جستجوی استاد راهنمای دانشگاهی

Lars Hornuf is a Professor of Finance and Financial Technology at Dresden University of Technology. His research focuses on FinTech, artificial intelligence in finance, space economics, entrepreneurial finance, and blockchain technologies. He has contributed extensively to understanding the dynamics of crowdfunding, regulatory frameworks for financial innovation, and the ethical implications of AI-driven financial systems. Key areas of expertise include the economic impact of emerging technologies like generative AI and humanoid robots in banking, cybersecurity in blockchain ecosystems, and geopolitical aspects of space exploration funding. His work bridges academic research with practical applications, often collaborating with institutions like the Max Planck Institute and CESifo. He has received recognition for his paper 'How Do Banks Interact with Fintech Startups?' which won the Best Paper Award at the International FinTech, InsurTech & Blockchain Forum. His research frequently highlights the dual challenges and opportunities of integrating AI and data-driven tools into financial decision-making while addressing regulatory and ethical concerns. Lars Hornuf’s interdisciplinary approach spans corporate finance, entrepreneurial finance, and policy analysis, with a particular emphasis on fostering innovation while ensuring consumer protection and sustainable development.

• FinTech
• Artificial Intelligence
• Space Economics
• +۳ مورد دیگر

Prof. Marco Hutter is a Full Professor at the Department of Mechanical and Process Engineering at ETH Zürich, and Deputy Head of the Institute for Robotics and Intelligent Systems. His research focuses on advanced robotics, including autonomous legged systems, robotic perception, and control strategies for challenging environments. He leads projects in areas such as forest inventory using legged robots, space exploration robotics, and mobile manipulation systems. His work emphasizes real-world deployment, with contributions to robotic navigation, sensor integration, and policy optimization. Prof. Hutter collaborates on large-scale datasets and frameworks like ROS-LLM for embodied AI, and explores applications in logistics, construction, and planetary exploration. His team develops both hardware (e.g., LEVA logistic vehicles) and software solutions (e.g., risk-guided diffusion models for safety-critical systems). Key projects include ETHcavation (construction environment understanding) and TartanGround (robot perception datasets). He pioneers work in agile locomotion policies, magnetic climbing robots, and multi-agent robotic teams for parcel delivery. His research bridges theoretical advancements with practical implementations, addressing challenges in terrain adaptation, energy efficiency, and robustness in autonomous systems.

• Robotics
• Intelligent Systems
• Autonomous Navigation
• +۴ مورد دیگر

Klaas Stephan is a Full Professor at the Department of Information Technology and Electrical Engineering, ETH Zurich, holding the Chair for Translational Neuromodeling. Based in office WIL G 203 at Wilfriedstrasse 6, 8032 Zürich, Switzerland, he leads research at the intersection of engineering and neuroscience with contact details including phone +41 44 634 91 25 and email stephan@biomed.ee.ethz.ch. His work pioneers computational approaches to decode brain function and psychiatric disorders through advanced neuroimaging techniques. Key research thrusts include: Development of translational neuromodels bridging theoretical neuroscience and clinical applications Innovative fMRI data analysis methodologies for high-resolution brain mapping Computational frameworks for psychiatric diagnosis and treatment personalization Integration of machine learning with neuroimaging to identify biomarkers Professor Stephan teaches specialized courses including Computational Neuroimaging Clinic (227-0967-00L), Methods & Models for fMRI Data Analysis (227-0969-00L), and Computational Psychiatry (227-0971-00L) for Autumn Semester 2025, training students in cutting-edge neurotechnology. His research directly informs clinical neuroscience practice through ETH Zurich's biomedical engineering ecosystem.

• Computational Neuroscience
• Translational Neuromodeling
• Neuroimaging
• +۳ مورد دیگر

Franz-Josef Haug is a Senior Scientist and Senior Lecturer at École Polytechnique Fédérale de Lausanne (EPFL), specifically within the School of Engineering (STI) and the Photovoltaics and Thin Film Electronics Laboratory (PV-LAB). He also serves as a member of the EPFL teacher council (CCE). His research focuses on photovoltaic technologies, particularly silicon solar cells and passivating contacts. He has multiple teaching responsibilities including courses on modern photovoltaic technologies. Dr. Haug's educational background includes: Dipl. Phys. in Physics from University of Ulm (Germany), 1996 Dr. Sc. Nat. in Physics from Swiss Federal Institute of Technology (ETH) Zürich, 2001 His research interests span multiple areas in renewable energy and semiconductor physics, with a strong focus on photovoltaic technologies. He specializes in the development of passivating contacts for crystalline silicon solar cells, using thin silicon films as contact layers. His work also encompasses optics, charge transport in semiconductors, and various aspects of thin film electronics for solar energy conversion. Dr. Haug has made significant contributions to the field of photovoltaics through his extensive publication record. His recent work focuses on TOPCon solar cells, passivating contacts, boron emitters, and high-temperature processing techniques. He has also explored applications of machine learning in solar cell design and investigated alternative materials like zinc phosphide and indium gallium nitride for next-generation photovoltaic devices. His scientific achievements include numerous publications in high-impact journals, though specific awards are not mentioned in the available information. Dr. Haug has supervised multiple PhD students including Hurni Julien, Biron Rémi, Genç Ezgi, Lehmann Mario Joe, Libraro Sofia, Naqavi Ali, Nogay Gizem, Stückelberger Josua Andreas, Stückelberger Michael Elias, and Söderström Karin. His teaching responsibilities include the course 'Modern photovoltaic technologies,' which covers fundamental physics, device operation, and technological development of various solar cell technologies. He is actively involved in the academic community through his membership in the EPFL teacher council (CCE), where he represents the interests of intermediate staff and advocates for concerns of satellite campuses.

• Solar Cell Technology
• Photovoltaics
• Renewable Energy
• +۳ مورد دیگر

Simon Henein is an Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL) , leading the Micromechanical and Horological Design Laboratory (INSTANT-LAB) under the School of Engineering and Institute of Mechanical Engineering . Since 2024, he holds a Courtesy Appointment at the Digital Humanities Institute (DHI-GE) . He was Tenure Chairholder at Patek Philippe (2012–2020) and a Visiting Professor at the University of Lausanne's Centre d'études théâtrales (2020–2021). His research bridges micromechanical design and creative pedagogy , focusing on flexure mechanisms for aerospace, biomedical devices, and horology, alongside improvisational arts in education. He has authored over 25 peer-reviewed journal articles and 60+ conference papers , with 35 patents. Notable awards include the Best Teacher Award (2023) , OMEGA Scientific Prize (1996) , and Maillefer SA Award (1996) . His teaching involves 12 ECTS credits annually with over 200 students , including mentorship of 26 Master’s and 60 semester projects . He has directed 6 completed PhD theses and currently supervises 4 PhD students , co-supervising 1 more. His lab, INSTANT-LAB, comprises a dozen researchers focusing on centimeter-scale mechanisms with novel kinematics and technologies.

• Micromechanical Design
• Precision Mechanisms
• Flexure Guidance Systems
• +۸ مورد دیگر

Jean-Marc Odobez is a Senior Scientist at the IDIAP Research Institute and Adjunct Professor at the Swiss Federal Institute of Technology Lausanne (EPFL), where he is affiliated with the School of Engineering and serves on the Electrical Engineering Doctoral committee (EDEE). He leads the Perception & Activity Understanding Group at Idiap and has extensive teaching responsibilities across multiple departments. Dr. Odobez received his PhD in Computer Science from Rennes University in 1994. His research focuses on multimodal perception systems combining computer vision, statistical machine learning, and deep learning for activity recognition, behavior understanding, and human-robot interaction. His work spans diverse application domains including human health assessment, social robotics, and media content analysis. His recent research shows strong trends in gaze estimation, human activity recognition, and multimodal processing. His team has developed innovative solutions for gaze tracking, head pose estimation, and activity recognition using depth sensors and neural networks. His work increasingly bridges computer vision with digital humanities, particularly in the analysis of ancient Maya glyphs. IEEE member Associate Editor of Machine Vision and Applications journal Dr. Odobez has supervised numerous PhD students and serves as a committee member for the Electrical Engineering Doctoral program. He has been principal investigator for over 16 European and Swiss research projects and has worked on 10 technology transfer projects with SMEs. He co-founded Klewel SA and Eyeware SA, focusing on eye tracking and attention modeling technologies. His research group actively collaborates with industry partners and maintains strong connections with the computer vision and human-computer interaction research communities.

• Computer Vision
• Machine Learning
• Deep Learning
• +۶ مورد دیگر

Laurence Brandenberger is a Senior Researcher at the Chair of Systems Design, ETH Zurich. He holds a PhD and Master's degree in Political Science and Sociology from the University of Bern. His research focuses on legislative politics, political networks, and temporal dynamics of political collaboration. He employs computational methods like machine learning and network analysis to study decision-making processes and democratic transparency. Notable contributions include analyzing Swiss parliamentary records and developing relational event models. His work bridges theoretical insights with practical tools for enhancing political transparency, such as the DemocraSci Knowledge Graph. Education: PhD in Political Science (University of Bern), MA in Sociology (University of Bern) Affiliations: Chair of Systems Design, ETH Zurich His research interests prioritize understanding how social relations influence political decisions, spill-over effects in policy-making, and strengthening democratic transparency through accessible data platforms. He has authored multiple studies on legislative behavior, policy networks, and computational methodologies in political science.

• Political Science
• Legislative Politics
• Political Networks
• +۴ مورد دیگر

Prof. Dr. Tilmann Altwicker is an Associate Professor and Chair of Legal Data Science and Public Law at the University of Zurich's Faculty of Law. He leads the Center for Legal Data Science (CLDS) and previously held an SNSF professorship (2017–2023). His research focuses on applying data science to legal data, including statistical and machine learning methods to analyze judgments, legislative acts, and legal trends. He earned his doctorate in law from the University of Mannheim (2010) and a Habilitation in Public Law from the University of Basel (2018). His work bridges law, statistics, and digitalization, emphasizing evidence-based legal studies. Education: PhD in Law (Dr. iur.), University of Mannheim (2010) Habilitation (Venia Legendi) in Public Law, University of Basel (2018) Diploma in Applied Statistics, ETH Zurich (2017) LL.M. in Human Rights, Central European University (2005–2006) Research Interests: Altwicker's work centers on legal data science, including the collection, analysis, and ethical use of legal data. He explores intersections of law with statistics and machine learning, particularly in empirical legal studies. His projects address digitalization's impact on legal knowledge production, human rights interpretation, and transnational security law. Key Contributions: Pioneer in applying quantitative methods to legal research, such as analyzing ECtHR decisions and Swiss trademark opposition proceedings Leadership in the CLDS to advance legal data science as a field Educational initiatives, including courses on legal data science and statistical text analysis Awards and Grants: SNSF Ambizione Research Group Leader (2013–2017) SNSF Professorship (2017–2023) Peer Review Prize, European Journal of International Law (2020) Professional Activities: He serves as a Review Panel Expert for EU COST and has held visiting professorships at the University of St. Gallen. His work spans empirical legal studies, international human rights law, and security law, with frequent contributions to interdisciplinary conferences and publications in top journals like the European Journal of International Law and Artificial Intelligence and Law.

• Legal Data Science
• Law & Statistics
• Law & Machine Learning
• +۳ مورد دیگر

Melika Payvand is an Assistant Professor at the Institute of Neuroinformatics, University of Zurich and ETH Zurich, leading the Emerging Intelligent Substrates lab. She holds MSc and PhD degrees in Electrical and Computer Engineering from the University of California, Santa Barbara (2012 and 2016). Her research focuses on understanding natural intelligence and translating its principles into efficient artificial intelligence systems, particularly exploring hierarchical structures and memristive devices to reduce AI operational costs. She received the 2023 Swiss National Science Foundation Starting Grant and is actively involved in neuromorphic initiatives, including co-coordinating the NEUROTECH project and co-chairing the International Conference on Neuromorphic Systems (ICONS). Her work bridges neuroscience and engineering, emphasizing neuromorphic computing’s potential for scalable and energy-efficient AI. Key contributions include developing the Neurobench benchmarking framework and advancing 3D integration for neuromorphic systems. She also chairs the Neural Systems and Applications committee of the IEEE Circuits and Systems Society, reflecting her leadership in the field. Research interests span neuromorphic architectures, memristive technologies, and spiking neural networks. She has pioneered studies on temporal hierarchy, in-memory computing, and hardware-aware training methods. Her lab’s interdisciplinary approach integrates circuit design, machine learning, and neurobiology to create next-generation intelligent systems.

• Neuroinformatics
• Artificial Intelligence
• Neuromorphic Computing
• +۵ مورد دیگر

Michael Wolf is a Professor of Econometrics and Applied Statistics at the University of Zurich's Department of Economics, where he has been since 2005. He holds a Vordiplom in Mathematics from the University of Augsburg (1991), an MSc in Statistics from Stanford University (1995), and a PhD in Statistics from Stanford (1996). His research focuses on nonparametric inference methods, multiple testing procedures, financial econometrics, and large-dimensional covariance matrices. He has contributed to influential work on covariance matrix estimation, portfolio optimization, and statistical methodology. Wolf has served as an Associate Editor for journals including the Annals of Statistics (2004–2007), Statistics and Probability Letters (2014–2016), and the Journal of Financial Econometrics (2019–2022). His academic career includes roles at institutions like UCLA, Universidad Carlos III, and Universitat Pompeu Fabra, where he advanced from Assistant to Associate Professor before joining UZH. His research explores resampling techniques, financial markets analysis, and statistical methods for handling high-dimensional data. Notable contributions include the development of shrinkage-based covariance matrix estimators and their applications in portfolio management. He collaborates with researchers like Olivier Ledoit on nonlinear shrinkage methods and maintains software packages like covShrinkage for covariance matrix estimation. Wolf advises students on thesis topics in econometrics and maintains active roles in professional associations such as the American Statistical Association and the Institute of Mathematical Statistics. His work bridges theoretical statistics and applied finance, addressing challenges in modern portfolio theory, risk management, and statistical inference.

• Nonparametric Inference Methods
• Multiple Testing Procedures
• Financial Econometrics
• +۴ مورد دیگر

Christophe Pérignon is a Professor and Associate Dean for Research at HEC Paris, a leading business school in France. He is affiliated with the Finance Department and has established himself as a prominent scholar in financial risk management, systemic risk, and computational reproducibility in finance. His work bridges academic research with practical applications in banking regulation and risk management. His research spans several critical areas in modern finance: Advanced risk management methodologies, particularly Value-at-Risk (VaR) modeling and validation Systemic risk measurement and financial regulation frameworks Computational reproducibility in financial research through multi-analyst studies Machine learning applications in banking and credit scoring Ethical considerations in algorithmic finance Professor Pérignon's recent work demonstrates a significant shift toward examining the reproducibility crisis in financial research and the integration of machine learning techniques into traditional risk management frameworks. His influential paper "Nonstandard Errors" in the Journal of Finance (2024) examines how different research teams approach the same financial questions, highlighting methodological challenges in the field. He has also pioneered tools like "The Risk Map" for validating risk models, which has practical applications for financial institutions. His scholarly impact is substantial, with over 38 published papers that have collectively received more than 50,000 downloads and 499 citations on SSRN, placing him among the top researchers in finance. His collaborative work spans multiple international institutions, reflecting the global nature of financial research and regulation. As Associate Dean for Research at HEC Paris, Professor Pérignon plays a key leadership role in shaping the research agenda of one of Europe's premier business schools. His work continues to influence both academic discourse and practical risk management approaches in the financial industry worldwide.

• Risk management
• Systemic risk
• Value-at-Risk (VaR)
• +۶ مورد دیگر

Norman Schuerhoff is a Professor at the Swiss Finance Institute - HEC Lausanne, specializing in finance, corporate governance, and over-the-counter (OTC) market dynamics. His research spans capital structure, liquidity, market microstructure, and financial intermediation. Institutional Affiliations Swiss Finance Institute - HEC Lausanne University of Lausanne - School of Business and Economics Research Interests Liquidity and Market Microstructure Capital Structure and Corporate Governance Over-the-Counter Financial Markets Financial Intermediation and Trading Costs Applications of AI in Finance Recent Article Trends Focus on OTC market liquidity and AI-driven governance Examines real options, asymmetric information, and institutional impacts Keywords include finance, corporate bonds, market microstructure, and inverse reinforcement learning Scientific Contributions Co-authored 30+ scholarly papers with 41,814 downloads Research on municipal bonds, repo markets, and default recovery

• Finance
• Corporate Finance
• Financial Markets
• +۹ مورد دیگر

Julian Thimme is a researcher affiliated with the Karlsruhe Institute of Technology , specifically within the Department of Finance under the School of Business and Economics . His academic work focuses on asset pricing, financial econometrics, and volatility modeling, with an emphasis on empirical and quantitative methods. Education: Information not explicitly provided in the text. His research spans asset pricing anomalies, options markets, and the implications of consumption and macroeconomic factors on financial returns. He frequently employs advanced statistical techniques such as Generalized Method of Moments (GMM) and textual analysis of news data to explore these topics. Collaborations with scholars like Christian Schlag and Alexis Marchal highlight his interdisciplinary approach. Julian has published extensively in journals like the Journal of Finance and institutions including the Swiss Finance Institute , focusing on volatility-of-volatility risk, intertemporal substitution, and the effects of ambiguity on asset prices. While no specific prizes are listed, his papers have been widely downloaded, indicating significant academic impact.

• Asset Pricing
• Quantitative Finance
• Volatility Analysis
• +۳ مورد دیگر

Dacheng Xiu is a Professor at the University of Chicago Booth School of Business and affiliated with the National Bureau of Economic Research (NBER). His research spans finance, machine learning, and econometrics, focusing on asset pricing, volatility modeling, and high-frequency data analysis. His work includes developing machine learning frameworks for financial applications, such as return prediction, factor models, and text mining of market data. Recent publications emphasize leveraging large language models (e.g., BERT, GPT) and deep learning architectures (e.g., autoencoders) to address challenges in empirical asset pricing and portfolio optimization. He has collaborated extensively with scholars like Bryan T. Kelly and Stefano Giglio, contributing to high-impact journals and working papers. His research also explores the statistical limits of arbitrage and weak signal detection in financial markets, with applications to risk premium estimation and factor zoo regularization.

• Finance
• Machine Learning
• Asset Pricing
• +۶ مورد دیگر

Donald Glowinski is a Senior Lecturer and Senior Researcher at the Swiss Center for Affective Sciences (University of Geneva), where he coordinates the Music & Science team and leads a consortium investigating the cognitive and emotional impact of DEMOS orchestras on children. His work bridges neuropsychology, music performance, and applied research to enhance team coordination and resilience in professional settings. He holds an MSc in Cognitive Science (EHESS), Music and Acoustics (CNSMDP), and Philosophy (Sorbonne-Paris IV), with a PhD in Computing Engineering from the University of Genoa. His research focuses on music’s role in emotions, group creativity, and translational science, including developing immersive virtual environments and curricula for interdisciplinary training. He is also involved in public engagement through initiatives like culturehack.art and collaborations with festivals such as Montreux Jazz and NIFFF. Key research interests include the interplay between music, emotion, and social dynamics. He explores how music ensemble performances can model adaptive teamwork, leveraging technologies like virtual reality to simulate real-world scenarios. His projects emphasize practical applications, such as improving safety training for workers and fostering resilience in high-pressure environments. Awards include the Prix pour la Vocation (Bleustein-Blanchet Foundation) and the Declic Award (Fondation de France). He actively contributes to scientific dissemination through public talks and cultural partnerships, advocating for science that directly informs tangible, accessible tools for diverse communities. His advisory roles include coordinating the Music & Science team and leading the DEMOS consortium with the Philharmonie de Paris. He also spearheads a new psychology curriculum using high-fidelity simulations, reflecting his commitment to bridging academic and applied domains.

• Music and Emotions
• Group Creativity
• Neuropsychology
• +۶ مورد دیگر