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Francesca StradoliniView profile

Lecturer

• Bioelectronics
• IoT for Medical Monitoring
• Anesthesia Delivery Systems
• +3 more

Francesca Stradolini is a Lecturer at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Electrical Engineering Doctoral School (EDEE). She holds a PhD in Electrical Engineering from EPFL (2018), with prior education in Bio Engineering and Neuroscience from the University of Genoa (2012, 2015). Her current work focuses on R&D engineering for medical devices, emphasizing system lifecycle management, human factors engineering, and compliance with CE/FDA regulations. As an invited guest, she contributes to usability engineering education and interdisciplinary research at EPFL. PhD: IoT Bio-Electronic Multi-Panel Device for On-line Monitoring of Anaesthesia Delivery (EPFL, 2018) MSc: Bio Engineering (University of Genoa, 2015) BSc: Bio Engineering (University of Genoa, 2012) Her research spans bioelectronics, IoT-enabled medical monitoring, and electrochemical sensor development for clinical applications. Key areas include anesthesia delivery systems, wearable diagnostics, implantable devices, and human factors engineering. Her work integrates fluidic systems, noble metal nanostructures, and open-source hardware (e.g., Raspberry Pi) to address challenges in traceability, fouling mitigation, and pharmacokinetic modeling. Scientific recognition includes the Ville de Lausanne Award (2019) , EPFL Outstanding PhD Thesis Distinction (2018) , and a Best Paper Award at MOBIHEALTH (2016) . She has published extensively in journals like IEEE TBIOCAS, Sensors and Actuators B, and IEEE Sensors Journal, with collaborative studies on propofol monitoring, carbon nanoallotrope drug detection, and implantable sensor validation. Her technical expertise includes managing medical device development lifecycles, designing IoT architectures for intensive care, and optimizing electrochemical sensors for stability in undiluted biological fluids. She has contributed to conferences such as IEEE BioCAS, ISCAS, and MOBIHEALTH, focusing on translational studies in personalized medicine and 3D-printed medical systems.

Peter A. FlachView profile

Professor

• Machine Learning
• Artificial Intelligence
• Explainable AI (XAI)
• +3 more

Peter A. Flach is Professor of Artificial Intelligence at the Intelligent Systems Laboratory, School of Computer Science, University of Bristol, where he has been faculty since 1997 and was promoted to Professor in 2003. He currently directs the UKRI AI Centre for Doctoral Training in Practice-Oriented Artificial Intelligence and serves as Vice-President of the European Association for Data Science (EuADS), having previously served as its President. His research centers on rigorous evaluation and improvement of machine learning systems, with seminal contributions to classifier calibration (including Beta Calibration and Precision-Recall-Gain curves), explainable AI frameworks, and data science methodology. He pioneered the extension of CRISP-DM to data science trajectories and developed Explainability Fact Sheets for systematic assessment of XAI approaches. His work bridges theoretical foundations with practical deployment in real-world systems. Analysis of his recent publications reveals a dominant focus on interpretable and reliable machine learning, with strong emphasis on performance evaluation metrics, model calibration techniques, and human-centered explainability. His research increasingly addresses healthcare applications through projects like SPHERE and clinical decision support systems, while maintaining core contributions to fundamental ML theory. His scientific recognition includes prestigious fellowships: Fellow of the European Lab for Learning and Intelligent Systems (ELLIS) Fellow of the European Association for Artificial Intelligence (EurAI) Professor Flach has secured major research funding including UKRI Centre for Doctoral Training grants and EU network funding (TAILOR). He leads extensive collaborations across Engineering, Population Health Science, and international institutions (Monash University, Polytechnic University of Valencia), plus over 20 industry partners in the Practice-Oriented AI CDT including LV= and QinetiQ. His work with the SPHERE project demonstrates successful translation of AI research into residential healthcare settings. He leads the Intelligent Systems Laboratory at Bristol, which develops influential open-source tools including the FAT Forensics Python toolbox for algorithmic fairness and the Explainability Fact Sheets framework. His lab maintains strong connections with the European AI community through ELLIS and EurAI, positioning Bristol as a hub for human-centered and methodologically rigorous AI research.

Tobi DelbruckView profile

Professor

• Neuromorphic Engineering
• Event-Based Vision Systems
• Silicon Retinas
• +6 more

Tobi Delbruck is a titular professor of physics and electrical engineering at ETH Zurich, where he leads the Sensors Group at the Institute for Neuroinformatics (INI) in Zurich, Switzerland. He collaborates closely with Shih-Chii Liu and Giacomo Indiveri as part of the 'hardware groups' at INI. Delbruck has also served as visiting faculty at Caltech and is a Fellow of the IEEE. His work focuses on bio-inspired and neuromorphic event-based sensory processing systems. Professor Delbruck's research spans multiple areas of neuromorphic engineering, with particular emphasis on event-based vision systems and low-power analog VLSI circuits. His work has significantly advanced the field of Dynamic Vision Sensors (DVS), which mimic the human retina's response to changes in brightness rather than capturing full frames. This approach enables extremely low-latency vision processing with minimal power consumption, making it ideal for high-speed applications and robotics. His research has applications in robotics, autonomous systems, and low-power embedded vision. Delbruck is an active contributor to the neuromorphic engineering community, co-organizing the annual Telluride Workshop on Neuromorphic Engineering and serving in leadership roles with IEEE. He has authored numerous influential publications and co-authored books including "Event-Based Neuromorphic Systems" and "Analog VLSI: Circuits and Principles." His jAER (Java Address-Event Representation) project provides open-source tools for real-time event-based sensory processing. Analysis of his recent publications shows a clear trend toward integrating event-based vision with deep learning techniques and applying these systems to practical robotics problems. His scientific achievements have been recognized with multiple awards including: IEEE Fellow Winner of Best Live Demonstration award at ISCAS 2012 Honorable Mention Award from Sensory Systems Technical Committee at ISCAS 2012 Overall Best Student Paper Award and Best Paper Award from Sensory Systems Technical Committee at ISCAS 2010 Winner of the 2006 ISSCC Jan Van Vessem Outstanding European Paper Award Professor Delbruck actively mentors students and has supervised numerous PhD and Master's theses in the areas of neuromorphic engineering and event-based vision systems. His group has secured significant research funding from various sources to support their innovative work in bio-inspired sensory processing. He teaches courses on "Electronics for Physicists II (Digital)" and "Neuromorphic Engineering," helping to train the next generation of researchers in this field. The Sensors Group at INI, which Delbruck leads, operates state-of-the-art facilities for designing and testing neuromorphic vision systems. The group maintains close collaborations with researchers worldwide and has developed several important open-source resources including the jAER project and bias generator design kits. Their work continues to push the boundaries of what's possible with event-based sensory processing, with applications ranging from high-speed robotics to low-power embedded vision systems.

Davide ScaramuzzaView profile

Professor

• Robotics
• Computer Vision
• Autonomous Navigation
• +4 more

Davide Scaramuzza is a Professor and Director of the Robotics and Perception Group at the University of Zurich. He holds a Ph.D. from ETH Zurich and has conducted postdoctoral research at the University of Pennsylvania and Stanford. His research focuses on autonomous drone navigation using visual and event-based sensors, leading to breakthroughs like AI drones outperforming human pilots in racing (Nature 2023). He pioneered algorithms for Mars helicopter navigation and developed the PX4 autopilot system. Key awards include the Kiyo-Tomiyasu IEEE Technical Field Award (2024), ERC Consolidator Grant (2019), and multiple best paper awards. His entrepreneurial ventures include co-founding Zurich-Eye (later Meta Zurich) and SUIND for agricultural drones. He co-authored the textbook Introduction to Autonomous Mobile Robots , widely used in academia. Research spans event camera algorithms, visual-inertial SLAM, and reinforcement learning for agile flight. His lab's work is featured in IEEE Spectrum, The Guardian, and Forbes. He advises UN initiatives on AI for disaster response and nuclear safety. Current projects include Graph-Generating State Space Models (CVPR 2024) and event-based vision for automotive systems (Nature 2024).

• Cartography
• Geomatic Engineering
• Historical Map Analysis
• +4 more

Dr. Yizi Chen is a Researcher affiliated with the Professorship for Cartography at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. Their work focuses on advancing cartographic techniques through AI-driven methods, historical map analysis, and geospatial technologies. Key contributions include automated map vectorization, semantic segmentation of historical maps, and integrating multimodal data for robotic systems. They have published extensively in top-tier journals and conferences, addressing challenges in deep learning applications for geomatic engineering. Education details are not explicitly provided in the text. Research interests include semantic segmentation, generative AI for cartography, and steganography in image translation. Notable publications span topics from eye-tracking segmentation to urban land use mapping, reflecting a strong interdisciplinary approach. Dr. Chen collaborates on projects involving historical map digitization and benchmarking datasets for computer vision tasks. No awards or grants are mentioned. Their work contributes to advancing geomatic engineering through innovative solutions in digital mapping and spatial data analysis.

• Digital Health
• Mobile Computing
• Human-Computer Interaction
• +4 more

Katarzyna Wac is a researcher at the University of Geneva affiliated with the Faculty of Economics and Management and the Information Science Institute . Her work bridges Digital Health , Mobile Computing , and Human-Computer Interaction , focusing on leveraging wearable devices, smartphones, and AI for health and quality of life (QoL) quantification. Research Themes: Digital biomarkers for Alzheimer's and migraines, QoL assessment via ubiquitous computing, peer- and self-reported behavioral data, and QoE of mobile applications. Labs: Leads the mQoL Lab , a platform for interactive, mobile, and wearable-based studies. Her recent publications explore Transformer models for health data analysis, social robots in homecare, and ethical frameworks for digital mental health. She has contributed to standards for proxy-reported QoL measures and personalized drug delivery systems in digital health. The multimodal integration of emotional signals and context-aware QoS/QoE provisioning for m-health services are recurring technical themes. Key collaborations include the MobiHealth project and COPD24 , translating future internet technologies into telemonitoring solutions. Her work spans from foundational studies on mobile cognition to applied ambulatory assessment of affect and health risks.

• Semantic Web and Ontology Engineering
• Agent-Based Modeling
• Knowledge Graphs
• +4 more

Giovanna Di Marzo Serugendo is a researcher affiliated with the University of Geneva (Faculty of Social Sciences, Centre for Informatics) and the Institute of Information Service Science (ISS) . Her work spans semantic technologies, agent-based modeling, and sustainable systems. Research interests focus on Semantic knowledge graphs for regulatory compliance Ontology-driven resource management Self-organizing systems inspired by biological models AI applications in smart grids and urban mobility Digital agriculture platforms for smallholder farmers Recent publications highlight trends in ontology automation using LLMs, agent-based simulations for urban planning, and KG-enhanced compliance frameworks . She leads projects integrating digital twins with smart energy systems and develops bio-inspired coordination paradigms. Supervised works include 17 research projects in these domains. Current technical reports and conference papers explore cybersecurity-safety interdependencies in autonomous vehicles and decentralized event source detection in sensor networks.

Viktor von WylView profile

Assistant Professor

• Digital Health
• Epidemiology
• Public Health
• +6 more

Professor Viktor von Wyl is an Assistant Professor with Tenure Track for Digital and Mobile Health at the University of Zurich's Faculty of Medicine. He is affiliated with the Institute for Implementation Science in Health Care and serves as a DSI professor within the Digital Society Initiative. Since October 2023, he has been a member of the Directorate of the Swiss School of Public Health. He leads the Swiss Multiple Sclerosis (MS) Registry at the Institute of Epidemiology, Biostatistics & Prevention, which combines citizen science with digital health methodologies to improve MS care. He holds a PhD in Epidemiology from ETH Zurich (2008) and a Master’s in Biology from the University of Basel (2002). His professional career includes roles as a data manager for an HIV cohort in Washington, D.C. (2002–2004), an HIV epidemiologist at University Hospital Zurich (2004–2010) and University College London (2010–2011 with SNF support), and a Senior Researcher at the CSS-Institute in Luzern (2011–2014), focusing on end-of-life care and risk adjustment. His research interests prioritize digital epidemiology methodology, including the integration of digital data and citizen science. He explores text analysis via crowdsourcing, public trust in health systems, and factors influencing health behaviors, such as adherence to preventive measures during pandemics. His work addresses challenges in chronic disease management (e.g., MS) and musculoskeletal health through practice-based research networks (PBRNs), leveraging frameworks for interdisciplinary collaboration and implementation science. Scientific Awards: SNF Fellowship (2010–2011) SNF-funded Research at CSS Institute (2011–2014) His grants include SNF support for postdoctoral and CSS research. He co-leads the MAP-U and MAP-Z studies on mental health in conflict and displacement contexts. His advisory work involves the development of frameworks for clinician-patient engagement in PBRNs and the optimization of digital health study designs. He directs the Swiss MS Registry and chairs the Swiss Chiropractic Practice-based Research Network (Swiss ChiCo), advancing musculoskeletal primary care research. Viktor’s labs include the Swiss MS Registry and collaborations within the Institute of Epidemiology, Biostatistics & Prevention. He co-founded the corona immunitas digital ecohort to study pandemic impacts and has pioneered the use of fitness trackers in neurorehabilitation studies through the BarKA-MS initiative.

Tobias KowatschView profile

Associate Professor

• Digital Health Interventions
• Mobile Health (mHealth)
• Conversational Agents
• +5 more

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 .

• Robotics
• Artificial Intelligence
• Computer Vision
• +3 more

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.

• Autonomous Driving
• Computer Vision
• Robotics
• +5 more

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.

Hoda AllahbakhshiView profile

Researcher

• GIScience
• Spatio-temporal data analysis
• Sensor-based human mobility analysis

Hoda Allahbakhshi is a Researcher at the Digital Society Initiative of the University of Zurich , affiliated with the Faculty of Science and Department of Geography . Her work focuses on GIScience , spatio-temporal data analysis , and sensor-based human mobility analysis , particularly addressing accessibility challenges for mobility-restricted individuals. Research Themes include: Development of spatial accessibility analytics frameworks Integration of multi-sensor tracking data (GPS, accelerometers) Age-specific physical activity detection modeling Participatory approaches to urban accessibility mapping Her scientific contributions (2017-2024) analyze mobility patterns through big data and urban infrastructure interactions , with recent emphasis on microscale street elements and inclusive urban environments . Current affiliations: Department of Geography , Digital Society Initiative (University of Zurich).

• Information Security
• Privacy
• Cybersecurity
• +7 more

Kévin Huguenin is a Full Professor and head of the Information Security and Privacy (ISP) Lab at the University of Lausanne (UNIL), within the Faculty of Business and Economics (HEC). His research focuses on security and privacy in distributed systems, mobile/social networks, and interdisciplinary areas such as health informatics and legal aspects of privacy. He has held academic positions since 2016, including Assistant Professor (2016–2020) and Full Professor (2020–present). He previously worked at LAAS-CNRS and EPFL, with postdoctoral research at McGill University. Education: PhD (Computer Science, Université de Rennes, 2010), MSc (Network and Distributed Systems, University of Nice Sophia Antipolis, 2007), BSc (Computer Science, University of Rennes, 2006). He is an alumnus of École Normale Supérieure de Cachan. Research Interests: Interdependent privacy, wearable device security, genomic privacy, privacy-preserving technologies, and the social/human aspects of cybersecurity. His lab collaborates with institutions like CSEM and EPFL on projects such as PrivacyLife (SNF-funded). Recent Work: Focuses on second-hand storage device privacy, shadow health data, and participatory design for privacy solutions. Recent studies include personality inference from wearables and user behaviors in fitness data sharing. Awards: Best Paper Awards at OPODIS’09 and IEEE ICDCS’10, CNRS Excellence Award, and Best Teacher Award in the Master of Information Systems. Grants & Collaborations: Swiss National Science Foundation (SNF), Fondation Hasler, and industry partnerships like Nokia Research Center. Current projects include second-hand device privacy (SNF-funded) and mHealth privacy. Labs & Teams: ISP Lab at UNIL, collaborating with CSEM and EPFL on interdisciplinary projects. Active in program committees for venues like USENIX Security, PETS, and WEIS.

• Human-Computer Interaction
• Automotive Engineering
• Virtual Reality
• +4 more

Marine Capallera is a Researcher affiliated with the HumanTech - Technology for Human Wellbeing Institute at the University of Applied Sciences and Arts Western Switzerland (HES-SO). Her work focuses on Human-Vehicle Interaction (HVI), Virtual Reality (VR) applications for education and disability support, and driver state monitoring using physiological signals. She holds a PhD in Informatics from the University of Fribourg (2023), where her thesis addressed adaptive multimodal systems for driver supervision in automated vehicles. Her research spans projects like AdVitam (funded by Hasler Foundation), which explores collaborative driver-vehicle interaction models, and Pro-GIS, a VR initiative enabling social skills training for youth with intellectual disabilities. She collaborates with institutions like EPFL+ECAL Lab and the University of Fribourg, contributing to datasets on driver physiology and automated driving behavior. Key themes include: 1) Designing HVI systems that maintain driver situation awareness via ambient interfaces and physiological feedback; 2) Developing inclusive VR solutions for special needs populations; 3) Applying machine learning to classify driver states (fatigue, workload) using biometric data. Recent work emphasizes multimodal interaction in automated vehicles and cross-modal emotion integration in VR environments. Grants: Hasler Foundation-funded AdVitam project (2018-2021) Teams: Collaborates with Elena Mugellini, Quentin Meteier, and Omar Abou Khaled in automotive HVI research Labs: Leads VR training modules for nursing education and disability support

• Human Activity Recognition
• Machine Learning
• Sensor Technology
• +3 more

Anna Ferrari is a Researcher at the Research Institute for Statistics and Information Science, University of Geneva. She holds a Ph.D. from the University of Milano-Bicocca and specializes in human activity recognition through sensor-based systems, particularly using inertial data and deep learning techniques. Her work focuses on model personalization and the development of adaptive classification systems for diverse datasets. Her research interests include machine learning applications in sensor technology, data science methodologies for human activity analysis, and the integration of wearable devices. She has contributed to frameworks for collecting and unifying inertial signals to improve activity recognition accuracy. Anna Ferrari's publications span trends in smartphone-based activity recognition, personalized deep learning models, and sensor data homogenization. She actively maintains professional profiles on ResearchGate, LinkedIn, and Google Scholar, reflecting her commitment to academic collaboration and innovation.