جست‌وجوی استاد و پژوهشگر

Titus Mangham-Neupertمشاهده پروفایل

استاد

• Condensed Matter Physics
• Topological Quantum Matter
• Strongly Correlated Electron Systems
• +۷ مورد دیگر

Prof. Dr. Titus Mangham-Neupert is Full Professor of Theoretical Physics at the University of Zurich and co-director of its Digital Society Initiative . He leads the Theory of Quantum Matter group within the Department of Physics, Faculty of Science, and sits on several strategic boards including the Digital Strategy Board, Graduate Campus advisory board, and the Pauli Center board. Education & Career 2025–present: Full Professor, Department of Physics, University of Zurich 2021–present: Co-director, Digital Society Initiative, University of Zurich 2018–2025: Associate Professor, Department of Physics, University of Zurich 2016–2018: Assistant Professor, Department of Physics, University of Zurich 2013–2016: Postdoctoral Fellow, Princeton Center for Theoretical Science, Princeton University 2010–2013: PhD in Physics, ETH Zurich (advisors: Prof. Manfred Sigrist, Dr. Christopher Mudry) 2009–2010: Visiting Scientist, RIKEN, Japan 2007–2009: MSc in Physics, University of Zurich 2005–2007: Undergraduate studies, Dresden University of Technology Research Interests Neupert’s work straddles condensed-matter physics, quantum materials, topology, and machine learning . His group develops variational and tensor-network approaches to strongly-correlated electrons, explores fractional topological phases , and investigates kagome metals, moiré graphene, and unconventional superconductors . A growing focus is the deployment of neural-network quantum states and AI-assisted data analysis to uncover emergent quantum phenomena. Grants & Funding ERC Starting Grant “PARATOP” Swiss National Science Foundation project grants Member of the Swiss MaNEP network Scientific Awards & Honors Clarivate Highly Cited Researcher (2020-2024) Outstanding Referee, American Physical Society (2019) Klung-Wilhelmy Science Award (2019) ETH Medal for PhD thesis (2013) Swiss Physical Society Dissertation Prize (2013) Professional Service & Memberships Member, Editorial Board, Physical Review B (2020-2026) Member, Digital Strategy Board, University of Zurich Advisory boards: Graduate Campus UZH, Science Lab UZH & Science Pavilion UZH Board member, Pauli Center (UZH & ETH Zurich) Member, American Physical Society

• Comparative Politics
• Democracy Research
• European Politics
• +۵ مورد دیگر

Tina Freyburg is a Professor for Comparative Politics at the University of St. Gallen , affiliated with the School of Economics and Political Science (SEPS-HSG) and the Department of International Politics and Law (IPW-HSG). Her research focuses on empirical democracy research, functional cooperation with authoritarian regimes, and evidence-based policy advice. She leads an innovative research program addressing democratic challenges in a globalizing and digitizing world, emphasizing the protection of democratic institutions against populist threats. Key affiliations: Interdisciplinary working group External Democratization Policy (EDP), Competence Center for African Research (CCAR) Research methods: Mixed-method approaches including interviews, statistical simulations, and survey experiments Policy priorities: Sustainable Development Goals (SDG 13, 16, 7, 4) Her team investigates telecommunications ownership control, EU conditionality mechanisms, and climate governance. Funded by the Swiss National Science Foundation (SNSF), Horizon Europe, and the University of St. Gallen, the group maintains rigorous ethical fieldwork standards while implementing institutional sustainability measures.

• Human Factors
• Human-Machine Interaction
• Automated Driving
• +۳ مورد دیگر

Prof. Markus Hackenfort is a Professor for Human Factors Psychology at the ZHAW School of Applied Psychology, Zurich University of Applied Sciences (ZHAW). He leads modules in Traffic Psychology, Social Psychology, and Sociology. His research focuses on human factors, automated driving, and cognitive causes of human behavior. He holds a PhD in Applied Cognitive Science from the University of Duisburg-Essen (2007) and a 1st state examination in teaching psychology and social pedagogy (2002). Education: PhD in Applied Cognitive Science, University of Duisburg-Essen (2005–2007) 1st State Examination in Teaching Psychology & Social Pedagogy, Universities of Dortmund & Duisburg-Essen (1997–2002) Research Interests: Human-Machine Interaction Risk Perception and Decision-Making Automated Driving Systems Quantitative Methodologies Prevention Programs for Youth Road Safety Projects: Leader of projects analyzing overtaking maneuvers, e-scooter safety, and cyber resilience networks Co-lead of studies on road safety KPIs and sensor-based accident research Developed prevention programs for young drivers and urban mobility safety Awards: No specific awards listed, but has received grants for over 20 projects. Labs & Teams: Active in RoadCross Schweiz, Scientraffic, and ASTRA collaborations. Leads interdisciplinary teams in road safety and automated vehicle research.

Beate Sickمشاهده پروفایل

استاد

• Machine Learning
• Medical Imaging
• Deep Learning
• +۳ مورد دیگر

Beate Sick is a Professor at the Zurich University of Applied Sciences School of Engineering, specializing in Data Analysis and Statistics. Her work bridges machine learning, probabilistic modeling, and medical applications, particularly in stroke outcome prediction, uncertainty quantification, and statistical methods for healthcare.

• Quantitative Finance
• Financial Mathematics
• Risk Engineering
• +۱ مورد دیگر

Dr. Gisela Reichmuth is Lecturer for Financial Mathematics at the ZHAW School of Engineering, Zurich University of Applied Sciences. Her professional background includes executive roles as CEO of RockX (2018-2024) and COO of move digital AG (2015-2018), following her tenure as Head of Trading at IMC Financial Markets (2005-2012). She holds a PhD in Atmospheric Sciences from ETH Zurich and an MBA in International Management. Her academic focus applies mathematical, statistical, and algorithmic methods to financial markets and investment analysis. Earlier atmospheric science research examined ozone depletion mechanisms and stratospheric chemistry. Recent work addresses open banking systems and financial technology innovation. She maintains active industry engagement through the Start Angels Network and professional certifications in digital innovation.

Sergey Litvinovمشاهده پروفایل

پژوهشگر

• Computational Mechanics
• Biomedical Engineering
• Industrial Applications
• +۶ مورد دیگر

Sergey Litvinov is a Researcher at ETH Zürich, affiliated with the Department of Structural Mechanics and Monitoring within the College of Civil, Environmental and Geomatic Engineering. His work focuses on computational and statistical models for biomedical and industrial applications, leveraging tools like C++, PyTorch, and cloud computing. He contributes to hierarchical Bayesian analysis on big data and probabilistic programming, emphasizing data-driven methodologies. Current projects include the DCoMEX initiative (Data-Driven Computational Mechanics at Exascale), aiming to advance large-scale computational frameworks for structural mechanics and monitoring. His research interests span computational mechanics, fluid dynamics, and machine learning applications, with a strong emphasis on hybrid numerical methods and high-performance computing for multiphase systems. He has no listed scientific awards or advisees. His contributions are centered on software development (e.g., Aphros and Mirheo ) for multiphase flow simulations and novel optimization techniques for inverse problems, particularly in biomedical and engineering contexts. Recent articles highlight his work on discrete loss optimization, reinforcement learning for flow control, and data-driven methods for tumor growth modeling and drug delivery systems. He is part of interdisciplinary teams addressing challenges in microfluidics, turbulence modeling, and biomedical applications, with a focus on scalable solutions for complex systems. His projects often involve collaboration with industrial and academic partners on computational models for real-world applications.

Maria Willeckeمشاهده پروفایل

مدرس

• Statistical Methodology
• High-Dimensional Data Analysis
• Network Analysis
• +۳ مورد دیگر

Dr. Maria Willecke is a Lecturer at the Department of Health Sciences and Technology, ETH Zürich. She holds a BSc in Mathematics from the University of Science and Technology of China (USTC) and a PhD in Statistics from the University of Wisconsin-Madison. Her research focuses on developing statistical methods for analyzing complex, high-dimensional, and networked data. She has held faculty positions at Peking University, the University of Munich, and the National University of Singapore. Dr. Willecke is an active organizer of workshops, including the Tsinghua Sanya International Mathematics Forum Workshop on Statistical Methods for Network Analysis (2024) and the Workshop on Statistical Analysis of Networks (2023). She leads a research group at the University of Warwick and advises PhD students in statistical theory and applications. She has received prestigious awards, including Fellowship from the Institute of Mathematical Statistics and election to the International Statistical Institute. Her work spans collaborations with institutions globally, and she maintains an office at ETH Zürich’s Gloriastrasse location.

Maria Giulia Pretiمشاهده پروفایل

مدرس

• Neuroimaging
• Brain Connectivity
• Alzheimer's Disease
• +۳ مورد دیگر

Maria Giulia Preti is a Senior Scientist at MIPLAB, Research Staff Scientist at the CIBM Center for Biomedical Imaging (Switzerland), and a Lecturer (Maître-Assistante) at the University of Geneva. She holds a PhD in Bioengineering from Politecnico di Milano (2013) and completed postdoctoral research in Dimitri Van De Ville’s group at EPFL. Her work focuses on integrating neuroimaging techniques (fMRI, DTI, EEG, fNIRS) with graph signal processing to study brain function-structure relationships in health and disease. Key clinical applications include Alzheimer’s disease, epilepsy, multiple sclerosis, and stroke. She has pioneered methods like groupwise fMRI-guided tractography to study neurodegenerative pathologies. Education: PhD in Bioengineering (2013), Politecnico di Milano MSc in Biomedical Engineering (2009), Politecnico di Milano BSc in Biomedical Engineering (2007), Politecnico di Milano Research emphasizes multimodal neuroimaging integration and computational neuroscience. Notable achievements include developing connectome embedding techniques and demonstrating brain fingerprinting via spectral signatures. She received the Progetto Rocca fellowship (2011) supporting her work at MIT/Harvard Medical School. Ongoing projects investigate structure-function coupling dynamics, drowsiness markers, and DBS mechanisms in depression. Labs/Teams: MIP:Lab (part of the Van De Ville group at EPFL and University of Geneva collaborations).

• Environmental Systems Science
• Ecosystem Ecology
• Flood Modeling
• +۳ مورد دیگر

Dr. Priyanka Chaudhary is a Researcher affiliated with the Professorship for Global Ecosystem Ecology at ETH Zurich's Department of Environmental Systems Science . Her work focuses on integrating computational methods with environmental science, particularly in flood modeling and disaster risk assessment. She contributes to advancing methodologies for water resource management and urban resilience through deep learning and social media data analytics. Her research interests span ecosystem ecology , flood prediction systems , and environmental monitoring technologies . Notably, she develops innovative approaches using convolutional neural networks and ensemble methods to estimate flood depths and uncertainties. Recent work leverages social media imagery for real-time flood level estimation, enhancing crisis response capabilities. Dr. Chaudhary's publications reflect a strong emphasis on interdisciplinary solutions to environmental challenges, combining hydrology, computer science, and geospatial analysis. Her contributions highlight the potential of data-driven methods in addressing global environmental issues such as climate change impacts and urban flood risk mitigation.

Semyon Malamudمشاهده پروفایل

دانشیار

• Big Data
• Machine Learning
• Liquidity and Market Frictions
• +۸ مورد دیگر

Semyon Malamud is an Associate Professor of Finance at the Swiss Finance Institute at École Polytechnique Fédérale de Lausanne (EPFL), where he has held a tenured position since October 2015. He is also a Research Fellow at the Center for Economic Policy Research (CEPR), a Senior Chair at the Swiss Finance Institute, and has served as a Visiting Assistant Professor at the University of Texas at Austin’s McCombs School of Business and a Visiting Professor at UBC Sauder School of Business in 2020. Additionally, he holds a Research Fellow position at the Bank for International Settlements and was a Lamfalussy Fellow of the European Central Bank in 2015. Education: Ph.D. in Mathematics, Swiss Federal Institute of Technology (ETH Zurich), Switzerland, May 2006. Diploma in Mathematics, Donetsk National University, Donetsk, Ukraine, July 2001. Current Research Interests: Big Data and Machine Learning , focusing on their applications in asset pricing and financial markets. Liquidity and Market Frictions , exploring their impact on market dynamics and investment strategies. International Finance , including exchange rate models and dominant currency debt. Information Economics , studying information percolation and equilibrium-driven market behaviors. Equilibrium Asset Pricing and Optimal Contracting , addressing viable markets and security design. Network Economics and Corporate Finance , analyzing market integration and corporate capital structure. Work in Macroeconomics , particularly in endogenous growth and risk management. Scientific Awards and Grants: INQUIRE Europe Research Grant (2022) Lamfalussy Fellow of the European Central Bank (2015) Joint INQUIRE Europe-INQUIRE UK Prize (2015) CEPR Research Fellow (2015–present) ETF Academy Award (2015) Europlace Institute of Finance Award (2015) Swiss National Science Foundation Starting Grant (CHF 1m, 5 years) Dauphine Amundi Prize in Asset Management (2014 and 2013) Swiss Finance Institute Research Grant (2013–2015) Narrative on Advising and Grants: Malamud’s research has been supported through prestigious grants such as the Swiss National Science Foundation Starting Grant and INQUIRE Europe awards. He has collaborated extensively with scholars like Bryan Kelly, Darrell Duffie, and Julien Hugonnier. As an Associate Editor for top journals including the Journal of Finance and Journal of Financial Econometrics , he contributes to academic rigor in finance. His work on machine learning applications and large factor models reflects cutting-edge trends in financial economics. Labs and Teams: Malamud’s research is anchored within the Swiss Finance Institute (SFI) and its collaborative networks. He actively engages with the CEPR and BIS research communities, contributing to interdisciplinary projects in financial markets and policy.

Mario Valentin Wüthrichمشاهده پروفایل

استاد

• Actuarial Science
• Insurance Mathematics
• Stochastic Finance
• +۶ مورد دیگر

Mario V. Wüthrich is a Professor for Actuarial Science in the Department of Mathematics at ETH Zurich. Born in 1969, he earned a diploma (1995) and PhD (1999) in mathematics from ETH Zurich. He held a postdoc position at Nijmegen University (1999–2000), worked at Winterthur Insurance (2000–2005), and became a Senior Scientist at ETH Zurich's Mathematics Department (2005). Since 2011, he has been an Adjunct Professor and currently serves as a full Professor. His research focuses on actuarial models, insurance liabilities, and risk management. He is Editor-in-Chief of the ASTIN Bulletin and a Senior Scientific Advisor at InsureAI. He has received numerous awards, including the Brian Hey Prize (2021) and JoCo Best Paper Award (2025). His work spans machine learning applications in insurance, claims reserving, and data analytics. Upcoming engagements include the International Congress on Insurance: Mathematics and Economics (2025–2028). Educations: ETH Zurich (PhD 1999, Diploma 1995) Affiliations: RiskLab, ASTIN Bulletin Editorial Board Research interests combine theoretical actuarial science with practical applications in insurance pricing, risk modeling, and AI-driven solutions. Recent publications include advancements in neural networks for actuarial problems and credibility theory.

Patrick Schniderمشاهده پروفایل

مدرس

• Discrete Geometry
• Computational Geometry
• Topological Data Analysis
• +۴ مورد دیگر

Patrick Schnider is a lecturer in the Department of Mathematics and Computer Science at the University of Basel and the Department of Computer Science at ETH Zürich. His academic journey includes postdoctoral positions at ETH Zürich under Prof. Bernd Gärtner and Prof. Emo Welzl, and at the University of Copenhagen with Prof. Karim Adiprasito. He holds a PhD in Theoretical Computer Science from ETH Zürich between 2015 and 2020. Education: Bachelor's and Master's degrees in Mathematics from ETH Zürich. PhD in Theoretical Computer Science under Prof. Emo Welzl. Research focuses on combinatorial and topological methods in discrete geometry and high-dimensional data analysis, including topological methods for mass partitions, combinatorial depth measures, geometric transversals, computational geometry, and topological properties of solution spaces. Recent work explores geometric algorithms, topological data analysis, and combinatorial optimization, with notable contributions to clustering algorithms, persistent homology applications, and fair division problems. No scientific awards explicitly mentioned. Collaborations include the Theory of Combinatorial Algorithms Group at ETH Zurich and research groups led by Prof. Gärtner and Adiprasito. Other interests include music, playing clarinet in a wind orchestra, and conducting in various orchestral projects.

• Marketing
• Data Science
• Machine Learning
• +۳ مورد دیگر

Simone Griesser is a Lecturer at the Lucerne School of Business, part of Lucerne University of Applied Sciences and Arts (HSLU), where she is affiliated with the Institute of Communication and Marketing (IKM) and the CC Communication Management department. Her research focuses on leveraging language data (voice/text) for business and NGO insights, using statistical methods and machine learning. She holds a PhD from Warwick Business School, granting her an international and regional academic network. She teaches courses including Supervision of Bachelor and Master Theses, Applied Research Projects, and Marketing Communication. Professional competencies span marketing/communication strategy, service experience sales, project management, and programming in R/Python. Key research interests include AI-driven customer segmentation, brand polarization analysis, sustainability in e-commerce, and algorithmic nudging. She actively reviews for conferences like EMAC and SDS, and serves on the board of the Swiss Association for Natural Language Processing (SwissNLP). Notable projects include developing real-time sentiment barometers for brand reputation and analyzing mis/disinformation characteristics.

Halldór Janetzkoمشاهده پروفایل

استاد

• Visual Analytics
• Data Science
• Information Visualization
• +۳ مورد دیگر

Halldór Janetzko is a Professor at the Lucerne School of Computer Science and Information Technology, part of Lucerne University of Applied Sciences and Arts. His expertise lies in Visual Analytics, Data Science, and Information Visualization. He holds a PhD in Computer Science (2015) and dual Master's and Bachelor's degrees in Information Engineering from the University of Konstanz. Research focuses on integrating temporal, geospatial, and multi-dimensional data analysis, particularly through projects like Visual Analytics for Soccer, Geospatial Sentiment Analysis, and Energy Consumption Monitoring. His work emphasizes user-centric systems for pattern discovery and decision-making support. Education: PhD in Computer Science, University of Konstanz (2015) MSc in Information Engineering, University of Konstanz (2010) BSc in Information Engineering, University of Konstanz (2008) Teaching includes Programming Fundamentals, Data Visualization, and Geographic Information Systems. He has led multiple research initiatives, including the Smart Region Lab and energy transition visualization projects. His work bridges computational methods with real-world applications in sports, urban planning, and environmental monitoring.

• Regional Economics
• Data Analysis
• Knowledge Economy
• +۳ مورد دیگر

Silke Zöllner is a Lecturer at the Lucerne School of Business (HSLU), part of the Institute of Business and Regional Economics (IBR), specializing in Regional Economy. She holds a Master of Science in Business Administration (HTW Chur) and a Bachelor of Science in Human Geography (University of Dalarna, Sweden). Her research focuses on regional economic development, data analysis methodologies, knowledge economy dynamics, and industrial policy. Notable projects include studies on 3D printing adoption in Switzerland, manufacturing sector trends, circular economy transitions, and energy-efficient building retrofitting strategies. Her work integrates quantitative methods with spatial analysis, addressing topics such as innovation networks, municipal building consultancy systems, and policy evaluation. She has contributed to collaborative projects like the European Manufacturing Survey and the UNESCO Biosphere Entlebuch advisory program. Key publications include works on regional economic networks, servitization in manufacturing, and data literacy for designers.