جست‌وجوی استاد و پژوهشگر

Tobias Kowatschمشاهده پروفایل

دانشیار

• Digital Health Interventions
• Mobile Health (mHealth)
• Conversational Agents
• +۵ مورد دیگر

Prof. Dr. Tobias Kowatsch is an Associate Professor at the Institute for Implementation Science in Health Care, Faculty of Medicine, University of Zurich. He serves as Scientific Director of the Centre for Digital Health Interventions (CDHI) and Director of the School of Medicine at the University of St. Gallen (HSG). His research focuses on digital health interventions at the intersection of information systems, computer science, and behavioral medicine. PhD in Management (University of St. Gallen, 2016) Master in Business Informatics (2012) Master in Media and Informatics (2007) Diploma in Informatics (2005) Kowatsch develops digital health solutions such as MobileCoach (open-source platform for health interventions) and Pathmate Technologies (digital therapeutics like manoa for hypertension). His work integrates machine learning, conversational agents, and wearable technology to address non-communicable diseases and mental health challenges. His recent research trends emphasize personalized health interventions , conversational AI , and biopsychosocial monitoring using wearables. Key areas include dementia prevention , menstrual health , and cancer patient support . ISRII Poster Award (2023) Gold & Silver Awards, World Media Festivals (2023) Fitrockr & Garmin Health EMEA Research Grant (2023) Kowatsch leads the CSS Health Lab and collaborates with institutions like ETH Zurich and the Singapore-ETH Centre. His initiatives include the Precision Digital Therapeutics Summer School and industry partnerships with companies like Pathmate Technologies .

• Human-Computer Interaction (HCI)
• Multimodal Interaction
• Visual Analytics
• +۵ مورد دیگر

Denis Lalanne is a full Professor in the Department of Informatics at the University of Fribourg, leading the 'human-building interaction' group at the Smart Living Lab and directing the Human-IST institute . He specializes in Human-Computer Interaction (HCI), focusing on multimodal interaction, visual analytics, and Human-Building Interaction (HBI). His work bridges computer science with architecture and urban design to improve building occupants' comfort and accessibility. His research spans topics such as assistive technologies for visually impaired individuals, energy-efficient lighting systems, and predictive models for indoor environmental quality. He has led projects like the Human-IST Lab and SWICE (Sustainable Well-being in Energy Transition), emphasizing interdisciplinary collaboration between academia, industry, and public institutions. Key contributions include the development of frameworks for human-centric lighting, wearable sensors for urban comfort analysis, and empathic systems to enhance HCI. His work is published in top venues like ACM Transactions on Accessible Computing , IEEE , and CHI . Education and career highlights include a PhD from EPFL (Swiss Federal Institute of Technology), postdoctoral research at IBM’s USER Group, and prior teaching roles at the University of Avignon. He is a Swiss representative at IFIP TC13 and has organized major conferences like IHM 2016.

• Robotics
• Artificial Intelligence
• Computer Vision
• +۳ مورد دیگر

Björn Jensen is a Professor and Co-Head of the AI Robotics Research Lab at Lucerne University of Applied Sciences and Arts (HSLU), specifically within the Lucerne School of Computer Science and Information Technology. He also teaches medical robotics at the University of Bern's Biomedical Engineering Program. His professional background includes roles at the Autonomous Systems Lab at EPFL, Switzerland, and founding the startup Singleton 3D focusing on 3D laser measurement technology. Educational background: MSc in Electrical Engineering (Automation & Image Processing) from TU Darmstadt (1998), followed by a Master's in Industrial Management from the same institution. PhD in human-robot interaction from EPFL (2005), with research stints at Tokyo University (2005) and involvement in projects like Robox@Expo.02 and Smarter-Elrob. Research interests span robotics, human-robot interaction, autonomous systems, medical robotics, and sensor-based navigation. Notable projects include the 'Smart Ennoblement Factory', 'NaviMow' autonomous lawnmower, and 'Bagger Assistenzsysteme'. His work emphasizes real-world applications of robotics in dynamic environments and human-centric systems. Lab leadership includes co-directing the AI Robotics Research Lab, focusing on advancing robotics technologies for practical scenarios. No scientific awards explicitly listed, but contributions to industry-academia collaborations are highlighted through startup ventures and applied research projects.

Umberto Michelucciمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Astrophysics
• +۵ مورد دیگر

Umberto Michelucci is a Professor of Scientific Machine Learning at Lucerne University of Applied Sciences and Arts (HSLU), Switzerland. He holds a PhD in Machine Learning applied to Physics and has over 20 years of industry experience. He is the Subject Head of Applied Data Intelligence in Continuing and Executive Education, Head of Certificates in Machine Learning/Data Engineering, and founder of TOELT LLC and the AI Center of Excellence at Helsana Versicherung AG. His research focuses on machine learning applications in science, astrophysics, uncertainty quantification, and sensor technology. Education PhD in Machine Learning applied to Physics (Portsmouth University) Master in Theoretical Physics (University of Florence) Postgraduate Certificate in Higher Education (Open University, UK) Research Interests Michelucci’s work bridges machine learning and scientific disciplines. Key areas include: Machine learning for astrophysics (INAF collaborations) Uncertainty analysis in high-stakes ML systems Deep learning for optical sensing (e.g., olive oil quality analysis) Foundational mathematical concepts for ML in science Awards & Recognition World’s Top 2% Scientists (Stanford List) Google Developer Expert in Machine Learning AI Global Ambassador (2022) TOP AI Influencer in Switzerland (2021) Grants & Collaborations He collaborates with institutions like INAF (Italy) and NVIDIA/Google, leading projects on AI for agrifood, medical imaging, and astrophysics. His work includes $multi-million industry partnerships and EU-funded research. Labs & Teams Director of the TOELT AI Lab and oversees HSLU’s Applied Data Intelligence programs. Active in open-source initiatives and global AI standardization efforts.

Clotaire Michelمشاهده پروفایل

مدرس

• Risk Management
• Technology Assessment
• Seismic Risk
• +۲ مورد دیگر

Dr. Clotaire Michel serves as a Lecturer in Risk Assessment and Risk Management at ZHAW School of Engineering, where he also holds roles as Deputy Programme Director for MAS/DAS/CAS Integrated Risk Management (IRM), Module Manager for Risk Management (Bachelor), and Coordinator for the CAS Risk Assessment program. His academic work spans Technology Assessment in the Master Circular Economy Management program and MSE module coordination. His educational background includes a PhD in Earth Sciences from Université Grenoble Alpes (2004-2007), an Ingénieur Civil des Mines (Engineering Geology) from Ecole Nationale Supérieure des Mines de Nancy (2001-2004), and a Master in Earth Sciences from Université Grenoble Alpes (2003-2004). Continuing education includes CAS Earthquake Engineering (HSLU, 2023) and Habilitation à diriger les recherches (Université Grenoble Alpes, 2017). Michel's research focuses on interdisciplinary risk management, integrating seismic risk assessment, technology evaluation, and climate resilience. His work bridges engineering geology with practical safety applications, particularly in structural safety, fire protection systems, and earthquake engineering. Current projects address circular economy risk frameworks and regulatory compliance in European safety standards. His 15 most recent publications (2020-2025) reveal evolving expertise from traditional seismic site characterization toward broader risk domains including climate adaptation and fire safety. Key trends include methodological advances in ambient vibration analysis for structural monitoring and practical applications of risk assessment frameworks in European regulatory contexts. Professional networks include Verein Risiko und Sicherheit, Netzwerk Risikomanagement, Institut pour la maîtrise des risques (ImdR), Association Française du génie ParaSismique (AFPS), and Schweizer Gesellschaft für Erdbebeningenieurwesen und Baudynamik (SGEB). His industry role as Project Manager/Section Leader at Risk&Safety AG complements his academic work in hazard and risk analysis. As Deputy Programme Director for IRM, Michel oversees curriculum development and program coordination for professional risk management education. His research group within ZHAW's Technology Assessment focus conducts field studies on structural safety systems and develops risk assessment protocols adopted by Swiss safety agencies.

• Artificial Intelligence
• Medical Imaging
• Data Analysis
• +۳ مورد دیگر

Simone Lionetti is a Lecturer and Co-Head (acting) of the Applied AI Research Lab at the Lucerne School of Computer Science and Information Technology, Lucerne University of Applied Sciences and Arts. His academic journey includes a Ph.D. in Physics from ETH Zürich (2018), a Master's in Physics from Università degli Studi di Milano (2013), and a Bachelor's in Physics from the same institution (2010). He has held postdoctoral and research roles at institutions such as Durham University and ETH Zürich. His research focuses on AI applications in healthcare, including medical anomaly detection, dermatology, and bioaerosol monitoring. He also explores theoretical particle physics and software engineering for scientific computing. Key competencies include data analysis, algorithm design, and self-supervised learning techniques. Recent work emphasizes robust AI systems for medical imaging, data quality audits, and scalable foundation models. His projects bridge technical innovation with societal needs, such as addressing diversity gaps in dermatological AI and improving real-time environmental monitoring. He has contributed to over 20 peer-reviewed articles and holds two notable awards/honors (specific details not disclosed in text). His work integrates cross-disciplinary approaches, combining theoretical physics insights with practical AI solutions for healthcare and environmental challenges.

Duccio Testaمشاهده پروفایل

پژوهشگر

• Plasma Physics
• Nuclear Fusion
• Mathematical Modeling
• +۴ مورد دیگر

Duccio Testa is a Researcher at the Swiss Plasma Center (SPC) within the School of Basic Sciences at École Polytechnique Fédérale de Lausanne (EPFL). He holds concurrent Lecturer positions in the School of Engineering (SB-SPH) and the School of Humanities and Social Sciences (CDH-SHS). His career spans plasma physics for nuclear fusion, mathematical modeling of complex systems, and archaeology of the Roman and pre-Roman eras. Education : High School Diploma from Liceo Classico Vincenzo Gioberti (1988); Bachelor/Master in Physics from Universita di Torino (1994); Ph.D. in Plasma Physics from Imperial College London (1998); Post-Doc at MIT (2002-2007). His research focuses on plasma diagnostics and magnetic sensor development for tokamaks like JET, TCV, and ITER. He pioneered LTCC sensors and real-time MHD instability detection algorithms (e.g., SparSpec). His work bridges fusion engineering and archaeology , with publications on Etruscan civilization and Pharaonic trade routes. Recent articles highlight advancements in photolithography-based magnetic sensors for DTT and DEMO, high-frequency diagnostics across tokamaks, and fast ion transport modeling . He has received European Community Research Training Grant , Ph.D. Fellowship , and Post-Doc Fellowship . Scientific Awards European Community Research Training Grant (1995) Ph.D. Fellowship (Imperial College London, 1995-1998) Post-Doc Fellowship (MIT, 1998-2007) Testa has mentored numerous Ph.D. students (e.g., Theodoros Panis, Christian Schlatter) and post-doctoral researchers , while contributing to MOOC courses and tutorials on plasma physics. His leadership in international collaborations (EPFL, MIT, UKAEA) underscores his role in fusion technology and diagnostic systems .

• Drug Discovery
• Biosensors
• Implantable Medical Devices
• +۳ مورد دیگر

Andrea Cavalli is an Adjunct Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with both the VPA-AVP-CP CECAM-GE unit and the School of Basic Sciences (SB) within the ISIC department (SB-CECAM). His research focuses on advanced biosensor technologies, implantable medical devices, and personalized medicine applications. He teaches a course on drug discovery, emphasizing computational methods for drug design and pharmacokinetics. Key research interests include nanotechnology-driven biosensors, biocompatible materials for implantable devices, and multiplexed detection systems for infectious diseases. Cavalli leads projects on in vivo validation of biochips for metabolic monitoring and integrates electrochemical sensors with circuit design for real-time diagnostics. His work spans from fundamental material science to clinical translation, with a focus on HIV/tuberculosis diagnostics and chronic disease management. PhD Student: Alessia Ghidini Lab: CECAM (European Center for Atomistic and Molecular Simulations) Key collaborations: Molecular diagnostics platforms, nanomaterials for bioelectronics Publications highlight innovations in nanoplasmonic biosensors, biocompatible packaging solutions, and CNT-based bioelectronics. Ongoing work explores remote patient monitoring systems and multipanel biosensors for personalized therapy optimization.

Andrea Ridolfiمشاهده پروفایل

استاد

• Communication Technologies
• Information Processing
• Sensor Networks
• +۷ مورد دیگر

Andrea Ridolfi is a Professor at Bern University of Applied Sciences (BFH), School of Engineering and Computer Science, and a Lecturer at École Polytechnique Fédérale de Lausanne (EPFL). He is affiliated with the Department of Electrical Engineering and Information Technology at BFH, where he contributes to both teaching and research in communication technologies and information processing. His research interests include: Sensor Networks Internet of Things (IoT) Signal Processing for Communications Stochastic Processes Biomedical Portable Devices Mobile Sensors Andrea Ridolfi teaches undergraduate and graduate courses such as Digital Signal Processing, Communication Networks, Wireless Communication Systems, and Statistical Signal and Data Processing. His international academic engagement includes lecturing at EPFL, reflecting his strong technical and pedagogical expertise. He is fluent in English, French, Italian, Spanish, and German, with professional working proficiency in German, and has intercultural experience across Switzerland, Italy, France, the United States, Canada, and Spain. Prof. Dr. Ridolfi is actively involved in advising and curriculum development, though specific grants or student supervision details are not mentioned. He is passionate about human-centered technologies and outdoor activities such as mountaineering, climbing, skiing, paragliding, and mountain biking.

Olivier Verscheureمشاهده پروفایل

استاد مدعو

• Stream and Big Data Mining
• Geospatial Analysis
• Large-scale Data Management
• +۴ مورد دیگر

Olivier Verscheure serves as the Executive Director of the Swiss Data Science Center (SDSC), a national R&D center organizationally hosted by both École Polytechnique Fédérale de Lausanne (EPFL) and ETH Zurich. He also holds multiple Adjunct Professor appointments at EPFL, specifically within the School of Computer and Communication Sciences (SIN and SSC) and the School of Engineering (SEL). His educational background includes: Ph.D. in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL), June 1999 Verscheure's research focuses on the intersection of data science and real-world applications. His work centers on stream and big data mining, geospatial analysis, and large-scale data management. These technical capabilities are applied across diverse domains including personalized health and medicine, Intelligent Transportation Systems, telecommunications, smart building technologies, Smart Grid infrastructure, healthcare analytics, and waste water management systems. His approach emphasizes creating practical data science solutions that address complex challenges in these sectors while considering the constraints of real-world deployment. An analysis of his recent publication record reveals a strong focus on real-time data processing and analytics, particularly for transportation and urban systems. His work frequently addresses challenges in handling massive time series data, developing efficient architectures for low-latency analytics, and creating practical applications for smart city infrastructure. There's a clear progression from theoretical data science contributions to production-ready systems that can process billions of data points daily, demonstrating his ability to bridge research and practical implementation. His notable achievements include: Two IBM Outstanding Technical Achievement Awards Best Paper Award for his research Student Best Paper Award Verscheure has substantial experience in research leadership and mentoring. During his tenure at IBM, he managed the Exploratory Stream Analytics research group and led a technical and management team of approximately 40 people at the IBM Research lab in Ireland. He has served on PhD committees at major universities and published nearly 100 research papers that have garnered over 2,400 citations. His work has resulted in more than 40 US and international patents, demonstrating both academic and practical impact. As Executive Director of the Swiss Data Science Center, Verscheure oversees a distributed multi-disciplinary team working across domains including personalized health, transportation, earth and environmental science, social science and digital humanities, and economics. The center aims to federate data providers, data and computer scientists, and subject-matter experts around a cutting-edge analytics platform while addressing security and privacy issues. Under his leadership, the SDSC develops embedded data science support, offers end-to-end data science services, and fosters a community to share tools and knowledge in data science.

• Autonomous Driving
• Computer Vision
• Robotics
• +۵ مورد دیگر

Holger Caesar is a tenured Assistant Professor at Delft University of Technology (TU Delft) in the Intelligent Vehicles Lab . He leads research on scalable approaches for autonomous vehicle perception, prediction, and data annotation, with a focus on sensor fusion, domain adaptation, and minimal supervision. His work has been cited over 15,000 times. Education PhD in Computer Vision, University of Edinburgh Prior studies at KIT Karlsruhe, EPF Lausanne, and ETH Zurich Research Interests span autonomous driving perception, weakly supervised learning, novel view synthesis (NeRFs), diffusion models, and collaborative perception. He emphasizes reducing reliance on manual annotations through active learning and partial labeling techniques. Recent Publications include work on 4D Gaussian Splatting, camera-radar fusion, open-set scene graph generation, and safety benchmarking. These reflect trends toward multi-modal perception, robust sensor fusion, and foundation models for scalable autonomous systems. Scientific Awards ELLIS Europe Scholar (2024) TU Delft Cohesion Grant (100k EUR, 2024) Climate Action Grant (30k EUR, 2024) TKI High Tech Systems Grant (502k EUR, 2022) AiNed XS Grant (80k EUR, 2023) Argoverse Scene Flow Challenge Winner (unsupervised track, 2024) Advising & Grants include EU Horizon funding for the MOSAIC project (1 PhD and 1 Postdoc, 2024), EU KDT Cynergie4MIE grant (450k EUR, 2024), and industrial collaborations with Bosch, Motional, and partners across Europe. Labs & Teams include the Intelligent Vehicles Lab at TU Delft and founding roles in Motional's Data Annotation, Autolabeling, and Data Mining teams. He co-organizes workshops at ICCV, CVPR, and NCCV, and leads the ELLIS Delft Unit seminar series.

Seonwook Parkمشاهده پروفایل

پژوهشگر

• Eye Tracking
• Deep Learning
• Gaze Estimation
• +۳ مورد دیگر

Seonwook Park is a Researcher at Lunit Inc. , focusing on advancing eye-tracking technology through deep learning. He earned his PhD in June 2020 from ETH Zurich 's Department of Computer Science under the supervision of Prof. Dr. Otmar Hilliges. His research bridges eye tracking and deep learning , aiming to make eye-tracking accessible in uncontrolled, everyday environments. This includes gaze estimation from monocular RGB images, real-time 3D gaze tracking, and self-learning transformations for gaze redirection. His work often intersects with computer vision and human-computer interaction , as seen in his contributions to UI adaptation via eye movement analysis. His publication record spans top conferences like NeurIPS , ECCV , and ICCV , reflecting expertise in gaze estimation , hand pose estimation , and visual SLAM . Notably, he won the Best Presentation Award at ETRA 2018 . He has supervised multiple theses, including MA and BA projects, and served as a teaching assistant for courses such as Machine Perception and Human-Computer Interaction at ETH Zurich.

• Embedded Systems
• AI Algorithms
• FPGA/VHDL Design
• +۵ مورد دیگر

Jürgen Wassner is a Professor of Edge Computing and Co-Head of the Competence Center for Intelligent Sensors and Networks at the Lucerne School of Engineering and Architecture (HSLU T&A). He holds a master's degree from Technical University of Dresden and a PhD from ETH Zurich. His career spans industry roles in Silicon Valley Group Inc. and telecommunication R&D before joining academia in 2007. His research focuses on embedded systems, AI at the edge, FPGA/VHDL design, real-time systems, and powerline communication . He leads projects such as 'Visual-Servoing Testbed with AI-Hardware in the Loop' and 'Low-Cost High-Performance Intelligent Camera for Space Debris Mitigation,' collaborating with companies like Diehl Aerospace. Recent publications emphasize wire fault detection using powerline communication, AI-based odor classification systems, and hardware acceleration for CNNs. His work bridges theoretical research with practical applications in avionics, rail freight, and space debris mitigation. Wassner advises Master of Science in Engineering students and has been recognized for his media engagement including a feature in the Luzerner Zeitung. He teaches Digital Design (FPGA, VHDL) and Digital Signal Processing , emphasizing hands-on implementation of cutting-edge systems.

Christian Vogtمشاهده پروفایل

مدرس

• IoT and Embedded Systems
• Wireless Sensor Networks
• Medical Electronics
• +۳ مورد دیگر

Dr. Christian Vogt Dr. Christian Vogt is a Lecturer at the Department of Information Technology and Electrical Engineering within the Center for Project-Based Learning at ETH Zürich. His research focuses on IoT systems, embedded electronics, and wearable technology with applications in agriculture, healthcare, and urban computing. He specializes in energy-efficient sensor networks, flexible electronics, and real-time data transmission systems. Research Interests Vogt's work bridges hardware innovation and software optimization, emphasizing practical implementations through project-based learning. Key areas include: IoT and Wireless Sensor Networks Low-power embedded machine learning Wearable biomedical devices Flexible/stretchable electronics Ultra-wideband and radar-based sensing Publications Recent work highlights energy-efficient livestock monitoring systems using LoRa, battery-free sensor nodes powered by human body energy, and real-time gesture recognition with novel sensors. His research often involves interdisciplinary collaborations between computer science, electrical engineering, and biomedical applications. Affiliations ETH Zürich - Center for Project-Based Learning Department of Information Technology and Electrical Engineering Contact: christian.vogt@pbl.ee.ethz.ch

• Seismology
• Geophysics
• Seismic Tomography
• +۵ مورد دیگر

Prof. Dr. Andreas Fichtner is a Full Professor of Seismology and Wave Physics at ETH Zurich's Department of Earth and Planetary Sciences. He leads research in seismic tomography, fiber-optic sensing, and high-performance computing, deploying innovative techniques for imaging Earth's interior. His work includes developing distributed fiber-optic sensing for seismic monitoring in urban areas, volcanoes, and glaciers. Beyond seismology, he explores applications in medical ultrasound imaging and metamaterial design. Research interests span seismic wave inversion, uncertainty quantification, and fiber-optic technology. Notable achievements include co-founding Mondaic, a spin-off providing full-waveform modeling solutions. Awards include the 2011 Keiiti Aki Award (AGU), 2015 Early Career Scientist Award (IUGG), and 2018 Hoffmann Prize. He currently serves on the Board of Directors of the Seismological Society of America. Key contributions include pioneering fiber-optic seismology in ice streams and volcanoes, advancing multi-scale inversion methods, and integrating seismic data for continental-scale tomography. His research bridges geophysics with engineering, medical imaging, and computational science.