جست‌وجوی استاد و پژوهشگر

Dirk Mohrمشاهده پروفایل

استاد

• Mechanical Engineering
• Manufacturing Processes
• Materials Science
• +۵ مورد دیگر

Prof. Dirk Mohr is a Full Professor at ETH Zürich's Department of Mechanical and Process Engineering, leading the Artificial Intelligence in Mechanics and Manufacturing (AIMM) group. He specializes in computational models for lightweight materials under extreme conditions, crashworthiness, and high-strain-rate material behavior. His research integrates experiments and simulations, with applications in automotive safety and advanced manufacturing. Education: PhD in Applied Mechanics from MIT (2003) MSc from University of Karlsruhe and École Nationale des Ponts et Chaussées Research Focus: Developing AI-driven models for material design and failure prediction Investigating material behavior under impact, high strain rates, and elevated temperatures Creating architected metamaterials for energy absorption and structural efficiency Battery safety mechanics and lithium-ion cell modeling Key Contributions: Recipient of the Hetenyi Award (2007) and IJP Young Investigator Award (2016) Editorial roles at International Journal of Impact Engineering and International Journal of Solids and Structures Industry collaborations with Daimler and BMW Current Projects: Machine learning for material modeling and battery safety High-speed experimentation for failure analysis Design of ultralight cellular materials

• Combustion
• Acoustics
• Fluid Mechanics
• +۴ مورد دیگر

Prof. Nicolas Noiray is an Associate Professor and Deputy Head of the Institute of Energy and Process Engineering at ETH Zürich, where he leads the Combustion, Acoustics & Flow Physics (CAPS) Laboratory established in 2014. His research focuses on combustion, acoustics, and fluid mechanics, addressing both fundamental and applied challenges. He holds a Ph.D. from École Centrale Paris (2007) and previously worked at Alstom’s Gas Turbine Research Division. Key achievements include pioneering work on thermoacoustic instability control, hydrogen combustion systems, and plasma-assisted stabilization. He has received prestigious awards such as the Silver Medal from the International Combustion Institute and ERC grants. His academic affiliations include the Department of Mechanical and Process Engineering at ETH Zürich, with a focus on interdisciplinary research at the intersection of energy systems and fluid dynamics. His lab investigates topics like flame dynamics, aeroacoustic feedback, and novel combustor designs to enhance efficiency and reduce emissions. Research interests span combustion instabilities, acoustic wave control, and sustainable energy technologies. Recent work includes studies on hydrogen-powered combustors, nonlinear dynamics of flames, and metamaterial-based solutions for noise reduction. He has contributed to advancing computational models for large-eddy simulations and real-time digital twins for combustion systems. Notable awards include the Hiroshi Tsuji Early Career Award and ERC Consolidator/Synergy Grants, reflecting his impactful contributions to combustion science. His research bridges theoretical insights with industrial applications, particularly in aerospace and power generation sectors.

• Machine Learning
• Natural Language Processing
• Computational Linguistics
• +۳ مورد دیگر

Prof. Ryan Cotterell is an Assistant Professor in the Department of Computer Science at ETH Zürich. His research focuses on machine learning and natural language processing, particularly in transformer models, syntactic control of language systems, and computational linguistics. He teaches courses such as Neural Networks and Computational Complexity, Natural Language Processing, and Advanced Topics in Machine Learning. His work bridges theoretical foundations and practical applications, exploring topics like language model expressivity, information locality, and formal language theory. Recent publications highlight innovations in controlled generation, model evaluation, and multimodal systems. While no specific awards are listed, his contributions to the field are evident through his extensive publication record and academic roles. Advising and grant details are not explicitly mentioned in the provided texts, but his involvement in teaching and research indicates active mentorship and project leadership. No lab or team affiliations specific to Ryan Cotterell are detailed here.

Mrinmaya Sachanمشاهده پروفایل

استادیار

• Artificial Intelligence
• Educational Technology
• Natural Language Processing
• +۳ مورد دیگر

Mrinmaya Sachan is an Assistant Professor in the Department of Computer Science at ETH Zürich, specializing in artificial intelligence, educational technology, and natural language processing. His research explores the intersection of AI and pedagogy, focusing on knowledge tracing, uncertainty quantification, and ethical implications of language models. Recent publications highlight his work on improving AI safety, detecting reasoning errors, and enhancing educational tools through machine learning. Key topics include arithmetic reasoning, causal analysis, and vision-language integration for physics problems. His projects often involve benchmarking AI systems in domains like legal reasoning (LEXam), math education (Mathtutorbench), and cognitive modeling of students. Collaborative efforts extend to multilingual dialogue systems, automated grading, and ethical AI frameworks.

• Nonlinear Dynamical Systems
• Reduced Order Modeling
• Hybrid Testing
• +۳ مورد دیگر

Tom Simpson is a Researcher at ETH Zurich specializing in computational mechanics and data-driven engineering methods. Previously completing his PhD at the Chair of Structural Mechanics (2018-2023), he focuses on developing advanced simulation techniques for complex engineering systems. His work bridges theoretical mechanics with machine learning applications. His educational background includes a Master's degree in Mechanical Engineering from the University of Sheffield (2018), where his thesis explored manifold learning techniques for nonlinear dynamical systems. During his studies, he gained practical experience at the Advanced Manufacturing Research Centre investigating aerospace alloy machining methods. Simpson's research centers on reduced order modeling, hybrid simulation techniques, and machine learning applications in structural dynamics. His work particularly emphasizes variational autoencoders for nonlinear systems, parametric dependencies in engineering models, and real-time simulation frameworks. Key application areas include structural health monitoring, offshore wind energy systems, and railway vehicle dynamics. His publication record demonstrates consistent focus on integrating physics-based modeling with data-driven approaches. Recent work shows increasing sophistication in error bound estimation, probabilistic modeling, and online monitoring-conditioned simulations. The research trajectory reveals progression from foundational nonlinear dynamics to cutting-edge hybrid AI-physics simulation frameworks. Simpson actively contributes to the DyVirt research project and collaborates extensively with Professor Eleni Chatzi's research group. His work appears in leading engineering journals including Mechanical Systems and Signal Processing, Scientific Reports, and Frontiers in Energy Research, demonstrating both theoretical rigor and practical engineering applications.

Silvio Barandunمشاهده پروفایل

پژوهشگر ارشد

• Non-Hermitian Systems
• Wave Propagation
• Metamaterials
• +۵ مورد دیگر

Silvio Barandun is a Postdoctoral Research Fellow at the Department of Mathematics of MIT, starting September 2025, working in the group 'Nanostructures and Computation' under Prof. S. G. Johnson. He completed his PhD in Mathematics at ETH Zurich in April 2025 under Prof. H. Ammari. His research focuses on photonic and phononic wave propagation in complex media, particularly non-Hermitian systems with geometric components. Barandun has taught courses such as Linear Algebra for electrical engineers and Numerical Methods for physicists at ETH Zurich. He actively supervises student projects and theses, co-organizes academic colloquia, and serves on the Foundation Council of the Swiss Study Foundation. His work bridges mathematical physics and applied mathematics, with a strong emphasis on metamaterials and resonator systems. Education: PhD (2025), ETH Zurich; Master's (2022), ETH Zurich; Bachelor's (2021), ETH Zurich. Research interests include non-Hermitian systems, topological metamaterials, and resonator dynamics. His publications span journals like Proceedings of the Royal Society A , SIAM Journal on Applied Mathematics , and Journal of Physics A . He frequently presents at international conferences on wave propagation and mathematical physics.

• Quantum Chemistry
• Materials Science
• Mathematics
• +۱۲ مورد دیگر

Michael F. Herbst is a tenure-track Assistant Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) with joint appointments in Mathematics and Materials Science. He leads the Mathematics for Materials Modelling (MatMat) research group, focusing on algorithm development for quantum-chemical simulations of solids and error control in computational modeling. His work bridges mathematics, solid-state physics, and computer science through interdisciplinary research. His research interests include: Density-functional theory (DFT) and Kohn-Sham equations Error propagation in materials property predictions High-throughput screening algorithms Julia programming for scientific computing Tensor networks and reduced basis modeling Self-consistent field convergence methods Recent publications highlight his contributions to: Efficient response property calculations in DFT Rotationally equivariant machine learning operators GPU-accelerated electronic structure methods Polarizable continuum solvation models Robust black-box quantum chemistry algorithms Open-source software development Teaching activities span mathematics, computer science, and chemistry curricula, including interdisciplinary workshops on electronic structure numerics and Julia programming for materials science. He has mentored PhD students Bruno Ploumhans and Niklas Frederik Schmitz.

Ueli Reberمشاهده پروفایل

پژوهشگر

• Environmental Policy
• Political Communication
• Transnationalization
• +۴ مورد دیگر

Ueli Reber is a Postdoctoral Researcher at the Swiss Federal Institute of Aquatic Science and Technology (Eawag), part of the Policy Analysis and Environmental Governance (PEGO) group. He holds a PhD in Social Sciences and a Master's in Geography from the University of Bern. His research focuses on environmental policy, political communication, transnationalization, and computational methods for text/network analysis. He currently leads the TRAPEGO project on pesticide governance evidence diffusion. His work bridges policy integration, biodiversity analysis, and online discourse dynamics. Publications span environmental policy, climate change skepticism, and methodological innovations in text analysis. He teaches courses in political communication and computational methods. Current Affiliation: Eawag, PEGO Group Education: PhD (University of Bern), MSc Geography (University of Bern) Research emphasizes evidence use in policy, transnational climate debates, and biodiversity integration. Projects include analyzing Swiss biodiversity policy and pesticide governance barriers. Teaching includes R programming for social sciences and text-as-data methodologies.

Yucheng Yangمشاهده پروفایل

استادیار

• Macroeconomics
• Finance
• Machine Learning
• +۳ مورد دیگر

Yucheng Yang is an Assistant Professor of Finance at the University of Zurich and a member of the Swiss Finance Institute. He earned his PhD from Princeton University in 2023, with prior degrees from Peking University and the University of Wisconsin-Madison. His research focuses on macroeconomics, finance, and machine learning, emphasizing topics like heterogeneous agent models, monetary policy, and big data integration. He has held visiting positions at NYU and Yale and has received awards such as the CICF Yihong Xia Best Paper Award and the CES Gregory Chow Best Paper Award. His work bridges theoretical economics with computational methods, addressing challenges in asset pricing, business cycle analysis, and policy design. Recent research includes applications of deep learning to search and matching models and the development of global solution methods for complex economic systems. Yang is actively involved in teaching and mentoring, currently hiring research assistants in machine learning and macroeconomic modeling. Awards include recognition for his contributions to macroeconomic analysis and financial modeling. His research has implications for central bank policies and financial market dynamics, with a focus on inclusive economic frameworks.

Saba Rebecca Brauseمشاهده پروفایل

پژوهشگر

• Social construction of technology
• Social & communicative construction of Artificial Intelligence
• Sociotechnical imaginaries
• +۳ مورد دیگر

Saba Rebecca Brause is a Researcher and Doctoral Research Assistant at the Department of Communication and Media Research (IKMZ) at the University of Zurich, Switzerland. She holds an MA from Sciences Po Paris and an MSc from the Oxford Internet Institute. Her research focuses on sociotechnical imaginaries, the social and communicative construction of AI, privacy in smart technologies, and quantitative methods. She currently leads the SNF-funded project analyzing AI imaginaries in China, Germany, and the US. Education includes: 2017–2021: Doctoral Research Assistant at University of Zurich 2018–2021: Research Assistant at Weizenbaum Institute and TU Berlin 2017–2021: MSc in Social Science of the Internet (University of Oxford) 2014–2016: MA in Communication (Sciences Po Paris, cum laude) 2011–2014: BA at Sciences Po Paris (with a year abroad at Heriot-Watt University) Her work bridges communication studies and technology sociology, examining how AI and smart technologies are socially constructed through media, discourse, and user practices. Recent studies explore privacy implications of voice assistants, cross-national AI media narratives, and platform labor dynamics. She has presented findings at top conferences like ICA and EASST, contributing to critical AI studies and science communication. Key grants include the Swiss National Science Foundation project on AI imaginaries. Her collaborative work spans interdisciplinary teams across Europe and North America, addressing ethical and societal dimensions of emerging technologies. Labs/teams: Primary affiliation with IKMZ’s Science Communication division, collaborating with institutions like the Weizenbaum Institute and McGill University on AI and public discourse projects.

Christian Ruffمشاهده پروفایل

استاد

• Neuroeconomics
• Decision Neuroscience
• Cognitive Neuroscience
• +۳ مورد دیگر

Christian Ruff is a Professor of Neuroeconomics and Decision Neuroscience at the University of Zurich's Department of Economics. His research focuses on the neural mechanisms underlying decision-making, integrating insights from economics, cognitive science, and neuroscience. He employs experimental, computational, and neuroimaging techniques to model how neural processes influence choices and social behavior. Education: PhD in Cognitive Neuroscience from University College London (2007), followed by postdoctoral work at UCL until 2010. His career at the University of Zurich since 2010 has centered on studying human motivation, decision-making, and learning, with a focus on neurocomputational models. Research interests include the neural basis of prosocial behavior, risk preferences, and strategic decision-making. He explores how brain regions like the prefrontal cortex and parietal cortex modulate choices, often using non-invasive brain stimulation (e.g., TMS, tDCS) to test causal hypotheses. His work bridges disciplines, with implications for economics, medicine, and policy. Key collaborations include the Zurich Center for Neuroeconomics and the SNS Lab. His studies on stress resilience, therapeutic inertia in medical decision-making, and the neurobiology of fairness highlight interdisciplinary applications. Current projects investigate how neural mechanisms adapt to contextual and social demands, aiming to improve models of human behavior in diverse settings.

Alexandre Bovetمشاهده پروفایل

استادیار

• Complex Systems
• Network Science
• Social Media Analysis
• +۷ مورد دیگر

Prof. Dr. Alexandre Bovet is an Assistant Professor in Quantitative Network Science at the Department of Mathematical Modeling and Machine Learning (D3ML), Faculty of Science, University of Zurich. He holds a PhD in Physics from EPFL (2015) and completed postdoctoral research at ETH Zurich, City College of New York, Université catholique de Louvain, and the University of Oxford. He is a member of the Swiss Young Academy and the steering committee of the Winter Workshop on Complex Systems. His research focuses on complex systems and network science, particularly modeling social media dynamics, disinformation propagation, and opinion formation. He develops interdisciplinary approaches combining physics, mathematics, and data science to address societal challenges. Key projects include analyzing polarization in social networks, algorithmic curation on platforms like Bluesky, and fact-checking with large language models. Awardees of SNSF and FNRS fellowships, Bovet leads the ClarifAI project (funded by DIZH) to combat disinformation using AI. His work spans conferences such as NetSci, CompleNet, and CCS, with over 50 publications. Collaborations include institutions like UCLouvain, Oxford, and interdisciplinary teams in computational social science. Bovet advises PhD students like Dorian Quelle and contributes to labs like the Digital Society Initiative (DSI) at UZH. His research bridges theory and practice, addressing real-world issues in media, democracy, and technology.

Meysam Alizadehمشاهده پروفایل

پژوهشگر ارشد

• Political Science
• Digital Media Governance
• Social Network Analysis
• +۳ مورد دیگر

Meysam Alizadeh is a Research Fellow at the Department of Political Science, University of Zurich. His work focuses on digital media governance, social network analysis, and the application of artificial intelligence in political and social contexts. He investigates issues such as platform governance, content moderation, fake news propagation, and the impact of social media on political discourse. Alizadeh has collaborated extensively on projects involving large language models (LLMs) for text annotation, comparing their performance to human workers, and developing methods to detect information operations and hate speech. His research bridges computer science, political science, and data science, addressing both theoretical and applied challenges in digital society. Key areas of investigation include analyzing cryptocurrency market dynamics through social media data, exploring the relationship between Russian information campaigns and hate crimes, and examining conspiracy theory proliferation during the pandemic. He has contributed to methodological advancements in creating national random samples of Twitter users and optimizing LLM-based tools for academic and practical applications. Alizadeh's publications span journals like Political Communication , Scientific Reports , and Proceedings of the National Academy of Sciences , reflecting interdisciplinary collaboration with institutions worldwide. His research often emphasizes the ethical and policy implications of emerging technologies in public communication and governance.

Colin Henryمشاهده پروفایل

پژوهشگر ارشد

• Political Behavior
• Digital Technology
• Violent Politics
• +۷ مورد دیگر

Colin Henry is a Research Fellow at the University of Zürich's Department of Political Science, focusing on the intersection of political behavior and digital technology. His work examines how platform governance structures influence extremism in online communities, using computational methods, network analysis, and digital ethnography. He holds a PhD from Vanderbilt University where he developed the Varieties of Platform Governance (VPG) dataset. His research has been published in PS: Political Science & Politics and Journal of Conflict Resolution . Education: PhD Candidate in Political Science, Vanderbilt University Affiliations: Research on Conflict and Collective Action Lab (Vanderbilt), Data Science for Social Good Fellow (2021) Key research themes include the architecture of social media platforms, hate speech classification, AI's influence on political behavior, and the structural drivers of online radicalization. His agent-based modeling work explores how platform algorithms and competition dynamics exacerbate political extremism. His peer-reviewed publications analyze data-security risks for researchers and the impact of violence on journalism in Mexico. Current projects investigate platform intervention strategies against hate communities and the ecological spread of online extremism. Grants/Awards: Data Science Institute Fellowship (2021) Labs: Led development of netify , an R package for conflict network analysis Colin co-founded the Vanderbilt Graduate Ideas Symposium, a graduate-student organized conference fostering interdisciplinary dialogue. His work bridges political theory, digital ethics, and computational social science.

Emma Hoesمشاهده پروفایل

پژوهشگر ارشد

• Digital Technologies
• AI and LLMs
• Misinformation
• +۳ مورد دیگر

Dr. Emma Hoes is a Postdoctoral Research Fellow at the Department of Political Science, University of Zurich. She holds a PhD from the European University Institute in Florence, Italy. Her research focuses on digital technologies' impact on information ecosystems, with emphasis on AI, misinformation, and content moderation. She is involved in the ERC-funded PRODIGI project and the Digital Democracy Lab. Her work challenges alarmist views on AI and disinformation, emphasizing evidence-based interventions. Key research themes include the effectiveness of misinformation countermeasures, AI governance, and the societal implications of social media. She employs experimental methods (surveys, field experiments) and computational social science approaches. Recent publications explore platform governance, media literacy, and policy U-turns. Teaching: She instructs the course Agenda Setting and the Media: Framing the Political Debate at UZH. Professional contributions include non-academic chapters on media polarization and conspiracy theories, plus media appearances in Phys , Algemeen Dagblad , and Dutch radio. Her work appears in top journals like Nature Human Behavior , Political Communication , and European Political Science Review . Ongoing projects examine AI-generated news engagement, conspiracy theory prevalence, and experimental methodological dilemmas.