Thijs Defraeye is a Senior Scientist at Empa (Swiss Federal Laboratories for Materials Science and Technology) and Adjunct Professor at Dalhousie University. He holds a PhD in Building Physics from KU Leuven (2011) and a Master's in Civil Engineering (2006). His work focuses on optimizing food supply chains through multiphysics simulations and digital twins, addressing challenges in refrigerated transport, postharvest quality preservation, and energy-efficient food processing. He leads the SimBioSys group, developing solutions for perishable goods logistics and electrohydrodynamic technologies. Research interests include: Biophysics of food systems Digital twin applications in agriculture Electrohydrodynamic drying Thermal management in cold chains Sustainable food technologies Recent work emphasizes reducing food loss through physics-based modeling of refrigerated containers, ventilated packaging optimization, and scalable evaporative cooling systems. His studies bridge engineering principles with biological processes, aiming to enhance global food security and environmental sustainability.
Martin Rajman is a Senior Scientist at École Polytechnique Fédérale de Lausanne (EPFL) with multiple affiliations across the institution. He holds positions in the School of Computer and Communication Sciences (SIN - Teaching, SCI IC MR Group, SSC - Teaching) as well as in the Vice Presidency for Strategic Development (VPS Artificial Intelligence) and the Vice Presidency for Academic Affairs (SNAI Administration). He serves as the Executive Director of Nano-tera.ch, a large Swiss Research Program funding collaborative multi-disciplinary projects in Health and the Environment. Rajman's research spans the intersection of artificial intelligence, natural language processing, and information retrieval. His work demonstrates a consistent focus on developing practical applications of computational linguistics and machine learning techniques. Early in his career, he contributed significantly to syntactic parsing, stochastic language models, and vector space representations for text. More recently, his research has expanded into deep learning applications for 3D reconstruction, empathetic conversational agents, and distributed analytics systems. His publications reveal a trajectory from foundational NLP research toward increasingly applied and interdisciplinary work connecting AI with healthcare, environmental monitoring, and human-computer interaction. Analysis of his recent publications (2015-2024) shows a clear evolution toward more applied AI research with strong interdisciplinary connections. While maintaining his core expertise in natural language processing and information retrieval, his work has expanded into computer vision, healthcare applications, and sustainable computing. The publications demonstrate increasing collaboration across disciplines, with applications in medical imaging, mental health support systems, environmental monitoring, and human-centered AI. His leadership role in the Nano-tera.ch program reflects this interdisciplinary approach, connecting computing research with real-world challenges in health and environmental contexts. Rajman has mentored several PhD students including Ailomaa Marita, Eckard Emmanuel, Melichar Miroslav, and Veselý Martin. His research has been supported through the Nano-tera.ch program, which has funded more than 100 research projects with over 95 million CHF in public funding. He has also managed more than 20 European projects during his tenure as Director of the EPFL Global Computing Center. As Executive Director of Nano-tera.ch, Rajman leads a significant research initiative connecting EPFL with national and international partners. His work bridges academic research with industry applications, notably through collaborations with eBay on product ranking technology and with Elsevier on article recommendation systems. His leadership extends to managing large-scale research programs while maintaining an active research agenda and mentoring the next generation of computer scientists.
Dr. Christian Russ is a Senior Lecturer at the Institute of Business Information Technology , Zurich University of Applied Sciences (ZHAW), with expertise in digital transformation, IT leadership, and business-IT alignment. His work spans healthcare, education, and automotive sectors, focusing on agile IT governance and adaptive business models. Current roles: Program Director MAS IT-Leadership and TechManagement Key projects: ZHAW Digital Culture Assessment, Monitoring eCH Standards Research interests include digital transformation , agile IT , health informatics , and emerging technologies . Recent publications analyze post-pandemic organizational culture, medical AI regulation, and cloud infrastructure in healthcare. 2025: Organizational culture shifts during/after pandemic 2024: ML solutions in Swiss hospitals under MDR 2023: iPaaS cloud security in healthcare 2023: Agile transformation in non-profits Scientific recognitions: Best Paper Award at SMART 2018 "Educate to lead" award (Soroptimist International Europa, 2016) Active in the ZHAW Digital Health Lab, he leads projects on tech startup coaching, digital ecosystems, and IT governance. His teaching covers IT strategy, digital transformation, and enterprise service management at ZHAW.
Paolo Prandoni is a Lecturer at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences (IC). He serves as a Scientist in the Audiovisual Communications Laboratory (LCAV) and teaches in the SSC-ENS and SIN-ENS units, focusing on signal processing theory and practical applications in audiovisual communications. He earned his PhD from EPFL after completing all prior education there, driven by childhood fascination with long-distance telephony. His doctoral work established foundations in communication systems that continue to inform his research. Prandoni's research spans audio/image processing, machine learning for media analysis, and DSP education. Key areas include computational photography (e.g., spectral imaging, stained glass rendering), speech quality assessment via transfer learning, music information retrieval (e.g., fingering prediction), and audience analytics through his company Quividi. His work consistently bridges theoretical signal processing with real-world implementation. Recent publications reveal a strategic shift toward machine learning integration in signal processing tasks, particularly non-intrusive speech assessment and lensless imaging reconstruction. Simultaneously, he advances DSP pedagogy through MOOC development and hands-on teaching tools using off-the-shelf hardware, emphasizing accessibility and practical skill development. No scientific awards are documented in the provided materials. He has advised PhD student Thanikachalam Niranjan (thesis: Image Based Relighting of Cultural Artifacts , 2016) and teaches Communication Systems and Computer Science courses. His educational impact extends through the open-access textbook Signal Processing for Communications (2008) and tools like MultiPub for maintainable online classes. Industry engagement includes Quividi co-founding (2006) and ongoing CSO role in attention analytics. As a core LCAV laboratory member, he collaborates on interdisciplinary projects including cultural heritage digitization, embedded signal processing systems, and real-time audience measurement, leveraging EPFL's infrastructure for both academic and commercial applications.
Dr. Alexander Artikis is an Associate Professor of Artificial Intelligence at the University of Piraeus and a Research Associate at the National Centre for Scientific Research (NCSR) "Demokritos". He leads the Complex Event Recognition (CER) group , focusing on symbolic and probabilistic approaches to event recognition and forecasting. University of Piraeus (2025–present) NCSR Demokritos (2017–present) Complex Event Recognition Group (2017–present) His research spans Artificial Intelligence and Distributed Systems , with a focus on: Complex Event Recognition (CER) : Developing logic-based systems for detecting events in real-time data streams Event Calculus : Creating probabilistic and incremental versions for runtime reasoning Multi-Agent Systems : Modeling norm-governed interactions Maritime Informatics : Applying CER to vessel trajectory analysis and fleet management Key publications reveal trends in: Neuro-symbolic forecasting models combining deep learning and logic-based reasoning Symbolic automata with memory for pattern detection Online learning techniques for dynamic event rule generation Tensor-based formalizations for efficient temporal reasoning Handling uncertainty in real-time maritime data streams Optimizing memory usage for scalable stream processing He contributes to open-source tools like RTEC (Run-Time Event Calculus) and holds a European patent on complex event forecasting. His work addresses challenges in: Proactive decision-making systems Knowledge Graph consistency Hybrid human-machine discovery of movement patterns Big Data analytics for time-critical applications
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.
Dr. Christoph Leitner is a Research Fellow at ETH Zurich's Integrated Systems Laboratory under Prof. Luca Benini, focusing on biomedical and IoT applications. His work integrates printed piezoelectric transducers and flexible electronics with energy-efficient systems. He holds a PhD in Biomedical Engineering from TU Graz (2022) and has collaborated with institutions like Sant'Anna School of Advanced Studies and KTH Stockholm. Notable achievements include the Josef Krainer Young Researcher Award and Motorik Scholarship. Leitner's research spans ultrasonics, machine learning, and wearable devices, with contributions to muscle-tendon dynamics and real-time biofeedback systems. Education: PhD in Biomedical Engineering, TU Graz (2022), Advisor: Prof. Christian Baumgartner Previous roles: University Assistant (2006–2011) and R&D Engineer at Virtual Vehicle GmbH Research Interests: Convergent technologies merging biomedical engineering and IoT Ultrasound-based monitoring for musculoskeletal systems Energy-efficient embedded systems for wearable applications Collaborations & Awards: Recipient of Josef Krainer Young Researcher Award (2023) and Motorik Scholarship (2018) Active collaborations with University of Zurich, Veterinary University of Vienna, and Queensland University of Technology Labs & Projects: Integrated Systems Laboratory at ETH Zurich Developed a patented ultrasound-transparent tattoo-based SEMG system with Prof. Francesco Greco
Philip Brunner is a Professor of Hydrogeology at the University of Neuchâtel's Faculty of Science since 2012. He is based at the Center for Hydrogeology and Geothermics (CHYN), leading the Laboratory of Hydrogeological Processes. His work centers on sustainable water resource management through quantitative tools. He earned his PhD from ETH Zurich, focusing on sustainable salt and water management in Western China's agricultural basins. Post-PhD, he conducted three years of postdoctoral research in Australia, developing new approaches for simulating river-aquifer interactions. Brunner's research spans surface water-groundwater interactions, numerical modeling, and remote sensing. He integrates methods from numerical modeling, remote sensing, scientific computing, and isotopic chemistry. His interdisciplinary collaborations with mathematicians, biologists, and physicists address challenges in agriculture, ecohydrology, engineering, and sustainable resource management. Recent publications highlight innovative tracer techniques (noble gases, microbes), low-cost monitoring systems, and advanced numerical models. His work tackles climate change impacts on ecosystems, groundwater in conflict zones, and sustainable practices in diverse environments including mountains and agricultural regions. He teaches courses such as Introduction to Hydrological Processes (Master), Numerical Modeling (Master), Remote Sensing (Master), and Introduction to Soil Physics (Bachelor, in French). His laboratory serves as a center for experimental and computational hydrogeological research.
Christian Weber serves as a Senior Lecturer & Researcher at the Institute of Business Information Technology within the Zurich University of Applied Sciences (ZHAW) School of Management and Law. He directs the CAS Cyber Security program and contributes to the ZHAW Digital Health Lab, focusing on sustainable digital ecosystems and security frameworks. His educational background includes an Executive MBA in General and Entrepreneurial Management from Johannes Gutenberg-Universität Mainz/McCombs School of Business and a Dipl.-Ing in Industrial Electronics & Electrical Power Engineering from RheinMain University of Applied Sciences. His continuing education spans numerous certifications in AI, sustainability, and digital health from institutions including Hasso Plattner Institute. Weber's research centers on sustainable smart solutions for digital ecosystems, including digital health, ambient assisted living, and smart environments. His work explores computer-supported cooperative working scenarios, applications of open source systems in SMEs, and data protection, cybersecurity, compliance, and forensics as enablers for digital ecosystems. His teaching portfolio spans multiple modules in IT Security, Emerging Technologies, IoT-Data Streaming & Analytics, and Digital Transformation across BSc and MSc Business Informatics programs. His recent publications demonstrate strong interdisciplinary connections between cybersecurity, digital health, and organizational transformation, with particular emphasis on practical applications in real-world settings. His work bridges technical implementations with organizational and societal impacts of digital technologies. Best Paper Award at SMART 2018 for "Citizens as Sensors" research "Educate to lead" award from Soroptimist International Europe for STEM outreach Weber's professional experience combines academic leadership with industry expertise, having served as Managing Director of the Cisco Networking Academy since 2012 and holding previous positions as Administrative Professor and Lecturer at University of Applied Sciences Braunschweig/Wolfenbüttel. His industry background includes executive roles as CIO/CTO and IT management consulting. He contributes to the ZHAW Digital Health Lab and has led projects including the ZHAW Digital Culture Assessment and Digital Health Hackathon, focusing on practical implementations of digital health solutions and organizational transformation.
David Atienza is a Professor in the Department of Electrical Engineering at the School of Engineering, Swiss Federal Institute of Technology in Lausanne (EPFL), renowned for pioneering embedded systems education and research in ultra-low power computing. His innovative teaching methods, including using Nintendo DS consoles and smartphones to teach embedded systems, earned him the 2015 EPFL Teaching Award in Electrical Engineering. His research focuses on Embedded Systems , Edge AI , and Wearable Healthcare , with breakthroughs in energy-efficient hardware-software co-design for biomedical applications. Key contributions include open-source platforms like X-HEEP and HEEPocrates for ultra-low power edge computing, and frameworks like SzCORE for seizure detection benchmarking. His work bridges computer architecture with real-world healthcare challenges, emphasizing privacy-preserving algorithms and sustainable computing. Recent publications (2023-2025) reveal a dominant trend toward biomedical edge AI and sustainable computing , with 70% of articles targeting healthcare wearables (seizure detection, cough monitoring) and 30% addressing energy efficiency in data centers and edge devices. His research consistently integrates open-hardware principles (RISC-V) with novel algorithm-hardware co-design. Awards include: 2015 EPFL Teaching Award in Electrical Engineering section While specific advising details are unreported, his extensive publication record and leadership in multi-partner projects like Sustainable Textile Electronics (STELEC) indicate active graduate supervision and significant research funding. His group develops open-source hardware frameworks used globally in academia and industry. He leads the Embedded Systems Laboratory at EPFL, driving projects in ultra-low power RISC-V architectures, biomedical wearables, and sustainable computing. Current initiatives include carbon-aware data center frameworks and multi-modal health monitoring systems deployable on commercial wearables.
Dr. Christina Haag is a postdoctoral researcher at the Institute for Implementation Science in Health Care , affiliated with the Faculty of Medicine at the University of Zurich . She leads interdisciplinary projects at the intersection of mental health, digital health, and computational linguistics, focusing on chronic illnesses like multiple sclerosis (MS). Her work leverages free text, sensor data, and advanced analysis techniques such as hierarchical modeling and natural language processing (NLP). Doctorate from the Institute of Psychology, University of Zurich Research experience at the MRC Cognition & Brain Sciences Unit, University of Cambridge Her research explores: Daily-life mental and physical health indicators in MS Development of NLP methods for text classification and topic modeling Digital biomarker creation using wearable sensor data Mindfulness interventions for affective executive control Implementation of remote monitoring tools in healthcare Her recent publications highlight trends in applying NLP and machine learning to unstructured health data, analyzing MS activity patterns, and refining interdisciplinary research methodologies. She contributes to DSI communities including AI & Law , Health , and Ethics , and collaborates on projects like BarKA-MS and DSI-Approach . She is a core member of the UZH Digital & Mobile Health Group , working under Prof. Viktor von Wyl.
Alexander Damm is a Professor and head of the Remote Sensing of Water Systems (RSWS) group, holding a joint appointment between the Department of Geography at the University of Zurich (UZH) and the Swiss Federal Institute of Aquatic Science and Technology (Eawag). His research integrates advanced Earth observation technologies with environmental science to study water systems under changing climatic and anthropogenic pressures. University: University of Zurich Institutional Affiliation: Swiss Federal Institute of Aquatic Science and Technology (Eawag) Department: Department of Geography Alexander Damm obtained his MSc and PhD in remote sensing from Humboldt-University Berlin. Since 2008, he has been contributing to UZH’s leadership in imaging spectroscopy and Earth observation science. MSc, Remote Sensing, Humboldt-University Berlin PhD, Remote Sensing, Humboldt-University Berlin His research focuses on the fundamentals of remote sensing as applied to terrestrial and aquatic ecosystems, particularly in studying water dynamics and environmental change impacts. He specializes in sun-induced chlorophyll fluorescence (SIF), imaging spectroscopy, and the development of methods to monitor ecosystem productivity, drought responses, and biogeochemical cycles. His work bridges physics, ecology, and environmental engineering to improve understanding of plant-water relations and ecosystem resilience. The recent publications highlight a strong trend in using airborne and satellite-based spectroscopy to assess vegetation health, water stress, forest dynamics, and atmospheric constituents. Key themes include SIF retrieval, drought monitoring, canopy structure modeling, and air quality estimation. These works span applications from croplands and forests to tundra and inland waters, reflecting a broad interdisciplinary approach grounded in quantitative remote sensing. Alexander Damm is involved in several high-profile research initiatives, including: ESA’s FLuorescence EXplorer (FLEX) mission SNSF projects: FLUO4ECO, Spatial-sustainable-finance, DeltAs MeteoSwiss: UrbanNature EU Horizon: NextGenCarbon He leads the RSWS group, which develops and applies cutting-edge remote sensing methodologies for water system monitoring. The team collaborates across disciplines and institutions, focusing on integrating field measurements, airborne campaigns, and satellite data for environmental assessment. Damm’s leadership in projects like FLEX and HyPlant underscores his role in advancing spectroscopic remote sensing for global ecosystem monitoring.
Dr. Burcu Demiray is a researcher at the Department of Psychology, University of Zurich, leading a team focused on real-life cognitive activities in the context of healthy longevity. Her interdisciplinary work integrates smartphone sensing, experience sampling, and machine learning to analyze real-life audio, speech, and text data. She is also developing e-learning concepts for Generation 65+ to combat ageism and enhance digital literacy. Education: Not explicitly detailed in the provided text. Research Interests: Healthy cognitive aging and psychological well-being. Automated semantic analysis of real-life conversations. Machine learning applications in gerontology and memory studies. Digital health interventions and ambient audio monitoring. Publications Trends: Focus on naturalistic observation studies using smartphone sensing and wearable devices. Development of machine learning models for reminiscence and memory function detection. Analysis of gender differences in daily communication and cognitive aging. Scientific Awards: No specific awards mentioned. Labs/Teams: Affiliated with the Healthy Longevity Center at UZH and the Digital Society Initiative (DSI) Community Health.
PD Dr. Kaspar Riesen is the Head of the Pattern Recognition Group at the Institute of Computer Science, University of Bern. His research focuses on graph-based methods for pattern recognition, with applications in document analysis, environmental modeling, and healthcare. Key interests include graph matching, neural networks, and spatio-temporal modeling. His work spans structural pattern recognition, graph embeddings, and keyword spotting in historical documents. Recent projects involve river network analysis using graph regression and hypoglycemia prediction via LSTM-GNN hybrid models. Publications emphasize graph theory advancements, such as normalized graph compression and geometric similarity learning. Collaborations include developing specialized algorithms for automated error detection and improving decision-making in simulated sports. Labs/Teams: Pattern Recognition Group (PRG) at the University of Bern.
Prof. Taekwang Jang is an Associate Professor at the Department of Information Technology and Electrical Engineering, ETH Zürich. He leads the Energy Efficient Circuits and IoT Systems Group, focusing on analog and mixed-signal circuits for energy-constrained applications such as wireless sensor nodes and biomedical electronics. His research includes sensor interfaces, energy harvesters, power converters, and communication systems. He holds 15 patents and has authored over 80 peer-reviewed publications. Key awards include the 2024 IEEE Solid-State Circuits Society New Frontier Award and the SNSF Starting Grant. Educations: B.S. and M.S. in Electrical Engineering, KAIST (2006, 2008) Ph.D. in Electrical Engineering, University of Michigan (2017) Affiliations: Chair of IEEE Solid-State Circuits Society, Switzerland Chapter Associate Editor for Journal of Solid-State Circuits (JSSC) Research Interests: His work spans energy-efficient integrated circuits, biomedical interfaces, and IoT systems. Notable contributions include low-power keyword spotting ICs, ultra-low-noise amplifiers, and neural stimulation systems. He emphasizes practical applications in healthcare and wearable devices. Awards: 2024 IEEE Solid-State Circuits Society Distinguished Lecturer 2022 IEEE ISSCC Jan Van Vessem Award 2009 IEEE CAS Guillemin-Cauer Best Paper Award Advising & Grants: Supervises a team of researchers and has secured grants including the SNSF Starting Grant. His lab collaborates with institutions like the Competence Center for Rehabilitation Engineering and Science. Labs & Teams: Leads the Energy-Efficient Circuits and Intelligent Systems group at ETH Zurich, focusing on interdisciplinary projects at the intersection of circuits, systems, and biomedical engineering.
