جست‌وجوی استاد و پژوهشگر

Nadine Schellerمشاهده پروفایل

پژوهشگر

• Educational Technology
• Instructional Design
• Digital Media
• +۳ مورد دیگر

Nadine Scheller is a Researcher at the University of Zurich, working at the Chair of Educational Technology in the Swiss National Science Foundation (SNF) project 'SDT4ID' since March 2024. Prior to this role, she held research associate positions at Chemnitz University of Technology, contributing to projects like 'DYNAMIK' (funded by the European Social Fund) and the Collaborative Research Center (CRC) Hybrid Societies. Her academic background includes a Master of Science in Media and Instructional Psychology (2021–2022) with an outstanding grade of 1.0 and a Bachelor of Arts in Media Communication (2017–2021) with a grade of 1.8, both from Chemnitz University of Technology. Her theses focused on measuring state empathy and comparing empathetic reactions in different film formats, specifically Disney remakes. Research Interests span the design and development of digital learning materials, with a focus on emotional design, personalization, and structuring principles in digital media. She integrates self-determination theory into instructional design, examining motivation during learning processes and the role of retrieval practices and cues in enhancing knowledge retention. Her work also explores choice principles in educational technology. Further Activities include serving as a reviewer for the European Association for Research on Learning and Instruction (EARLI) since 2023, and she has been involved in teaching as a tutor at Chemnitz University of Technology.

Charlotte Malterre-Barthesمشاهده پروفایل

عضو هیئت علمی

• Urban Design
• Architectural Education
• Climate Emergency
• +۶ مورد دیگر

Charlotte Malterre-Barthes is a Tenure Track Assistant Professor of Architectural and Urban Design at EPFL, leading the RIOT laboratory. She previously held roles at Harvard GSD and ETH Zurich. Her research focuses on the political economy of space, urban inclusivity, and feminist activism in architecture. She co-founded OMNIBUS, an urban design collective, and chairs initiatives like the Parity Front to advance gender equality in architecture. Education: Ph.D. in Architecture, ETH Zurich (2012–2018) Master of Advanced Studies in Urban Design, ETH Zurich (2008) Architect DPLG, National School of Architecture of Marseille (2004) Research Interests: Her work interrogates climate and social emergencies through urban design, advocating for a moratorium on new construction and anti-extractive practices. She emphasizes feminist, intersectional approaches to reform planning disciplines and architectural education. Awards & Recognition: Schönsten Deutschen Bücher Award 2021 (for Migrant Marseille ) Transfer Video Award 2023 (for Material World: Iron Tail, Iron Tale ) Future Architecture Laureate 2019 (for Curriculum Revolution ) Advocacy & Labs: Co-founded the Parity Front to address gender disparities in architecture. Collaborates with OMNIBUS on community-driven urban projects. Active in curatorial roles (e.g., São Paulo Biennale 2019).

Elisa Oricchioمشاهده پروفایل

دانشیار

• Cancer Genomics
• Epigenetics
• Chromatin Architecture
• +۴ مورد دیگر

Elisa Oricchio is an Associate Professor at EPFL's School of Life Sciences (SV), affiliated with the ISREC Institute and the Department of Life Sciences Engineering. She leads the Oricchio Lab, which focuses on integrating genomic and functional analyses to identify oncogenic mechanisms and design novel therapies. Her research emphasizes the role of chromatin 3D architecture in cancer progression, particularly in lymphomas and solid tumors. Roles: Director of ISREC-GE Unit, Teaching Responsibilities in Life Sciences Engineering and Education Programs Affiliations: EPFL SV ISREC, SV-SSV Education, EDMS Education Program Research Interests: Cancer genomics, epigenetics, chromatin structure-functional relationships, and translational therapies. Key areas include EZH2 mutations' impact on chromatin domains, cathepsin inhibitors for lymphoma treatment, and spatial genomics in cancer heterogeneity. Recent Work Trends: Focus on chromatin 3D organization as a driver of oncogenesis, development of targeted therapies using antibody-peptide conjugates, and understanding tumor evolution through multi-omics approaches. Advisees: Supervises 6 PhD students and has mentored 7 past thesis students Lab Members: Includes scientists, doctoral assistants, and technicians Labs/Teams: Oricchio Lab at EPFL ISREC, collaborating with groups on genomic screens, CRISPR assays, and tumor microenvironment studies.

Alexandre Terrierمشاهده پروفایل

مدرس

• Biomechanics
• Orthopaedic research
• Mechano-biology
• +۵ مورد دیگر

Alexandre Terrier is a Group Leader and Lecturer at the École Polytechnique Fédérale de Lausanne (EPFL), School of Engineering (STI), within the Department of Biomedical Engineering. He leads the Laboratory of Biomechanical Orthopedics (LBO) and holds teaching roles in multiple departments including SSV, EDBB, and SGM. His expertise spans biomechanics, orthopaedic research, and patient-specific modeling. Terrier's research focuses on joint biomechanics, mechano-biology, and finite element analysis, with applications in orthopaedic surgery and implant design. Education: PhD in Biomechanics (EPFL, 1999), MSc in Physics (EPFL, 1994). Professional experience includes roles as Head of the Joint Biomechanics Group (LBO, EPFL, 2006), Post-Doc at Columbia University (1999), and teaching at Lycée cantonal de Porrentruy (1995). Research interests include patient-specific models of human joints, statistical analysis of bone morphology, and prosthetic implant optimization. Over 120 peer-reviewed articles highlight his contributions to shoulder and hip arthroplasty biomechanics, bone strain analysis, and computational modeling. Terrier advises PhD students in biomechanical engineering and leads interdisciplinary projects combining experimental and computational methods. Labs/Teams: Laboratory of Biomechanical Orthopedics (LBO), collaborating with clinical and engineering partners on surgical innovation and implant development.

• International Relations
• East Asia
• Japan
• +۶ مورد دیگر

Dominique Ursprung is a Senior Lecturer and Deputy Head of the Center for Geopolitics and Competitiveness at ZHAW School of Management and Law, ZHAW Zurich University of Applied Sciences. His research focuses on International Relations, East Asia, Free Trade Agreements, and Swiss-EU Relations. He teaches electives in European Affairs, International Trade Policy, and Diplomacy. Education: MSc in International Management for Japan (SOAS, University of London, 2008–2011) MA in International Relations (Geneva Graduate Institute, 2010–2011) CAS in Higher Education Didactics (ZHAW, 2014) Research Interests: Ursprung explores geopolitics, trade policy, and Swiss foreign policy. His work bridges diplomacy with business strategy, particularly in East Asia and the Asia-Pacific region. He emphasizes intercultural learning and vocational education in global contexts. Publications: He has authored/co-authored over 20 peer-reviewed articles and book chapters on topics like Swiss trade agreements, digital diplomacy, and geopolitical risks. Recent publications analyze the impact of free trade zones and hybrid diplomatic practices in the digital age. Awards/Grants: None explicitly listed. His work focuses on applied policy research and academic leadership. Projects & Affiliations: Leads the Parliamentary Friendship Group Switzerland-Japan project and serves on the Swiss-Japanese Chamber of Commerce Board. Active in the ZHAW Digital Futures Lab and Swiss Forum on Foreign Policy (foraus).

• Energy & Sustainability
• Behaviour Change
• Digital Innovations
• +۳ مورد دیگر

Devon Wemyss is a Researcher at the ZHAW School of Management and Law , specifically within the Institute of Innovation and Entrepreneurship , focusing on Energy & Sustainability, Behaviour Change, and Digital/Social Innovations. His work emphasizes transdisciplinary collaboration and systemic approaches to energy transitions. Education includes a PhD in Science & Technology Policy Studies from the University of Sussex (2019-2024), an MSc in Environmental Science from ETH Zürich (2009-2012), and a BEng in Civil Engineering from McGill University (2003-2008). He holds an ORCID ID: 0000-0003-1615-7515 and LinkedIn presence. Research Interests : Development and evaluation of digital tools for climate-relevant behavior change; integration of design methods into behavioral theory; co-design processes for energy-saving apps. His work bridges academic research and practical implementation, with a focus on household energy consumption, community engagement, and policy frameworks. Key Projects : Project Leader for SWEET LANTERN (Living Labs for Energy Transition) Deputy Leader for Innovation Monitor and Energy Startup Day Team Member in SWEET COSI , Social Power Plus , and Swiss Competence Center for Energy Research (SCCER CREST) Grants & Funding : Involved in multiple research initiatives supported by Swiss government agencies and collaborative networks, though specific grant details are not disclosed. Labs/Teams : Active in interdisciplinary teams within ZHAW's Innovation Institute, collaborating with Eawag, ETH Zurich, and industry partners like Pöyry and CH2M Hill.

• AI in Science
• Environmental Sciences
• Natural Language Processing
• +۴ مورد دیگر

Dr. Martin Schüle is a Researcher at the Zurich University of Applied Sciences (ZHAW), specifically within the Institute of Computational Life Sciences at the ZHAW School of Life Sciences and Facility Management. He leads the 'Head Research AI & Computational Environment Focus' initiative and specializes in AI applications across environmental sciences, financial markets, and natural language processing. His work bridges theoretical computer science with real-world challenges, including optimizing agricultural practices and analyzing non-financial corporate communication. Research interests span AI ethics, neural networks, and nonlinear dynamics, with a focus on interdisciplinary projects like predicting investor behavior and improving fertilizer efficiency. He has contributed to over 15 peer-reviewed articles and conference papers, often as a principal investigator or co-author in collaborative international teams. Projects include leading efforts on optimal fertilizer application, greenwashing detection in corporate ESG reporting, and real-time agricultural decision systems. Active in networks such as the Deutsche Physikalische Gesellschaft and collaborates with institutions like Paris 1 Sorbonne. His articles explore foundational AI topics (e.g., large language model semantics) and applied domains (e.g., bond market sentiment analysis). He has presented at major venues like the International Symposium on Nonlinear Theory and its Applications (NOLTA), addressing synchronization in cellular automata and hybrid deep learning for environmental forecasting. While no scientific awards are explicitly listed, his extensive project portfolio highlights impactful contributions to computational science and policy-relevant research in sustainability and finance.

• Machine Learning
• Deep Learning
• Explainable Artificial Intelligence
• +۳ مورد دیگر

Prof. Dr. Jasmina Bogojeska is a Professor for Artificial Intelligence and Machine Learning at ZHAW School of Engineering, where she leads the Explainable Artificial Intelligence Group since March 2024. She previously held roles as Senior Principal Data Scientist at Roche (2022-2024) and Research Staff Member at IBM Research Zurich (2013-2022), with postdoctoral work at Max Planck Institute for Informatics (2011-2013). Her affiliations include ZHAW Datalab and Digital Health Lab. PhD in Computer Science (2011), Saarland University/Max Planck Institute MSc in Computer Science (2007), Saarland University BSc in Computer Science (2004), University Ss. Cyril and Methodius Her research bridges Explainable AI with applications in Healthcare , IT Infrastructure Management , and Critical Care Time-Series Analysis . Key focus areas include domain-specific foundation models , conversational data systems , and low-resource NLP solutions . Recent work explores multi-modal medical AI for chest X-ray interpretation and large-scale clinical time-series datasets . Notable contributions include GIT-CXR for automated radiology reports and domain-specific protein language models in immunology. Her publications span IEEE, BMC, and Nature journals, emphasizing practical AI deployment in healthcare and IT operations. Scientific Recognition: Edelman Prize Finalist (2020) IBM Research Accomplishment Award (2019) IBM Corporate Award (2017) Best Paper Award at CNSM (2013) She actively develops reliable AI systems for server incident reduction (PASIR) and child injury monitoring, while advancing automated medical analytics through projects like Antibiotika-Resistenz Tracker. Her teaching covers Machine Learning , Data Mining , and Safer AI at bachelor and master levels.

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.

• Robotics
• Industry 4.0
• Predictive Maintenance
• +۵ مورد دیگر

Prof. Hans Wernher van de Venn is a Professor at the ZHAW School of Engineering's Institute of Mechatronic Systems, Zurich, Switzerland. His work focuses on Industry 4.0, robotics, predictive maintenance, and human-robot collaboration. He leads and collaborates on projects such as SmartAssets, Cybathlon 2024, and Robo-Mate, aiming to enhance industrial automation and safety. Research Interests: His research spans robotics systems, digital twins, and sustainable manufacturing. Notable contributions include predictive maintenance algorithms using autoencoders and domain adaptation techniques, as well as advancements in human-robot interaction safety through deep learning. He has also pioneered wearable robotic exoskeletons for industrial applications. Projects & Awards: Over 20 projects highlight his leadership in Industry 4.0 innovation. Recent work includes testing frameworks for digital twins, generative SDK development, and applying ChatGPT for structured industrial data. His publications emphasize practical applications of AI in manufacturing and healthcare robotics. Grants & Labs: Active in collaborative grants focusing on smart factories, maintenance systems, and embedded systems. His team develops solutions at the intersection of mechatronics and software engineering, with a focus on real-world deployment.

• Computational Biology
• Population Genetics
• Statistical Genetics
• +۴ مورد دیگر

Christoph Leuenberger is a Lecturer at the University of Fribourg, holding positions in the Department of Informatics and the Department of Physics, while also serving in the Dean's Office of the Faculty of Science and Medicine. His work bridges computational methods, population genetics, and ecological modeling. He specializes in statistical inference techniques, particularly Bayesian methods applied to genomic data and evolutionary processes. His research focuses on analyzing population trends, genetic diversity, and evolutionary dynamics across species. Key research interests include computational biology, population genetics, and the development of statistical tools for analyzing large-scale genomic datasets. He has contributed to studies on lactase persistence evolution, ancient DNA analysis, and predator population dynamics. His interdisciplinary approach integrates methods from computer science, mathematics, and ecology to address complex biological questions. Recent articles highlight his work in ecological monitoring, Bayesian inference for sex chromosome analysis, and evolutionary jump modeling in phylogenies. These studies underscore his expertise in bridging theoretical frameworks with practical data analysis in genetics and environmental science. No scientific awards or grants are explicitly mentioned in the provided information. He advises no students listed here but actively contributes to teaching and academic administration within the Faculty of Science and Medicine. Labs and teams associated with his work are not specified in the available data. His location is at PER 21 bu. C321, Bd de Pérolles 90, 1700 Fribourg, with contact details via email and ORCID.

• Graph Theory
• Combinatorial Optimization
• Logistics
• +۴ مورد دیگر

David Schindl is a Lecturer in the Department of Informatics at the University of Fribourg's Faculty of Management, Economics and Social Sciences, with his primary appointment at Haute Ecole de Gestion (HEG) Geneva since 2008. His research bridges graph theory and combinatorial optimization with practical applications in logistics, vehicle routing, and academic timetabling systems. Education: PhD in Mathematics, EPFL, 2004 Research Interests: Dr. Schindl specializes in theoretical graph structures—including k-community detection, clique-width parameterization, and EPG graphs—with direct applications to transportation logistics, waste management, and educational scheduling. His work on course/exam timetabling at HEG since 2012 demonstrates his commitment to solving real-world operational challenges through mathematical optimization. Research Trends: Analysis of his 2020-2025 publications reveals sustained focus on community structures in graph classes and width-parameterized algorithms, alongside growing emphasis on sustainable logistics. His waste collection project exemplifies the environmental application of combinatorial optimization to reduce municipal fuel consumption and emissions. Grants and Projects: Efficient and sustainable waste collection (2019-2022): Funded by Innovation, this project developed optimization algorithms for waste collection routing in Swiss municipalities using electric vehicles and intermediate depots to minimize environmental impact. Teaching: At the University of Fribourg, he teaches decision support and graph theory courses. At HEG Geneva, he delivers instruction in statistics and mathematics for economics students, emphasizing practical applications of quantitative methods.

• Computational Biology
• Computational Chemistry
• Drug Design
• +۲ مورد دیگر

Vittorio Limongelli is a Full Professor at the Faculty of Biomedical Sciences, Università della Svizzera italiana (University of Italian Switzerland). His research focuses on computational biology, drug design, and molecular simulations, with applications in pharmacology and medicinal chemistry. PhD in Drug Sciences (2007) Postdoctoral research at ETH Zurich His work explores advanced computational methods for drug/target binding interactions, including enhanced sampling simulations and machine learning approaches. Notable research themes include G protein-coupled receptor dynamics, bile acid receptor modulation, and extracellular vesicle profiling for disease risk assessment. Scientific awards include the Premio Scrocco (2013), Young Researcher in Medicinal Chemistry award (2016), EFMC Prize runner-up (2017), and recognition as a top 5 scientist in physical/chemical sciences for the USERN Prize (2020). He received an ERC Consolidator Grant in 2020. Email: vittorio.limongelli@usi.ch Office: East Campus, Sector D, Office D5.07 (Level P5), Via la Santa 1, 6962 Lugano-Viganello

Susan Atheyمشاهده پروفایل

استاد

• Economics of Digitization
• Machine Learning and Causal Inference
• Marketplace Design
• +۳ مورد دیگر

Susan Athey is the Economics of Technology Professor at Stanford Graduate School of Business and a Professor of Economics (by courtesy) at Stanford's School of Humanities and Sciences. She is also a Senior Fellow at the Stanford Institute for Economic Policy Research and Stanford Institute for Human-Centered Artificial Intelligence. Her primary affiliation is with the Graduate School of Business, where she leads the Golub Capital Social Impact Lab. She previously served as Chief Economist at the U.S. Department of Justice Antitrust Division (2022–2024) and has held roles at MIT, Harvard, and Microsoft. Her research focuses on the economics of digitization, machine learning applications in causal inference, and marketplace design. Key areas include platform markets, online advertising, vaccine policy, and social impact technology. She earned her PhD from Stanford University and a BA from Duke University. Athey's work bridges economics and technology, with contributions to policy design, antitrust analysis, and digital health interventions. Her recent projects include evaluating the impact of social media campaigns on vaccine adoption and designing auction mechanisms for pandemic vaccine distribution. Education: PhD, Stanford (1995); BA, Duke (1991) Affiliations: Stanford GSB, Stanford Institute for Economic Policy Research, National Academy of Sciences Her research has addressed critical issues such as consumer privacy (The Digital Privacy Paradox), AI governance, and experimental methods for policy evaluation. She is a recipient of the John Bates Clark Medal (2007) and R. K. Cho Award (2024). Current initiatives include the Golub Capital Social Impact Lab, which develops technology-driven solutions for social sector challenges. She also advises governments and tech firms on market design and innovation policy.

Titus Neupertمشاهده پروفایل

استاد

• Condensed Matter Physics
• Quantum Materials
• Topological Insulators
• +۵ مورد دیگر

Prof. Titus Neupert is a Professor of Condensed Matter Theory at the University of Zurich's Faculty of Science. He leads the research group on quantum materials with topological properties, focusing on topological insulators, superconductors, and machine learning applications in physics. He holds roles as Director of the Digital Society Initiative and Co-director of the Graduate Campus. His work is funded by an ERC Starting Grant and has earned awards like the Klung-Wilhelmy Science Award (2019). Education: PhD in Physics (ETH Zurich & Paul Scherrer Institute, 2013) Postdoc at Princeton University (2013–2016) MSc in Physics (University of Zurich, 2009) BSc in Physics (Dresden University of Technology, 2007) Research Interests: Quantum materials with topological properties, including exotic semiconductors, magnets, and superconductors. His group combines theoretical approaches like numerical simulations and machine learning to study topological phases and their experimental realizations. Key Contributions: Discovery of topological charge density waves in kagome metals Development of variational methods for quantum many-body problems Exploration of non-Hermitian topology and strain engineering in quantum materials Awards & Grants: ERC Starting Grant, Clarivate Highly Cited Researcher (2020–2024), Klung-Wilhelmy Science Award, and Swiss Physical Society Dissertation Prize. Advising & Teams: PhD advisees: Bastien Lapierre, Nikita Astrakhantsev, Martina Soldini, and others Postdocs: Maurizio Storni, Attila Szabó, and international collaborators Labs: Research Group for Condensed Matter Theory at UZH