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Silvio BarandunView profile

Research Fellow

• Non-Hermitian Systems
• Wave Propagation
• Metamaterials
• +5 more

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
• +12 more

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 ReberView profile

Researcher

• Environmental Policy
• Political Communication
• Transnationalization
• +4 more

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 YangView profile

Assistant Professor

• Macroeconomics
• Finance
• Machine Learning
• +3 more

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 BrauseView profile

Researcher

• Social construction of technology
• Social & communicative construction of Artificial Intelligence
• Sociotechnical imaginaries
• +3 more

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 RuffView profile

Professor

• Neuroeconomics
• Decision Neuroscience
• Cognitive Neuroscience
• +3 more

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 BovetView profile

Assistant Professor

• Complex Systems
• Network Science
• Social Media Analysis
• +7 more

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 AlizadehView profile

Research Fellow

• Political Science
• Digital Media Governance
• Social Network Analysis
• +3 more

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 HenryView profile

Research Fellow

• Political Behavior
• Digital Technology
• Violent Politics
• +7 more

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 HoesView profile

Research Fellow

• Digital Technologies
• AI and LLMs
• Misinformation
• +3 more

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.

Oleg ProkopyevView profile

Professor

• Operations Research
• Optimization
• Network Analysis
• +3 more

Oleg Prokopyev is a Professor of Quantitative Business Administration at the University of Zurich, affiliated with the Department of Business Administration. His office is located at PLR F 105, and he can be reached at +41 44 634 3444. His research focuses on optimization, network analysis, and stochastic programming, with applications in supply chain management, environmental studies, and healthcare systems. He holds a leadership role in the Chair of Quantitative Business Administration, contributing to interdisciplinary research in operations research and mathematical programming. Prokopyev’s work spans theoretical advancements in fractional programming, bilevel optimization, and graph algorithms, alongside practical applications such as wildfire fuel management, supply chain sustainability, and maintenance scheduling. His recent publications address dynamic assortment planning, interdiction models under uncertainty, and centrality measures in networks. His research emphasizes computational methods for solving complex optimization problems, including exact and heuristic approaches for clique relaxations, betweenness centrality, and robust decision-making frameworks. Prokopyev has collaborated on projects involving environmental impact assessments of beef supply chains and optimal design of healthcare systems like surgical patient routing.

• Finance
• Economics
• Experimental Finance
• +4 more

Michael Razen is a Researcher at the Department of Economics within the Faculty of Economics at the University of Innsbruck , Austria. His work bridges finance, economics, and behavioral research, with a focus on reproducibility, risk preferences, and tax compliance. His research interests include: Experimental Finance (e.g., choice architecture, monetary incentives) Behavioral Economics (e.g., financial literacy, cognitive biases) Quantitative Finance (e.g., non-standard errors, liquidity studies) Tax Policy (e.g., transparency effects on consumer and firm behavior) Recent publications highlight collaborations with institutions like Stockholm School of Economics , Vrije Universiteit Amsterdam , and Goethe University Frankfurt . His work appears in journals such as the Journal of Finance and European Accounting Review , emphasizing reproducibility, behavioral finance, and policy impacts. Key trends in his publications: 2019–2024 : Focus on data reproducibility , tax transparency , and behavioral finance using multi-analyst studies and experimental economics . Collaborative Networks : Frequent co-authorship with institutions across Europe (e.g., University of Innsbruck , HEC Paris ) and Asia (e.g., Singapore Management University ).

Marc LangheinrichView profile

Professor

• Privacy
• Security
• Ubiquitous Computing
• +7 more

Marc Langheinrich is a Full Professor and Dean at the Faculty of Computer Science, Università della Svizzera italiana (USI), where he also leads the Research Group for Ubiquitous Computing. His academic journey includes a PhD from ETH Zurich and prior roles at NEC Research and the University of Washington. He is affiliated with the Institute of Information Systems (SYS) at USI. Education: PhD (Dr. sc.) in Computer Science, ETH Zurich, Switzerland (2005) Master’s degree (Dipl.-Inf.) in Computer Science, University of Bielefeld, Germany (1997) Marc Langheinrich's research centers on privacy, security, and usability in ubiquitous and pervasive computing environments. His work explores how communication protocols, user interfaces, and system designs can protect personal data while enabling seamless interactions with smart devices. Key interests include lifelogging, memory augmentation, IoT privacy, and ethical design frameworks. He investigates technical and human factors in privacy-aware systems, often integrating insights from human-computer interaction and social computing. His recent publications demonstrate a strong focus on privacy-preserving machine learning (e.g., federated learning), mobility modeling, affective computing, and dataset development (e.g., LAUREATE). The research spans theoretical frameworks and practical implementations, often involving wearable sensing, multimodal data, and real-world user studies. Scientific Awards: Best Paper Award at DIS '18 for Roaming Objects: Encoding Digital Histories of Use into Shared Objects and Tools Best Paper Honorable Mention at MUM '16 for Design and evaluation of a wearable AR system for sharing personalized content on ski resort maps Marc Langheinrich has supervised numerous PhD and Master’s students, including Anton Fedosov, Evangelos Niforatos, and Matias Laporte. He has led multiple funded research projects in privacy, IoT, and human-computer interaction. He serves as Editor-in-Chief of IEEE Pervasive Magazine and on the steering committee of the IoT Conference Series, reflecting his leadership in the academic community. He leads the Research Group for Ubiquitous Computing at USI, which focuses on privacy-aware systems, digital memory augmentation, and interactive public displays. The group develops technologies that enhance user control over personal data while enabling novel applications in smart environments.

Gianni BuserView profile

Researcher

• Quantum Optics
• Quantum Information Science
• Atomic Physics
• +5 more

Dr. Gianni Buser is a Researcher at the University of Basel's Department of Physics, affiliated with the Quantum Optics Lab under Prof. Philipp Treutlein. He holds a PhD (2021) and Master’s degree (2016) from the University of Basel, specializing in quantum atom optics and atomic vapor-based quantum technologies. His research focuses on developing scalable quantum memories and optical storage systems using atomic vapor cells, with applications in quantum communication and quantum networking. Key contributions include advancements in microfabricated vapor cells, diode laser control techniques, and single-photon storage protocols. Buser’s work bridges quantum optics with optomechanical systems, exploring hybrid atom-light interfaces for next-generation quantum technologies. Teaching includes courses such as Physik IV (Quantum Optics), Physik II, and introductory computational quantum mechanics. His experimental techniques span laser manipulation, hyperfine state engineering, and optomechanical coupling. No scientific awards are explicitly listed for Buser, though his group has received recognition for related work. His research is supported by collaborations in quantum atom optics, optomechanical systems, and semiconductor-atomic interfaces.

Alexandre De MasiView profile

Researcher

• Mobile Computing
• Quality of Experience (QoE)
• Healthcare Technology
• +3 more

Alexandre De Masi is a Researcher at the Research Institute for Statistics and Information Science, University of Geneva. He holds a Ph.D. from the Centre Universitaire d'Informatique (University Computer Science Center). His research focuses on mobile computing, quality of experience (QoE), healthcare technology, and social robotics. He has contributed to interdisciplinary projects like the GUARDIAN ecosystem, a social robotics platform for assisted living. His work integrates wearable devices, predictive models, and living lab methodologies to enhance healthcare and user experience. Key areas include smartphone application behavior analysis, usability of social robots in homecare, and longitudinal data collection in human studies. He teaches 'Introduction to Programming' in executive programs. His recent studies explore AI-driven dialogue systems for clinical caregivers and the impact of physical activity on sleep using small data. Publications span conferences like ACM Multimedia Systems and Mobile and Ubiquitous Multimedia (MUM), with a focus on mobile QoE, IoT, and healthcare robotics. His research bridges technical innovation with real-world applications in health and daily life.