جست‌وجوی استاد و پژوهشگر

Thomas Maillartمشاهده پروفایل

مدرس ارشد

• Collective Intelligence
• Complex Socio-Economic Systems
• Human Dynamics
• +۱۲ مورد دیگر

Thomas Maillart is a Senior Lecturer and researcher at the Research Institute for Statistics and Information Science at the University of Geneva. His work bridges complex systems, collective intelligence, and cybersecurity, with a focus on modeling human dynamics and digital risks. Education: PhD in Science, ETH Zurich (2011) Master’s degree, EPFL (2005) His research centers on understanding how incentives, structures, and social interactions shape collective behavior in online and physical environments. He investigates topics such as cyber risks, privacy, resilience, and technological innovation. His work often applies statistical physics and data science to socio-technical systems, including open-source software development, cybersecurity policy, and human behavior modeling. His recent publications reflect a strong trend toward interdisciplinary research, combining insights from computer science, economics, psychology, and public policy. He explores how machine learning can forecast digitization labor needs, how collective action enhances cybersecurity, and how bio-sensors can aid in medical diagnosis. His work frequently appears in high-impact journals such as Science , PLOS ONE , and Physical Review . Scientific Awards: Zurich Dissertation Prize (2012) for pioneering work on cyber risks Thomas Maillart has advised and collaborated with numerous researchers and students, though specific names are not listed in the provided text. He has been involved in significant research grants and initiatives, including cybersecurity consulting for governmental and private organizations and co-founding a cybersecurity startup in 2005. His academic service includes organizing and presenting at international conferences such as WEIS and ACM conferences. He is associated with several research platforms, including ResearchGate, Google Scholar, LinkedIn, and Twitter, and has contributed to both peer-reviewed and practitioner-oriented publications. His recent editorial work includes co-editing a book on critical information infrastructure security.

Giacomo Vaccarioمشاهده پروفایل

مدرس

• Agent-Based Modeling
• Network Science
• Supply Chain Analysis
• +۳ مورد دیگر

Dr. Giacomo Vaccario is a Lecturer at ETH Zurich's Department of Management, Technology, and Economics, where he researches socio-economic systems through computational approaches. His work bridges complexity science, data analysis, and network theory, with applications in supply chain optimization and scientific collaboration patterns. His research focuses on understanding cooperation determinants in socio-economic systems using agent-based models and statistical analysis of large-scale data. Current projects examine wood supply chains for sustainable construction and knowledge creation patterns through patent/publication networks. Recent publications demonstrate strong emphasis on network resilience, distribution systems, and methodological innovations in interdisciplinary research. As editorial board member for Social Network Analysis and Mining, Dr. Vaccario actively shapes scholarly discourse in complex systems research.

• Natural Language Generation
• Computational Linguistics
• Referring Expression Generation
• +۴ مورد دیگر

Kees van Deemter is a Professor in the Department of Computing Science at the University of Aberdeen's School of Natural and Computing Sciences. With a research career spanning over three decades, he has established himself as a leading figure in Natural Language Generation and Computational Linguistics. His work bridges theoretical linguistics with practical NLP applications, with particular focus on referring expression generation, multilingual processing, and evaluation methodologies. Van Deemter's research interests center on Natural Language Generation, with special emphasis on Referring Expression Generation (REG), computational modeling of linguistic phenomena across languages, and the development of robust evaluation frameworks for NLP systems. His work spans theoretical foundations to practical applications, including logic-to-text generation, cross-linguistic studies comparing East Asian and European languages, and addressing challenges in hallucination and reproducibility in NLP. His recent publications demonstrate a consistent focus on improving evaluation methodologies in NLP, with particular attention to task-based assessments rather than purely ratings-based approaches. He has made significant contributions to understanding how linguistic features influence reference production across languages, with extensive work on Chinese and Mandarin processing. His research group has developed several important corpora including QTUNA for quantifier studies and Mtuna for Mandarin referring expressions. Co-authored the influential survey 'Computational Generation of Referring Expressions: A Survey' (2012) Developed the Mtuna corpus for Mandarin referring expressions Contributed foundational work on the incremental algorithm for referring expression generation Pioneered research on vague language generation from a game-theoretic perspective Investigated cross-linguistic differences in reference production between English and East Asian languages Van Deemter has supervised numerous PhD students who have become active researchers in NLP, including Guanyi Chen, Fahime Same, and Albert Gatt. His collaborative work extends across multiple institutions and has significantly shaped current approaches to referring expression generation and evaluation in NLP. His recent work critically examines the limitations of current evaluation practices in NLP and proposes more scientifically grounded assessment frameworks.

Nicolás Vila Blancoمشاهده پروفایل

استادیار

• Medical Image Processing
• Deep Learning
• Biomedical Engineering
• +۴ مورد دیگر

Nicolás Vila Blanco is an Assistant Professor at the University of Santiago de Compostela, primarily affiliated with the Information Technologies Research Center (CiTiUS). His work bridges Medical Image Processing and Deep Learning through software development and algorithm optimization. Education includes: PhD in Information Technology Research (Universities of Santiago de Compostela and Coruña) M.Sc. in Data Science and Computer Engineering (University of Granada) B.Sc. in Computer Science (University of Vigo) Research focuses on applying Artificial Intelligence to biomedical challenges, particularly in dental imaging and cardiac diagnostics . Key contributions include: Developing IDALib (Image Data Augmentation Library) Creating DenTiUS Deep Plaque software for dental plaque analysis Designing PrimerEvalPy for microbiome primer evaluation Building gVARVI for heart rate response analysis Recent publications demonstrate expertise in: Clinical software development Deep learning architectures (U-Net, Few-Shot Learning) Medical imaging applications Biomedical data processing AI in dental diagnostics Microbiome sequencing techniques

Hanspeter Schmidمشاهده پروفایل

استاد

• Signal Integrity
• Sigma-Delta Modulation
• Low-Power Electronics
• +۷ مورد دیگر

Prof. Dr. Hanspeter Schmid is a Lecturer for Microelectronics and Signal Processing at the University of Applied Sciences and Arts Northwestern Switzerland (FHNW) within the School of Engineering and the Environment. He also serves as a part-time Senior Lecturer at ETH Zurich for Analog Signal Processing and Filtering. Diploma, Postgraduate, and Doctoral degrees from ETH Zurich His research focuses on fast low-power circuits for sensor electronics, signal integrity in analog systems , and sigma-delta modulation . Recent publications address noise analysis, statistical fallacies in small sample measurements, and mixed-signal circuit design. Key article trends include analog/digital filter design, signal-flow graphs, and FFT applications in noise measurement. His work bridges theoretical mathematics with practical circuit implementation, as seen in his 3σ Fallacy study and switched-capacitor tutorials. IEEE CAS Society : Co-Chair (2008-2010), Associate Editor (TCAS-I 2007-2011, TCAS-II 2016-2017) Distinguished Lecturer (2011-2012) and ESSCIRC committee member until 2019 He supervises research projects like Authenticity in Music Production , collaborating with digital music research centers to simulate electronic equipment. His professional affiliations include FHNW’s Institute for Sensors and Electronics and ETH Zurich.

• Medical Imaging
• Computational Biology
• Neurology
• +۳ مورد دیگر

Dr. Norman Juchler is a researcher at the Zurich University of Applied Sciences (ZHAW) within the Institute of Computational Life Sciences. He specializes in computational methods for medical diagnosis and disease modeling, particularly focusing on intracranial aneurysms and wearable technologies. His work integrates machine learning, radiomics, and biomechanical modeling to improve clinical decision-making in neurology and vascular medicine. Research Projects - Principal contributor to Stroke DynamiX, AneuX, and Digital Futures Lab initiatives. - Co-developed the AneuX morphology database for standardized aneurysm analysis (Zenodo, 2022). - Investigated wearable technologies for pediatric infection monitoring and atrial fibrillation detection via photoplethysmography. - Validated cerebral aneurysm rupture prediction models across international cohorts. Key Research Themes Morphological analysis of intracranial aneurysms Shape-based clinical biomarker development Machine learning in medical imaging Biomechanical modeling of vascular diseases Integration of wearable devices in clinical workflows Recent Contributions His 2023 studies demonstrated shape superiority over size in aneurysm diagnostics and advanced Meniere's disease etiology analysis through radiological heterogeneity. Ongoing work explores neurovascular instability markers and open-set recognition in hematology. Labs & Networks Affiliated with ZHAW's Digital Health Lab, Center for Computational Health, and Datalab. Active in interdisciplinary groups like The Interface Group and OSR4H consortium.

• Global History
• Digitization
• Environmental Policy
• +۳ مورد دیگر

Professor Daniel Speich Chassé is a Full Professor in Global History at the University of Lucerne since 2018, affiliated with the Department of History within the Faculty of Humanities and Social Sciences. His research focuses on digitization's social impacts, environmental issues, and global economic inequality. He holds a Ph.D. (2004) and Habilitation (2012) from the University of Zurich. Before joining Lucerne, he worked at ETH Zurich and held fellowships at the Max-Planck-Institute for the History of Science (Berlin) and the Institute of Advanced Studies (Nantes). Administrative roles include Director of the Historical Seminar, Board Member of the Graduate School Lucerne, Co-Director of the Master program in World Society and Global Governance, and Co-Director of the Faculty's Digital Issues Focus. His academic trajectory includes key contributions to the history of economic thought, development policies, and colonial/postcolonial studies. Research interests span global governance frameworks, statistical methodologies in development, and the historical interplay between economic theories and political imagination. His work examines how quantitative metrics shape international policies, particularly in Africa and postcolonial contexts. Notable projects include studies on the origins of the Millennium Development Goals and the role of carbon metrics in environmental governance. He has supervised numerous doctoral and master’s projects, though no specific advisees are listed. His extensive publications (over 50 entries) reflect interdisciplinary engagement with global history, economics, and environmental policy. Awards or fellowships are not explicitly detailed but include his prestigious Max-Planck and Nantes fellowships.

Christian M. Franckمشاهده پروفایل

استاد

• High Voltage Gaseous Insulation Systems
• Future Overhead Power Transmission Lines
• High Voltage Solid Insulation
• +۷ مورد دیگر

Christian M. Franck is a Full Professor of High Voltage Engineering at ETH Zurich's Department of Information Technology and Electrical Engineering, where he leads the Power Systems and High Voltage Laboratory. Appointed Assistant Professor in January 2010, promoted to Associate Professor in June 2015, and elevated to Full Professor in March 2020, he has established himself as a leading researcher in electrical power transmission technologies. Dr. Franck's academic foundation includes physics studies at the Universities of Bonn, Edinburgh, and Kiel (diploma 1999), followed by a Ph.D. in experimental physics from the Max-Planck-Institute for Plasma Physics in 2003. His industry experience at ABB Research Center (2003-2010), where he headed the high voltage systems and gas circuit breakers group, provided crucial practical insights that inform his research approach. Research Focus: His laboratory investigates 'technologies for future electric power transmission systems' with four primary thrusts: High Voltage Gaseous Insulation Systems, Future Overhead Power Transmission Lines, High Voltage Solid Insulation, and Current Interruption. This includes developing SF6 alternatives, HVDC insulation systems, hybrid AC-DC overhead lines, corona mitigation techniques, and advanced circuit breaker technologies. His methodology combines cutting-edge experimental techniques with multiphysics simulations to achieve both practical solutions and fundamental physical understanding. Analysis of his recent publications (2023-2025) reveals a strong emphasis on eco-friendly alternatives to traditional insulating gases, advanced monitoring systems for circuit breakers, and the physics of current interruption in novel gas mixtures. His work bridges fundamental gas discharge phenomena with practical engineering applications in power transmission infrastructure. Full Professor of High Voltage Engineering, ETH Zurich (March 2020 - present) Associate Professor, ETH Zurich (May 2015 - March 2020) Assistant Professor, ETH Zurich (January 2010 - May 2015) Group Leader, High Voltage Systems and Gas Circuit Breakers, ABB Research Center (2005-2010) Dr. Franck teaches foundational and advanced courses including Networks and Circuits I, High Voltage Engineering, and Introduction to Electric Power Transmission. His research group maintains strong industry connections, ensuring practical relevance while advancing the fundamental science of high voltage engineering. The laboratory's work directly addresses critical challenges in the energy transition, particularly in developing sustainable alternatives to SF6 and enabling more efficient electrical energy transmission systems.

• Plasma Physics
• Fusion Energy
• Numerical Simulation
• +۵ مورد دیگر

Paolo Ricci is a Full Professor and Director at the Swiss Plasma Center (SPC) at École Polytechnique Fédérale de Lausanne (EPFL) since October 2023. He previously held the Tenure Track Assistant Professor position (2010) and Associate Professor position (2016) at EPFL. His academic affiliations include leadership roles in multiple SPC sub-groups, such as Theory, Low Temperature Plasma Physics and Applications, International Installations, Tokamak Physics, Material Group, Plasma Processing, Applied Superconductivity, Edge Plasma Physics, and Administration. Politecnico di Torino (Italy): Master's in Nuclear Engineering (2000) Los Alamos National Laboratory: Doctoral studies in kinetic simulation of magnetic reconnection Dartmouth College: Postdoctoral research in gyrokinetic simulations of Z pinch plasmas Ricci's research focuses on plasma turbulence and instabilities, numerical simulations of laboratory and fusion plasmas, and computational methods for plasma physics. His work spans tokamak and stellarator boundary layer dynamics, scrape-off layer turbulence, fast ion transport, and validation of plasma simulation codes like GBS. His recent publications emphasize global fluid simulations in diverted geometries, snowflake magnetic configurations, and theoretical scaling laws for scrape-off layer widths. His scientific awards include the 2016 Section de Physique Teaching Prize, 2021 Craie d'Or (EPFL physics bachelor students), and 2021 Polysphère d'Or (AGEPoly). Ricci has supervised numerous Ph.D. theses on topics ranging from gyrokinetic moment-based models to scrape-off layer simulations, and actively collaborates with institutions on plasma turbulence validation projects.

Sabine Schillingمشاهده پروفایل

مدرس

• Statistics
• Machine Learning
• Numerical Simulations
• +۳ مورد دیگر

Dr. Sabine Schilling is a Lecturer at the Lucerne School of Business, part of Lucerne University of Applied Sciences and Arts, affiliated with the Institute of Tourism and Mobility (ITM). She holds a PhD in Theoretical Particle Physics from the University of Zurich and studied physics at the University of Heidelberg. Her research focuses on interdisciplinary applications of statistics , machine learning , and numerical simulations , with particular emphasis on biomedical challenges like intracranial aneurysm analysis. Key areas include: Morphological quantification of vascular structures Hemodynamic modeling of blood flow Genome-wide association studies for neurological disorders Development of computational biology frameworks She maintains active software development contributions, including the R package visStatistics for automated statistical test visualization. Her teaching portfolio includes courses in descriptive statistics.

• Alzheimer's Disease
• Neuroimaging
• Biomarkers
• +۴ مورد دیگر

Giovanni Frisoni is a Full Professor of Neuroscience at the University of Geneva's Faculty of Medicine, specializing in Alzheimer's disease research and diagnostics. He leads multiple European consortia including the AMYPAD project and contributes to European task forces for brain health services. His work bridges clinical neurology, neuroimaging, and biomarker development. Frisoni's research focuses on the intersection of neuroimaging biomarkers, cognitive decline, and Alzheimer's disease pathology. His team investigates amyloid and tau dynamics using PET imaging, develops blood-based diagnostic workflows, and explores novel therapeutic avenues including gut-brain axis interventions. Recent work demonstrates leadership in translating biomarker research into clinical practice through European intersocietal recommendations. His publication record shows a clear evolution from foundational neuroimaging studies (2020-2022) toward clinical implementation frameworks (2023-2025). Current work emphasizes blood biomarkers for tau-PET referral optimization, fecal microbiota transplantation effects, and anti-amyloid therapy guidelines. The research spans basic science (mouse models), translational studies (imaging-biomarker correlations), and health services research (diagnostic pathways). Key Scientific Contributions: Developed clinical implementation frameworks for amyloid and tau PET Pioneered blood biomarker workflows for memory clinic diagnostics Advanced understanding of gut-brain axis in Alzheimer's pathology Shaped European diagnostic guidelines through multisociety consensus Frisoni actively mentors junior researchers including Ribaldi, Altomare, and Ceyzeriat, who frequently co-lead projects. His work receives substantial European funding through consortia like AMYPAD and Euro-PAD. Current projects include the PreTAD dementia risk estimation initiative and RADAR-AD remote monitoring technologies. He maintains strong collaborations across European memory clinics and imaging centers. His laboratory focuses on multimodal biomarker integration, particularly combining PET imaging with fluid biomarkers and EEG. Recent technical advances include AI applications for generating FDG-PET images from amyloid scans and connectome identifiability metrics for Alzheimer's disease.

• Mathematical Modeling
• Life Sciences Applications
• Mathematics Education
• +۳ مورد دیگر

Prof. Dr. Julia Rausenberger serves as Joint-Head of Higher Education and Professor for Applied Mathematics in Life Sciences at the School of Life Sciences (HLS) of the University of Applied Sciences and Arts Northwestern Switzerland (FHNW) since 2023 and 2020 respectively. She joined FHNW in 2010 as a Lecturer in Mathematics and held key roles including Student Projects Coordinator (2014-2020) and Equality Representative (2013-2016). Her academic credentials include: PhD in Biomathematics, University of Freiburg (2005-2010) Post-Doc at ETH Zurich's Department of Biosystems Science (2010) University Didactics Certification, University of Basel (2014-2015) Mathematics Studies at Universities of Münster/Tübingen (1999-2005) with Pisa exchange (2002-2003) Her research integrates mathematical modeling in life sciences with transformative educational approaches. She pioneers agile teaching methodologies, digital assessment tools, and contextualized mathematics instruction specifically for application-oriented universities. Her work addresses critical gaps in STEM education through functional thinking development and industry-aligned pedagogy, significantly enhancing student engagement in engineering and life sciences curricula. Analysis of her recent publications reveals a strategic shift toward educational innovation since 2020, with dominant themes in agile methodology implementation, functional cognition in mathematics, and digital assessment design. These works consistently bridge theoretical pedagogy with practical classroom applications across chemistry, engineering, and life sciences contexts. Her scientific recognition includes: Teaching Award of HLS FHNW (2019) Teaching Award of HLS FHNW (2017) Prof. Rausenberger has secured industry collaboration with AICOS Technologies AG (2017-2018) on digital statistics education and mentored numerous student projects as Coordinator (2014-2020). Her leadership in equality initiatives and current role shaping institutional higher education strategy demonstrates comprehensive academic stewardship. As Joint-Head of Higher Education, she directs pedagogical innovation across HLS FHNW, establishing frameworks for digital learning transformation and faculty development in application-oriented mathematics education.

Roman Altherمشاهده پروفایل

پژوهشگر

• Biodiversity
• Community Ecology
• Spatial Ecology
• +۷ مورد دیگر

Roman Alther is a Senior Researcher at the Department of Evolutionary Biology and Environmental Studies, University of Zurich, and affiliated with Eawag in Dübendorf. His work spans biodiversity research, community ecology, and subterranean biology, focusing on amphipods and freshwater ecosystems in Alpine environments. Education: PhD in Ecology (University of Zurich & Eawag, 2018), Master of Science in Biology (ETH Zurich, 2013), Bachelor of Science in Biology (University of Zurich, 2011) Roman’s research integrates spatial ecology, genetic diversity analysis, and environmental DNA (eDNA) metabarcoding to study groundwater fauna and river networks. His work addresses how climate history, dispersal behavior, and anthropogenic impacts shape subterranean biodiversity patterns. Recent publications highlight his contributions to understanding amphipod metapopulations, cryptic speciation, and the global importance of groundwater ecosystems. Key trends in Roman’s publications include: (1) Advancing integrative taxonomy for subterranean amphipods, (2) Modeling biodiversity responses to glacial history and land use, (3) Applying citizen science and eDNA methods for aquatic monitoring, and (4) Advocating for policy changes to protect groundwater ecosystems. His studies often combine fieldwork, computational modeling, and molecular techniques.

Pascal Wagner-Eggerمشاهده پروفایل

مدرس

• Social Psychology
• Statistics
• Conspiracy Theories
• +۱۰ مورد دیگر

Pascal Wagner-Egger is a Lecturer and Researcher in Social Psychology and Statistics at the University of Fribourg, Switzerland. He co-directs the Psycholinguistics and Applied Social Psychology Unit with Pascal Gygax. Research Focus: Conspiracy Theories, Paranormal Beliefs, Racism/Sexism, Social Representations, Logical Reasoning. Teaching: Critical Thinking, Reasoning Biases, Belief Systems, Social Psychology at institutions like Amnesty International, Swiss Confederation, HEP, HES. Advisory Roles: Federal Commission against Racism (Bern), Swiss National COVID-19 Science Task Force, Swiss Science Council, France's 'Enlightenment in the Digital Age' Commission. Media: Contributed to RTS series 'Specimen', 'Dans la tête de', and 'Tataki'; frequently appears in radio/TV and lectures across Switzerland, France, and Belgium. Research Trends (2021-2024) : Explores how cognitive biases, socioeconomic precarity, and ideological orientation shape conspiracy beliefs. Investigates pandemic perception, climate change skepticism, and social movement dynamics (e.g., Yellow Vests). Scientific Awards : None explicitly mentioned. Advisory & Outreach : Regularly advises organizations on misinformation, racism, and cognitive biases. Collaborates with institutions like the Swiss National Science Task Force and the Federal Commission against Racism.

• Artificial Intelligence
• Digital Twins
• Time Series Analysis
• +۵ مورد دیگر

Stefan Amstutz serves as a Senior Researcher at the iHomeLab within the Institute of Electrical Engineering at Lucerne University of Applied Sciences and Arts (HSLU), School of Engineering and Architecture. His work integrates artificial intelligence with building automation, rehabilitation systems, and home care technologies through innovative digital twin platforms and explainable AI frameworks. His academic credentials include: Doctorat d'Automatique from Université de Haute-Alsace Master of Science in Engineering (MSE) specializing in Mechatronics and Automation from University of Applied Sciences Northwestern Switzerland Bachelor of Science in System Engineering specializing in Industrial Automation from University of Applied Sciences Northwestern Switzerland CAS in DevOps Leadership and Agile Methods from HSLU CAS in Cloud and Platform Manager from HSLU Dr. Amstutz's research centers on two interconnected pillars: Digital Twin Architectures for intelligent building systems, utilizing hybrid modeling and time series forecasting to enable real-time optimization of energy and operational performance; and Trustworthy AI Systems incorporating human-in-the-loop mechanisms for explainable decision-making in critical applications like VR telerehabilitation and home care monitoring. His methodology emphasizes user-centered design and safety-critical validation. Analysis of his publication trajectory reveals a strategic evolution from foundational control engineering in photovoltaic manufacturing (2014-2018) toward cutting-edge AI applications in building automation and healthcare (2019-2025). Recent work demonstrates increasing focus on explainability, anomaly detection, and human-AI collaboration, particularly in the RecoveryFun and CleverGuard projects. As lead researcher for HSLU's strategic initiatives including AI in Buildings (open-source digital twin platform), RecoveryFun (VR telerehabilitation decision support), and CleverGuard (long-term home care anomaly detection), he secures project funding through applied research grants targeting real-world implementation. His professional skills integrate Agile methodology, DevOps transformation, and cloud-native architecture with core competencies in reinforcement learning and statistical modeling. Dr. Amstutz operates within the iHomeLab research ecosystem, which specializes in intelligent home technologies through interdisciplinary collaboration between electrical engineering, computer science, and healthcare domains. The lab's infrastructure supports full-stack development of AI-powered services for real-time simulation, prediction, and optimization in building environments.