, computational cognitive science, and machine learning. She joined the Chair of Computational Linguistics at UZH in July 2020 after establishing a Machine Learning Junior Research Group at the University of Potsdam, funded by the German Federal Ministry of Education and Research. Her educational background spans multiple disciplines: she earned an MA in Chinese Language and Culture (Sinology) from the University of Freiburg im Breisgau, Tongji University Shanghai, Beijing Language and Culture University, and Université Paris 7 Denis-Diderot; followed by an MSc in Experimental and Clinical Linguistics at the University of Potsdam; and completed her doctorate in cognitive science at the same institution. Notably, she also earned a bachelor's degree in computer science during or after her doctoral studies. Professor Jaeger's research focuses on investigating cognitive mechanisms underlying human language processing using experimental psycholinguistics, computational modeling, and machine learning methods. Her current work develops machine learning techniques for analyzing eye-tracking data to understand cognitive processes reflected in eye movement behavior. This interdisciplinary approach combines insights from linguistics, cognitive science, and artificial intelligence to create models that bridge human and machine language understanding. Her recent publications reveal a strong trend toward developing eye-tracking methodologies, creating multilingual corpora, and applying machine learning to understand reading behavior and language processing. Her work spans from fundamental research on cognitive mechanisms to practical applications in educational technology, medical diagnostics, and AI development. Best student late breaking work award for Reporting Eye-Tracking Data Quality: Towards a New Standard Best short paper award for Bridging the Gap: Gaze Events as Interpretable Concepts to Explain Deep Neural Sequence Models Professor Jaeger actively supervises multiple PhD students across computational linguistics, machine learning, and phonetics disciplines. Her research group collaborates extensively on large-scale projects like the MultiplEYE initiative, which establishes standards for multilingual eye-tracking data collection. She has secured significant research funding, including a Machine Learning Junior Research Group grant from the German Federal Ministry of Education and Research before moving to UZH. Her laboratory work centers on eye-tracking methodologies, developing tools like pymovements for eye movement data processing, and creating comprehensive corpora such as MECO (Multilingual Eye-Movement Corpus), MultiplEYE, and CoLAGaze. These resources support cross-linguistic research on reading behavior and language processing across diverse populations.

Denis Ribeaudمشاهده پروفایل

پژوهشگر

• Criminology
• Developmental Psychology
• Sociology of Violence
• +۵ مورد دیگر

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

Travis R. Nilesمشاهده پروفایل

پژوهشگر ارشد

• Corpus Paulinum
• Gospels Research
• New Testament and Ancient Philosophy
• +۳ مورد دیگر

Dr. Travis R. Niles serves as a Postdoctoral Researcher (Habilitand) at the Institute for New Testament Studies within the Faculty of Theology at the University of Bern. He leads research in the Swiss National Science Foundation project 'Resonances through History: Biographically Grounded Construals of History in the Early Roman Imperial Era' under Prof. Dr. Rainer Hirsch-Luipold. His academic credentials include: Ph.D. in Theology, University of Bern (2021) Master of Divinity, Princeton Theological Seminary (2017) Bachelor of Arts in Theology, Whitworth University (2011) Dr. Niles specializes in the intersection of New Testament studies with classical literature and philosophy, focusing on biographically grounded approaches to ancient texts. His work examines how early Imperial authors like Plutarch, Lucian, and New Testament writers construed divine involvement in historical narratives through biographical frameworks, particularly exploring philosophical concepts within Hellenistic Judaism and early Christianity. His recent publications reveal consistent engagement with Pauline literature, Gospel studies, and Greco-Roman historiography, demonstrating methodological innovation through comparative analysis of biblical and classical texts. Key thematic threads include the relationship between Stoic philosophy and Christology, the use of biographical forms in historical writing, and theological interpretations of palace architecture in antiquity. Scientific recognition includes: NEH-funded Translation Fellowship for Karl Barth Translators’ Seminar Dr. Niles maintains active teaching responsibilities across multiple institutions, supervising tutorials on New Testament exegesis and biblical theology while collaborating on international research projects. His current SNSF grant supports comparative analysis of historical construals across Jewish, Christian, and Greco-Roman literature during the Roman Imperial period. He participates in research teams through the 'Resonances through History' project and maintains affiliations with the Studiorum Novi Testamenti Societas and Society of Biblical Literature for scholarly exchange.

Matthias Grossglauserمشاهده پروفایل

استاد

• Machine Learning
• Stochastic Networks
• Discrete Choice Models
• +۴ مورد دیگر

Matthias Grossglauser is a Full Professor at the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL), where he co-directs the Information and Network Dynamics lab. He serves on the Federal Communications Commission (ComCom), Switzerland's telecommunications regulatory authority, and previously directed EPFL's Doctoral School in Computer and Communication Sciences (2016-2019). His career includes positions at Nokia Research Center (Internet Laboratory lead), AT&T Research, and EPFL (Assistant Professor). Education Ph.D. in Computer Science from Sorbonne Universités M.Sc. in Electrical Engineering from Georgia Institute of Technology Engineering degree in Communication Systems from EPFL Research Focus Grossglauser's research integrates machine learning, stochastic networks, and discrete choice models to address challenges in artificial intelligence, network science, computational social sciences, and recommender systems. His work emphasizes both theoretical foundations and practical applications, including political forecasting, climate communication, and network dynamics. Publication Trends Recent articles demonstrate strong focus on causal inference, optimal learning algorithms, and social network analysis. Dominant themes include reinforcement learning optimization, graph-based modeling, and NLP applications in political science. Methodological innovations in matrix factorization, Bayesian modeling, and stochastic processes recur throughout. Awards & Honors Fellow of IEEE and ELLIS Cor Baayen Award (1998) CoNEXT/SIGCOMM Rising Star Award (2006) Best Paper Awards: ACM COSN (2014), IEEE INFOCOM (2001) Nokia Mobile Data Challenge Winner (2012) Academic Leadership Has advised 16+ PhD students to completion and currently supervises 4 doctoral candidates. Secured research funding for projects including dynamic recommender systems, network alignment algorithms, and computational social science tools (e.g., Predikon.ch vote prediction platform). Leads the Information and Network Dynamics lab, focusing on AI-driven network analysis.

• Systems Neuroscience
• Motor Learning and Control
• Animal Behavior
• +۷ مورد دیگر

Prof. Mackenzie Weygandt Mathis is Tenure-Track Assistant Professor and Bertarelli Foundation Chair of Integrative Neuroscience at EPFL’s Brain Mind Institute . Leading the Mathis Lab since 2020, she unites machine learning and systems neuroscience to decipher how brains learn and control movement. Education : PhD in Neuroscience, Harvard University (2017, advisor Naoshige Uchida) Post-doctoral training, University of Tübingen with Matthias Bethge (2017) Rowland Fellow, Harvard University (2017-2020) Research Focus : the lab develops open-source AI tools ( DeepLabCut , CEBRA , AmadeusGPT ) and combines them with large-scale neural recordings in behaving mice to uncover the neural basis of adaptive motor control. Core themes include sensorimotor learning, proprioception, and brain-inspired algorithms for robotics. Publications Trend : recent work spans robust machine-learning methods (ICLR, AISTATS 2025), foundational models for pose estimation ( SuperAnimal , 2024), and integrative studies linking neural population dynamics to muscle-level control ( Nature 2023, Cell 2024). Scientific Awards : Swiss Science Prize Latsis 2024 Robert Bing Prize 2024 Eric Kandel Young Neuroscientist Prize 2023 FENS EJN Young Investigator Prize 2022 Vallee Scholar, ELLIS Scholar, NSF Graduate Fellow Advising & Funding : she mentors 4 current PhD students and several postdocs, supported by SNSF Starting Grant (1.5 M CHF), CZI, Novartis, Radala Foundation, and Kavli Foundation grants. Labs & Teams : the Mathis Lab is located at Campus Biotech , Geneva, and actively collaborates with the Alexander Mathis group, Allen Institute, and international consortiums on open-source neuroscience tools.

Markus Wildمشاهده پروفایل

استاد

• Theoretical Philosophy
• Animal Ethics
• Naturalism
• +۵ مورد دیگر

Prof. Dr. Markus Wild serves as a Professor of Theoretical Philosophy at the University of Basel since 2013. He is affiliated with the Faculty of Humanities and the Department of Arts, Media, Philosophy , focusing on the intersection of philosophy, ethics, and animal cognition. Born in 1971 in Eastern Switzerland Doctorate (2004) and Habilitation (2010) from the University of Basel and Humboldt University of Berlin, respectively His research spans theoretical philosophy , animal ethics , and naturalism , examining topics such as: Non-linguistic conceptual thought in animals Biological interpretations of Aristotelian ethics Philosophical implications of Nietzsche's naturalism Hydraulic models in life sciences Cultural and ethical dimensions of animal studies Heideggerian and Traklian poetic hermeneutics Recent publications include works on Aristotelian naturalism, animal cognition, and interdisciplinary approaches to nature philosophy. He actively contributes to academic discourse through lectures, such as his 2022 lecture on Animal Ethics and Naturalism at the Einstein Forum. Key roles and affiliations: President of the Postdoc.Mobility Evaluation Commission for the Humanities Member of the steering committee of NRP 79 "Advancing 3R" Equal Opportunities Officer for the Faculty of Humanities and Social Sciences (since 2022) Co-organizer of academic colloquia (e.g., Mittelbaukolloquium with Karen Koch and Conrad Mattli)

Kerstin Deneckeمشاهده پروفایل

استاد

• Natural Language Processing in Healthcare
• Conversational Agents and Chatbots
• Patient-centered Digital Health
• +۶ مورد دیگر

Prof. Dr. Kerstin Denecke is a Professor at Bern University of Applied Sciences (BFH) in the Engineering and Computer Science department, where she co-leads the Institute for Patient-centered Digital Health (PCDH). She maintains an affiliate position at the University of Victoria's School of Health Information Science and has conducted research visits at Canadian and New Zealand institutions. Her academic journey includes leadership roles in national and EU research projects, heading the 'Digital Patient Model' research group at Leipzig University prior to joining BFH in 2015. Dr. Denecke's research focuses on the intersection of artificial intelligence and healthcare, with particular expertise in natural language processing, conversational agents, and patient-centered digital health solutions. Her work spans multiple clinical domains including mental health interventions, radiology documentation, and suicide prevention. She employs participatory design methodologies that actively involve healthcare professionals and patients in the development process. Analysis of her recent publications reveals a strong emphasis on the practical application of large language models in clinical settings, ethical considerations in healthcare AI, and the development of taxonomies for conversational agents. Her research demonstrates a consistent trajectory toward making AI tools clinically usable while addressing real-world healthcare challenges. Young Talent Award of the Friedrich Wingert Foundation for outstanding approaches in medical linguistics and semantics Best Poster Award at MIE 2021 for 'Crowdsourcing for Creating a Dataset for Training a Medication Chatbot' Professor Denecke actively supervises bachelor, master, and PhD students, with current doctoral candidates working on medical text classification, social media chatbots for physical activity, and NLP applications in radiology. Her research is supported by multiple active grants including Innosuisse-funded projects on generative AI for clinical documentation. She leads the PCDH/AI for Health research unit which develops practical AI solutions for healthcare challenges while maintaining strong connections with clinical partners. The Institute for Patient-centered Digital Health under her co-leadership focuses on developing human-centered digital health solutions that address real clinical needs through interdisciplinary collaboration between computer scientists, healthcare professionals, and patients.