جستجوی استاد راهنمای دانشگاهی

Prof. Dr. Julia Vogt is an Assistant Professor at the Department of Computer Science at ETH Zürich, leading the Professur für Medizin. Datenwiss. Her research focuses on medical machine learning, data science, and AI applications in healthcare. She specializes in developing interpretable AI systems for clinical decision support, particularly in pediatric diabetes management, medical imaging analysis, and anomaly detection. Her work bridges translational gaps by emphasizing causal approaches and clinical validation. Her academic role includes teaching courses like the Data Science Lab (263-3300-00L/10L) and Topics in Medical Machine Learning (263-5100-00L). Her lab's research spans predictive modeling for nocturnal hypoglycemia, echocardiogram analysis for pulmonary hypertension detection, and multimodal learning in radiology. She also contributes to national pediatric data initiatives like SwissPedHealth. Key technical areas include concept bottleneck models, stochastic AI frameworks, and generative models for medical signal denoising. Her work often emphasizes model interpretability, fairness, and robustness to distribution shifts. She collaborates on projects involving wearable devices for pediatric monitoring and AI-driven rehabilitation tools for post-stroke gait analysis.

• Medical Machine Learning
• Data Science
• Artificial Intelligence in Healthcare
• +۳ مورد دیگر

Gustavo Valverde Mora is a Lecturer at ETH Zurich's Power Systems Laboratory in the Department of Information Technology and Electrical Engineering. His research focuses on distributed energy resources, smart grid technologies, and power system control, with expertise in behind-the-meter DER integration and hosting capacity analysis. His recent work addresses key challenges in renewable energy integration, including voltage control coordination between transmission and distribution networks, data-driven local control schemes for active distribution grids, and unsupervised load disaggregation techniques using smart meter data. He has developed novel methods for DER modeling, GIS-based system analysis, and distribution network planning. Recognized with multiple awards including the 2022 Costa Rican National Technology Award, he actively contributes to IEEE Task Forces on DER integration. His research demonstrates strong emphasis on practical grid applications, combining theoretical power systems knowledge with advanced data analytics. Dr. Valverde teaches Power System Analysis (227-0526-00L) and maintains collaborations with utilities worldwide on renewable integration challenges.

• Power Systems
• Distributed Energy Resources
• Smart Grids
• +۳ مورد دیگر

Adam B. Badawi is a Professor of Law at the University of California, Berkeley - School of Law, where he maintains an active research agenda at the intersection of law, finance, and corporate governance. His scholarly work has established him as a leading expert in contract law, M&A transactions, securities litigation, and ESG compliance. Professor Badawi's research interests span multiple dimensions of corporate law and legal theory. His work on contractual complexity, particularly in debt agreements and M&A transactions, has provided significant insights into how legal drafting affects economic outcomes. He has extensively examined the business judgment rule, board authority, and the role of courts in corporate governance. More recently, his research has expanded into ESG-related topics, analyzing how environmental, social, and governance considerations intersect with traditional corporate law frameworks. His methodological approach often combines legal analysis with empirical techniques, including text analysis of legal documents and event studies of litigation outcomes. Professor Badawi's scholarly output demonstrates consistent high-impact research across multiple domains of corporate law. His early work focused on foundational aspects of contract theory and interpretation, while his more recent publications reflect growing interest in ESG metrics, executive compensation structures tied to sustainability goals, and the evolving regulatory landscape. The trajectory of his research shows a progression from theoretical legal analysis toward increasingly empirical and interdisciplinary approaches that bridge law with finance and data science. Professor Badawi has collaborated with numerous scholars across different institutions, including Duke University, Stanford Law School, and the University of Chicago Law School, reflecting the interdisciplinary nature of his work and its relevance to multiple academic communities.

• Contract Law
• Corporate Law
• Mergers and Acquisitions
• +۵ مورد دیگر

Prof. Dr. Jing Wang is a Full Professor at the Department of Civil, Environmental and Geomatic Engineering at ETH Zürich. His research focuses on air pollution control, nanoparticle transport, and environmental health and safety (EHS) impacts of nanomaterials. He has held roles including Assistant Professor at ETH Zürich (2010–present), Research Assistant Professor at the University of Minnesota (2007–2010), and postdoctoral associate in Particle Technology (2005–2007). Education: Bachelor’s in Engineering (2000) – Tsinghua University, Beijing Master’s in Computer Sciences (2003) – University of Minnesota PhD in Aerospace Engineering (2005) – University of Minnesota Research Interests: Air/water filtration technologies Nanoparticle emission reduction and measurement Multiphase flow mechanics Environmental impacts of nanomaterials Collaborations: Industrial partnerships include 3M, BASF, Boeing, Intel, Samsung, and others in nanoparticle measurement and filtration solutions. Honors: 2011 Smoluchowski Award (Association for Aerosol Research) 2006 ‘Best Dissertation’ Award (University of Minnesota) 2004 Doctoral Dissertation Fellowship Teaching: Courses include Air Pollution Control, Environmental Engineering Seminars, and Excursions for Environmental Engineers. Labs/Teams: Leads the Particle Technology Lab and collaborates with the Institute of Environmental Engineering at ETH Zürich.

• Air Pollution Control
• Nanoparticle Transport
• Emission Reduction
• +۴ مورد دیگر

Benjamin J. Keys is a Research Associate at the University of Pennsylvania's Wharton School within the Public Economics program. His work focuses on public economics, environmental economics, and financial risk management with particular emphasis on housing markets and climate change impacts. University of Pennsylvania - The Wharton School Public Economics Department His research explores: Climate risk capitalization in housing markets Mortgage insurance moral hazard Consumer credit card payment behaviors Emergency credit systems Regional economic redistribution through mortgages Email: benkeys@wharton.upenn.edu Scientific awards include: Fellowships on Consumer Financial Management

• Public Economics
• Environmental Economics
• Housing Markets
• +۴ مورد دیگر

Frédéric Kaplan serves as Director of the College of Humanities at École Polytechnique Fédérale de Lausanne (EPFL), where he holds the Chair of Digital Humanities. He also serves as President of the Time Machine Organisation, a nonprofit entity comprising over 600 institutions. His academic appointments span multiple departments including the Digital Humanities Laboratory (DHLAB), School of Architecture (SAR), and School of Humanities (SODH), demonstrating his interdisciplinary leadership across EPFL's academic structure. Dr. Kaplan's research focuses on the intersection of computational methods and humanities, particularly in historical urban analysis, cultural heritage digitization, and the development of the Mirror World concept. His work bridges computational techniques with historical scholarship, creating new methodologies for analyzing historical documents, maps, and urban structures through advanced digital tools. His research has significant implications for how we understand and reconstruct historical urban environments and cultural heritage. His publication record reveals a strong emphasis on computational approaches to historical data, with recent work focusing on LLM applications for historical cadastre navigation, historical map analysis through deformation patterns, 4D city modeling, and language technology applications for historical document processing. This research trajectory demonstrates an evolving focus from basic digitization toward sophisticated analytical frameworks that extract deeper historical insights from digital representations. Kaplan has supervised numerous doctoral students whose work spans digital heritage applications, historical document analysis, computational cartography, and language technology. His research has been supported through multiple institutional frameworks at EPFL and has resulted in practical applications demonstrated through exhibitions at major institutions including the Venice Architecture Biennale, Grand Palais, Centre Pompidou in Paris, and the Museum of Modern Art in New York. He leads the Digital Humanities Laboratory (DHLAB) which serves as a nexus for computational approaches to humanities research. The lab focuses on developing methodologies for historical data analysis, creating digital tools for cultural heritage institutions, and exploring the theoretical implications of computational approaches to historical scholarship. The lab's work with the Time Machine Organisation represents one of the most ambitious efforts to create comprehensive digital reconstructions of historical urban environments.

• Digital Humanities
• Computational History
• Historical Map Analysis
• +۴ مورد دیگر

Matthieu Cord is a Professor at Sorbonne University and Scientific Director of valeo.ai, leading research in computer vision, deep learning, and computational cooking. He heads the MLIA team at ISIR Lab, focusing on multimodal models, transformers, and efficient architectures. Research areas include computer vision, large language models with vision, and AI-driven food analytics. Key projects: VISA-DEEP AI chair, Foundation VaViM models, and SmolVLA collaboration with Hugging Face. His recent work examines scalable multimodal models , trajectory prediction , and diffusion-based segmentation , with studies on in-context learning and biased shortcut learning in visual question answering. Articles highlight DeiT variants , fishr for OoD generalization , and STEEX for counterfactual explanations . Scientific awards include IUF Honorary Membership (2009), BMVC 2017 Best Paper, and ICIP 2018 Best Paper. As an advisor, he supervised PhD theses on topics like GAN editing , semantic segmentation , and multimodal retrieval . Current roles involve mentoring the 'Research Band' at MLIA and leading EU-funded initiatives like SCAPE. His work bridges theoretical AI exploration with practical applications in autonomous driving and food technology.

• Computer Vision
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Prof. Claudio J. Tessone is a Professor of Blockchain and Distributed Ledger Technologies at the Department of Informatics, University of Zurich. He serves as Head of the Blockchain and Distributed Ledger Technologies group, Chairman of the UZH Blockchain Center, and is incharge of the NetSci Society. His academic background includes a PhD in Physics (Complex Systems) and an Habilitation in Complex Socio-Economic Systems from ETH Zurich. Education: PhD in Physics (2006): Thesis on synchronization in stochastic systems, Universitat de les Illes Balears, Spain Habilitation (2015): Thesis on agent-based modeling of socio-economic systems, ETH Zurich Master in Physics (1999): Thesis on stochastic resonance, Instituto Balseiro, Argentina Research Interests: Prof. Tessone specializes in modeling complex socio-economic and socio-technical systems, with a focus on blockchain-based systems. His work explores crypto-economics, blockchain scalability, decentralized finance (DeFi), and the interplay between micro-level agent behavior and macro-level emergent properties. Notable areas include transaction network analysis in Bitcoin/Ethereum, consensus mechanisms (Proof-of-Stake/Work), and blockchain governance models. Publications Trends: Recent articles emphasize empirical blockchain analysis (e.g., Ethereum microvelocity, Bitcoin mesoscopic structure), DeFi arbitrage strategies, and privacy-preserving blockchain applications in healthcare. His work bridges theoretical agent-based models with real-world blockchain datasets, addressing both technical and socio-economic dimensions of distributed ledger technologies. Grants & Labs: Director of the UZH Summer School on Blockchain and Certificate of Advanced Studies program. Active in interdisciplinary collaborations through the URPP Social Networks (2015–2021) and ETH Zurich’s Systems Design group (2007–2014). Labs/Initiatives: Leads the UZH Blockchain Center, a hub for academic-industry research on blockchain applications in finance, governance, and digital transformation.

• Blockchain Technology
• Cryptocurrency Systems
• Complex Socio-Economic Systems
• +۵ مورد دیگر

Prof. Dr. Beat Hintermann is a Professor of Public Finance at the University of Basel's Faculty of Business and Economics (WWZ). His research focuses on public sector economics with particular emphasis on climate policy and mobility behavior. Hintermann leads empirical research using GPS tracking data to study transportation choices and the effectiveness of pricing mechanisms to encourage sustainable mobility options. His research interests span several interconnected areas: public sector economics, climate policy design, transportation economics, and environmental economics. He investigates how pricing mechanisms can influence individual behavior to reduce environmental externalities, with special attention to sustainable mobility solutions like e-biking. His work often combines economic theory with rich empirical analysis of real-world data, particularly examining the intersection of environmental policy and individual decision-making. Hintermann's recent publications reveal a strong focus on empirical mobility studies, particularly through the MOBIS dataset that tracks mobility behavior in Switzerland. His research shows how transport pricing can effectively promote e-biking and reduce negative externalities. He has also conducted significant work on carbon pricing mechanisms, emissions trading systems, and the impacts of climate policies on economic behavior. His work during the pandemic period examining mobility changes provides valuable insights into how external shocks affect transportation choices. Hintermann's research methodology is characterized by rigorous empirical analysis, often employing field experiments and large-scale GPS tracking data to measure behavioral responses to policy interventions. His work on Pigovian transport pricing represents an important contribution to understanding how economic instruments can be designed to address environmental externalities in the transportation sector. As part of the University of Basel's Faculty of Business and Economics, Hintermann contributes to research centers focused on sustainable development and environmental economics. His work bridges academic research with practical policy applications, providing evidence-based insights for policymakers designing effective environmental and transportation policies.

• Public Sector Economics
• Climate Policy
• Transportation Economics
• +۴ مورد دیگر

Thomas Demeester is an Associate Professor at the Internet Technology and Data Science Lab (IDLab), Ghent University - imec, Belgium. Appointed as Assistant Professor in 2019, he leads an AI research group focused on health applications and drug design, co-directing the Text-to-Knowledge research cluster with Prof. Chris Develder. His educational background includes: M.Sc. in Electrical Engineering from Ghent University (2005), completed with thesis work at ETH Zurich Ph.D. in Computational Electromagnetics from Ghent University (2009), funded by Research Foundation - Flanders (FWO) Demeester's research spans artificial intelligence with emphasis on deep learning and neuro-symbolic methods. Current tracks include energy-based models (Hopfield Networks, Deep Equilibrium Models), diffusion models for drug design, and clinical reasoning systems. His work bridges NLP, healthcare informatics, and generative AI with strong industry partnerships. Recent publications (2023-2025) reveal strategic expansion from NLP into health-centric AI: BioLORD biomedical encoders (2023), synthetic medical data frameworks (UAI/NeurIPS 2024), and novel diffusion model guidance (ICLR 2025). This evolution demonstrates convergence of generative modeling, clinical data analysis, and protein design. He actively mentors 24 PhD students across diverse AI domains: Current Research: Conversational agents, emotion analysis, clinical reasoning, antibody design, and diffusion model optimization Recent Graduates: Interpretable language models, biomedical semantics, task-oriented dialogue, and social media knowledge extraction Research is supported by imec funding and collaborations with Flemish biotech companies, building on his post-doctoral experience securing media-sector projects. Within IDLab, he co-leads the Text-to-Knowledge cluster driving NLP innovations for healthcare, legal, and economic applications.

• Artificial Intelligence
• Natural Language Processing
• Deep Learning
• +۷ مورد دیگر

George Candea is an Associate Professor at the École polytechnique fédérale de Lausanne (EPFL) and heads the Dependable Systems Laboratory (DSLAB). He also holds teaching roles in the School of Computer and Communication Sciences, focusing on computer science, communication systems, and software engineering. Education: PhD in Computer Science (2005) from Stanford University; B.S. and M.Eng. in Electrical Engineering and Computer Science (1997, 1998) from MIT. His research centers on achieving reliability, security, and predictable performance in complex software systems. He has pioneered concepts like 'crash-only software' and 'microrebooting' to enhance system resilience. His work spans theoretical foundations and practical implementations, addressing scalability challenges in real-world systems. George has co-founded two technology companies: Cyberhaven (2016, cybersecurity) and Aster Data Systems (now Teradata Vantage , big-data analytics). He actively contributes to academic governance as a member of EPFL's Innovation Council (2017-2021) and Innogrant committee (2018-2022). Scientific Awards: 2024: ACM Mark Weiser Award 2014: ACM Eurosys Jochen Liedtke Young Researcher Award 2005: MIT TR35 Young Innovators Award 2011: ERC Starting Grant Multiple Best Paper Awards at ASPLOS, USENIX NT, and SIGCOMM KBNets He has advised numerous PhD students and served on program committees for top conferences like SOSP, OSDI, and ASPLOS. His work bridges academia and industry through startups and collaborations with tech giants.

• Dependable Systems
• Software Reliability
• Cybersecurity
• +۷ مورد دیگر

Dr. Marcel Dettling is a Group Lead in Data Analysis and Statistics at the ZHAW School of Engineering , focusing on predictive analytics, applied statistics, and complex data analysis. He also serves as a Lecturer at ETH Zurich , teaching advanced statistical methods. Education : PhD in Mathematics (2000-2004), ETH Zurich Postdoc in Applied Statistics (2004-2006), Johns Hopkins University His research spans predictive analytics (regression, classification, time series), data mining, and applications in health economics, transportation safety, social sciences , and business analytics . Recent work includes pharmaceutical cost group analysis for Swiss healthcare and predictive maintenance for marine vessels. Selected publications highlight his expertise in flight trajectory modeling , deep learning error mitigation , and statistical frameworks for rehabilitation finance . His projects address diverse fields like crowdworking in nursing, energy optimization for shipping, and customer behavior prediction.

• Predictive Analytics
• Applied Statistics
• Data Mining
• +۶ مورد دیگر

Jan Dirk Wegner is an Associate Professor at the University of Zurich, holding the chair in 'Data Science for Sciences' and leading the EcoVision Lab. He previously served as a Postdoc (2012–2016) and senior scientist (2017–2020) at ETH Zurich's Photogrammetry and Remote Sensing Group, following his PhD (with distinction) from Leibniz University Hannover (2011). His research bridges machine learning, computer vision, and remote sensing to address environmental and geoscience challenges, focusing on large-scale environmental data analysis, vegetation monitoring, and climate change mitigation. Education: PhD (with distinction) in Geodesy, Leibniz University Hannover (2011) Postdoc, ETH Zurich (2012–2016) Senior Scientist, ETH Zurich (2017–2020) Research Interests: Machine Learning, Computer Vision, Remote Sensing, Environmental Science, Climate Science, Geosciences, Explainable AI, Uncertainty Quantification, and Applications in Sustainability. The EcoVision Lab develops data-driven methods for global-scale environmental monitoring, including vegetation parameter mapping, flood prediction, forest degradation detection, and AI-driven ecological modeling. Awards: ETH Postdoctoral Fellowship (2012–2016) Science Prize of the German Geodetic Commission WEF Young Scientist Class 2020 (Top 25 globally under 40) Advising & Leadership: Director of the University of Zurich's Doctoral School in Data Science, leading the EcoVision Lab, and coordinating the CVPR EarthVision Workshops. His roles include Vice President of ISPRS Technical Commission II, member of the ETH AI Center, ELLIS, and UN-ETH Partnership. Labs/Teams: EcoVision Lab focuses on interdisciplinary AI applications for environmental challenges, collaborating with NGOs, governments, and industry to translate research into societal impact.

• Machine Learning
• Computer Vision
• Remote Sensing
• +۷ مورد دیگر

Professor Nikola Biller-Andorno is a leading academic in biomedical ethics and digital health innovation at the University of Zurich , where she directs the Institute of Biomedical Ethics and History of Medicine and serves as Vice Dean for Innovation and Digitalization at the Faculty of Medicine . Her work bridges cutting-edge technology with ethical frameworks for patient-centered healthcare. Director, Institute of Biomedical Ethics and History of Medicine (WHO Collaborating Centre) Vice Dean for Innovation and Digitalization, Medical Faculty Founding Director, UZH Center for Medical Humanities Chair, PhD program 'Biomedical Ethics and Law' Research Interests focus on digital transformation in healthcare, including ethical implications of AI, patient experience integration via big data, and crisis management frameworks during pandemics. Her scholarship addresses: Digitalization of health systems Algorithmic decision-making ethics Equity in digital health access Scientific Awards include: Commonwealth Fund Harkness Fellowship (2012-2014) Fellowship at Collegium Helveticum (2016-2020) Master of Health Business Administration (2018) Leadership roles in International Association of Bioethics and European Association of Centres of Medical Ethics

• Digitalization of healthcare
• Artificial Intelligence in medicine
• Patient experiences in healthcare
• +۴ مورد دیگر

Martin Volk is a Full Professor of Computational Linguistics at the University of Zurich, with a dual affiliation to the Department of Informatics since 2019. He holds a PhD from the University of Koblenz and has held academic positions at institutions including Stockholm University (part-time from 2008-2011), Zurich University of Applied Sciences, and the University of Georgia. His research focuses on grammar engineering, machine translation evaluation, multilingual text analysis, and cross-language information retrieval. Education : Born in Cochem, Germany Studied Computer Science and Computational Linguistics at EWH University, Koblenz Master's in Artificial Intelligence at the University of Georgia (Fulbright Scholar) PhD in Computational Linguistics from the University of Koblenz Research Interests : His work emphasizes data-driven NLP methods, including corpus-based approaches, parsing technologies, and the application of machine learning to historical and multilingual texts. Key focuses include: Machine translation systems and evaluation frameworks Grammar testing environments (e.g., GTU) OCR and digitization of historical documents (e.g., Gothic script) Development of parallel corpora for linguistic research Projects : SMULTRON: Multilingual parallel treebank project Bullinger Digital: Historical document digitization initiative Text+Berg: Digital Humanities project for alpine textual heritage EU-funded MuchMore (cross-language medical IR) Grants & Collaborations : Recipient of grants from the Swiss National Science Foundation, EU projects, and industry partnerships (e.g., Siemens, Xerox). His work integrates academic and industrial perspectives in NLP tool development. Labs & Teams : Leads research teams in the Institute of Computational Linguistics at UZH, focusing on projects like the Zurich Parallel Corpus Collection and MODERN (modeling discourse for MT).

• Computational Linguistics
• Machine Translation
• Natural Language Processing
• +۵ مورد دیگر