Nabil Ouerhani is a Professor in Computer Science at Haute Ecole Arc // HES-SO, leading the 'Interaction Technologies' research group focused on Human-Machine Interaction (HMI), Human-Robot Interaction (HRI), and Industry 4.0 applications. His work integrates IoT, cyber-physical systems, and multi-agent systems to develop innovative industrial solutions. Education: BSc HES-SO in Computer Science - Haute Ecole Arc - Ingénierie Key Research Areas: Collaborative robotics and AI-driven automation Thermal error prediction in machine tools IoT-enabled energy efficiency solutions Virtual/Augmented Reality for industrial safety Recent Projects: BonsAPPs (EU H2020): AI-as-a-Service platform for Deep Edge applications Decolleteur 4.0 (Innosuisse): AI-based Swiss-Type lathe programming system TherMoMac : Hybrid thermal error prediction for machine tools Grants & Funding: BonsAPPs: CHF 5,750,000 (EU H2020) Decolleteur 4.0: CHF 1,217,809 (Innosuisse) ECOMAC25: CHF 439,062 (Innosuisse) Research Collaborations: Industry partners: Tornos SA, NVISO SA, ST Microelectronics Academic partners: University of Bologna, ETH Zurich, SUPSI
Sebastian Probst is a Professor at the Haute école de santé - Genève within the Santé school and Soins infirmiers department. He specializes in chronic wound care, venous leg ulcers, and patient education, with a focus on multidisciplinary interventions, empathy in healthcare, and palliative care approaches. His research integrates clinical practice with technological innovation, such as mobile applications for wound monitoring and machine learning for medical imaging. Probst leads multiple international projects funded by organizations like InnoSuisse and EBNET-STIFTUNG. His work addresses wound healing mechanisms, pain management, and prevention strategies for high-risk populations. He collaborates with universities (e.g., Université de Genève), hospitals (e.g., CHUV), and industry partners (e.g., IMITO AG) to bridge research and clinical practice. Key contributions include developing evidence-based educational interventions for venous leg ulcer patients and advancing AI-driven tools for wound assessment. He co-authored over 20 peer-reviewed articles and book chapters on wound care, empathy in healthcare, and pressure injury prevention. His research emphasizes interprofessional collaboration and person-centered care to improve patient outcomes and reduce healthcare burdens.
Sylvain Boloré is a Teaching Professor at the Geneva School of Health Sciences (HES-SO), part of the Health School. He specializes in patient safety, interprofessional collaboration, and simulation-based education. His research focuses on enhancing clinical performance through experiential learning methods like simulation and serious games, with an emphasis on organizational learning and safety culture improvement. Education: MSc HES-SO/UNIL in Healthcare Sciences BSc HES-SO in Nursing Doctoral thesis: Analysis of interprofessional simulation-based training and its impact on patient safety competencies Research Interests: Patient safety, interprofessional teamwork, simulation-based education, healthcare quality improvement, clinical assessment techniques, and error management in healthcare settings. Projects (ongoing): PrimoSecure : Longitudinal study on novice nurses' transition to professional practice (2025–2027). SIRRIBloc : Review of interprofessional strategies to reduce surgical infections (collaboration with Université de Lyon). DERCI : Multicenter study on clinical reasoning teaching in nursing education (co-applicant). Grants: Fonds de recherche et d'impulsion (CHF 119,120 for PrimoSecure). Bonus Qualité Recherche International (DERCI project). Labs/Teams: IR-HEdS (Institute of Research at HES-SO), collaborating with Geneva University Hospitals (HUG) and international academic partners.
Balestra Gioele is a Full Professor at the Fribourg School of Engineering and Architecture (HES-SO) and Co-Head of the iPrint Institute. His primary affiliations include the BSc HES-SO in Mechanical Engineering, where he teaches CFD simulation and Fluid Mechanics. He leads the ComplexFluidPrint project (since 2019), developing advanced inkjet technologies for complex fluids. His research focuses on fluid mechanics, microfluidics, and rheology, with recent projects addressing micro-manipulation via liquid plugs and composite materials for IoT applications. Research interests include thin film instabilities, droplet dynamics, and industrial applications of inkjet technology. Notable projects include the experimental validation of liquid plug-based micro-manipulation (2020-2022), funded by HEIA-FR, and a collaborative effort on multifunctional composite materials with COMATEC (2019-2021), yielding 250'000 CHF in funding. His work bridges theoretical models, numerical simulations, and experimental validation. Publications span topics like machine learning for inkjet behavior prediction (2023), karst drapery morphogenesis (2021), and instability mechanisms in curved substrates (2018-2020). Current research emphasizes inertial microfluidics, airflow visualization for inkjet systems, and advanced nozzle plate manufacturing (2024). Grants: HES-SO, HEIA-FR, COMATEC Team Collaborations: Over 20 researchers across projects, including Domae Yoshinori, Maturo Jonas, and Gallaire François Labs/Teams: iPrint Institute, ComplexFluidPrint team
Frédéric Montet is a Researcher and Doctoral Student at the Fribourg School of Engineering and Architecture (HES-SO), part of the iCoSys Institute for Complex Systems. His primary role involves leading and contributing to projects focused on smart building technologies, energy efficiency, and machine learning applications. He is the Principal Applicant of the ongoing FACILITY 4.0 project (2019-2021), which develops data-driven solutions for building management and facility optimization using AI and IoT technologies. Research interests include: Machine Learning for energy systems, predictive modeling in smart buildings, radon gas monitoring infrastructure, and integration of large language models into control systems. His work bridges theoretical data science with practical applications in renewable energy management and industrial automation. Key contributions include the BBData 2.0 platform for smart building data integration, predictive domestic hot water temperature modeling in district heating systems, and benchmarking zero-shot time series forecasting models. His projects often involve collaboration with industry partners to co-create scalable ICT solutions. Current focus areas: Optimizing PV installations at grid level, predictive maintenance systems, and ethical challenges in LLM-based control systems for shared appliances.
Prof. François Avellan is a prominent academic at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Basic Sciences and the Department of Mechanical Engineering. His research focuses on hydraulic machinery, particularly Francis turbines, Pelton turbines, and cavitation phenomena. Key areas include CFD simulations, turbine design optimization, and hydropower system analysis. He leads projects like DuoTurbo (counter-rotating hydroturbines for energy recovery) and investigates fluid-structure interactions in off-design turbine operations. His work bridges experimental fluid mechanics with computational modeling, addressing challenges in renewable energy and grid stability. Education details are not explicitly provided in the text, but his extensive scholarly output indicates a strong academic background in mechanical engineering and fluid dynamics. Collaborations with institutions like the Laboratory of Hydraulic Machines (LMH) and the Swiss Federal Institute of Technology underscore his interdisciplinary involvement. Research interests emphasize cavitation dynamics, turbine instability mechanisms, and hydroacoustic resonance prevention. Recent studies explore part-load resonance risks, vortex rope behavior, and the integration of emerging hydropower technologies. His contributions span both fundamental and applied research, impacting turbine efficiency, energy recovery systems, and sustainable energy solutions. Publications highlight advancements in CFD validation, particle-based methods for erosion prediction, and predictive control of unstable flows. Innovations like the Y-junction hydraulic short-circuit and variable-speed pump-turbine simulations demonstrate practical applications of his research. Ongoing work includes multiscale erosion modeling and strategic hydropower potential assessments for Switzerland. Laboratory affiliations include the Laboratory of Hydraulic Machines (LMH), where experimental facilities support his investigations into turbine dynamics and fluid mechanics. His research directly informs industrial practices in hydropower plant design and operational reliability.
Dominique Bonvin is a Professor at the School of Engineering (STI) of École Polytechnique Fédérale de Lausanne (EPFL), holding a position within the Automatic Control Laboratory (LA). His research focuses on advanced process control, real-time optimization, and model-based systems engineering. Key topics include modifier adaptation for uncertain systems, dynamic optimization of chemical processes, and control strategies for reaction systems and energy systems. He has published extensively in top-tier journals such as Computers & Chemical Engineering and Journal of Process Control , with over 450 scholarly works to date. His work addresses challenges in industrial processes like wastewater treatment plants, gas compressors, and solid-oxide fuel cells, emphasizing robustness against plant-model mismatches. Collaborations span global institutions, with notable contributions to bioprocess modeling and control of energy-harvesting systems such as kite power. Research Themes: Real-Time Optimization (RTO), Model Predictive Control (MPC), Process Automation, and Systems Engineering Key Technologies: Modifier Adaptation, Dynamic Optimization, Port-Hamiltonian Systems, and Extent-Based Reaction Modeling His recent efforts include accelerating optimization algorithms (e.g., gradient-directed modifier adaptation) and integrating transient measurements for improved plant modeling. He has also pioneered the use of vessel extents to simplify reaction system analysis, enabling decoupled state estimation without full kinetic knowledge.
Maléna Bastien Masse serves as a Lecturer at the Department of Architecture within EPFL's School of Architecture, Civil and Environmental Engineering (ENAC), and as a Scientist at the Structural Exploration Lab (SXL). Her research focuses on advancing circular economy practices in construction through systematic building reuse methodologies. Her primary research interests include: Developing standardized assessment frameworks for building component reuse potential Creating digital inventories of construction systems (e.g., DISCS database with 102 Swiss buildings) Exploring concrete rubble as structural material through digital fabrication techniques Documenting historical reuse practices in Swiss construction heritage Designing interdisciplinary pedagogy for sustainable building with reused materials Recent publications demonstrate strong emphasis on data-driven approaches to circular construction, with 9 of 10 articles published in 2025 addressing methodological innovations in reuse assessment, material flow analysis, and digital process integration. Her work consistently bridges historical analysis with contemporary engineering solutions. Research is supported by the Swiss National Science Foundation (FNS 105216_192693), EPFL ENAC, and collaborative industry partnerships. She actively contributes to critical practice through conference installations and physical prototypes that demonstrate viable reuse systems. Her laboratory work centers on the Structural Exploration Lab (SXL), where digital tools are developed to enhance precision in deconstruction and material recovery processes. Current projects focus on creating waste-negative concrete structures and optimizing supply chains for reused building components.
Juan Carlos Farah is a Researcher at the École Polytechnique Fédérale de Lausanne (EPFL), holding dual appointments in the Fondation Bertarelli Chair in Neuroprosthétique Cognitive (School of Life Sciences/SV) and the SCI-STI-DG group (School of Engineering/STI). His work bridges neuroscience, artificial intelligence, and educational technology, focusing on innovative applications of AI in learning environments and neuroprosthetics research. Research Interests: Farah’s research spans educational chatbot design, AI-enhanced learning analytics, neuroprosthetic systems, and the ethical integration of technology in education. He has pioneered frameworks for task-oriented conversational agents, blockchain-based learning trace repositories, and gamified computational thinking tools. Key Projects: He contributed to the Graasp Desktop initiative for underconnected African schools and developed the TRACE model for educational chatbots. His work on code review notebooks and bot-mediated software engineering education has influenced pedagogical practices globally. Awards & Recognition: No specific awards listed, but his publications reflect high-impact contributions to IEEE, ACM, and Elsevier journals/conferences. Active in global initiatives like UNESCO’s Unequal World Conference on education equity. Technical Expertise: Proficient in Python, JavaScript, and AI toolkits. Specializes in building scalable educational platforms, learning analytics pipelines, and neuroimaging analysis for cognitive studies.
Gaétan Raynaud is a Researcher and Doctoral Assistant at the École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the Unsteady Flow Diagnostics Laboratory (UNFOLD) within the Institute of Mechanical Engineering (IGM) under the School of Engineering (STI) . His research focuses on fluid-structure interaction, fluid dynamics, and robotics, with applications in areas such as soft robotics, material design, and real-time sensing systems. He contributes to projects like the development of highly agile flat swimming robots and studies on flapping flag dynamics. His work integrates experimental fluid mechanics, computational modeling, and machine learning approaches, such as Physics-Informed Neural Networks (PINNs), to solve complex fluid-structure interaction problems and optimize robotic systems. Labs/Teams: UNFOLD Lab (EPFL), collaborating on interdisciplinary projects involving robotics, fluid dynamics, and soft materials. Technical Expertise: Event-based sensing, soft robotics actuation, data-driven modeling, and computational fluid dynamics.
Soheil Gholami is a Postdoctoral Researcher at the Learning Algorithms and Systems Laboratory (LASA) at the École Polytechnique Fédérale de Lausanne (EPFL) since March 2022. His research bridges robotics and human motor control , focusing on human-robot interaction , task/motion planning , ergonomics , and skill assessment . Prior affiliations include the Human-Robot Interfaces and Interaction (HRII) group at the Italian Institute of Technology (IIT) and the Neuroengineering and Medical Robotics Laboratory (Nearlab) at the Polytechnic University of Milan . Ph.D. in Bioengineering (2022) from Polytechnic University of Milan (Italy) and Italian Institute of Technology (IIT, Genoa) M.Sc. in Control Engineering (2015) from K. N. Toosi University of Technology (Tehran, Iran) His work explores teleoperation interfaces , ergonomic assessment , and scalable control schemes for robots. Key areas include microrobotics for surgery , industrial human-robot collaboration , and adaptive control methods . Articles highlight applications in telerobotics , supernumerary robotic arms , and bio-inspired control systems .
Christophe Fitamen is a Lecturer at the Department of Psychology within the Faculty of Philosophy at the University of Fribourg . He also holds a Senior Assistant position at the same department. His research focuses on the development of working memory in children, particularly examining how goal maintenance , visual cues , and reward value influence cognitive performance. He actively collaborates with Prof. Valérie Camos and Dr. Maximilien Labaronne. Research Interests : Working memory, cognitive strategies, attentional resource allocation, reward processing, visual-spatial cognition, educational psychology. Collaborations : University of Fribourg, University of Neuchâtel, Aix-Marseille University. Teaching : Cognitive development at undergraduate and continuing education levels. Publications (selected): 15+ articles on working memory mechanisms in preschoolers, reward-based prioritization, and cognitive scaffolding techniques across journals like Scientific Reports and Frontiers in Psychology . Current projects investigate attentional resource sharing in memory tasks with ongoing funding from the University of Fribourg.
Prof. Nina Kazanina is a faculty member in the Department of Basic Neurosciences at the University of Geneva’s Faculty of Medicine. She co-directs the NCCR Evolving Language and previously served as an Associate Professor in Psychology and Cognitive Neuroscience of Language at the University of Bristol’s School of Psychological Science. Research focuses on the neural mechanisms underlying language, memory, and cognitive domains Lab employs EEG, MEG, fMRI, and behavioral methods Translational work targets language assessment in neurodegeneration and stroke Recent work explores grammatical abstraction in language models, neural oscillations in syntax, and reward-modulated memory. Her lab investigates how the brain encodes linguistic categories and hierarchical structures, bridging neuroscience and theoretical linguistics. Key translational applications include cognitive assessment across the lifespan. Lab members include postdocs (Theo Desbordes, Berk Gercek, Mamady Nabe, Itsaso Olasagasti) and PhD student Katarina Labancova. Contact: nina.kazanina@unige.ch
Denis Ribeaud serves as Senior Research Associate and Co-Project Director of the Zurich Project on the Social Development from Childhood to Adulthood (z-proso) at the University of Zurich's Faculty of Arts and Social Sciences. Since 2006, he has directed the Zurich Youth Surveys (ZYS), which track youth violence trends in Zurich canton using representative student samples. The z-proso project, ongoing since 2003 with over 1,300 participants, examines longitudinal development of violence and problem behaviors through repeated surveys. His educational background includes: Sociology and Social Psychology studies at the University of Zurich PhD in Criminology from the University of Lausanne, where he worked at the Criminological Institute for several years Ribeaud's research focuses on criminology and developmental psychology, specifically investigating how peer victimization, parenting behaviors, socio-emotional skills, and harsh environments influence violence perpetration, mental health, and substance use across adolescence. His work integrates biological measures (e.g., hair cortisol analysis), ecological momentary assessment, and advanced statistical modeling to map causal pathways in youth development. Key specialties include longitudinal cohort design, transdiagnostic mental health analysis, and validation of behavioral instruments. Recent publications reveal heavy emphasis on multi-method approaches combining biological data with psychological assessments. He explores gene expression changes from victimization, hormonal correlates of aggression, and machine learning applications in EMA data, while consistently addressing Zurich-specific youth cohorts. His articles highlight Switzerland-focused violence research, substance use patterns in immigrant vs. native adolescents, and pandemic impacts on young adult coping mechanisms. No scientific awards were documented in the provided materials. Ribeaud's project leadership implies grant management and student supervision, though specific advisees or funding details are absent. His z-proso role involves coordinating cross-disciplinary teams across 13+ years of data collection, suggesting substantial advisory responsibilities in research design and execution. He directs the z-proso project and Zurich Youth Surveys (ZYS), major longitudinal initiatives based at the University of Zurich. These projects maintain archives of data collections from 2004-2022 and employ interdisciplinary teams for analyzing youth violence, mental health, and social decision-making through combined survey and biomarker approaches.
Stefan Elmer is a Senior Researcher at ETH Zurich specializing in computational neuroscience of speech and hearing. His work investigates neural mechanisms of language processing, bilingualism, and music cognition, with emphasis on how musical expertise influences speech perception and word learning across the lifespan using EEG and neuroimaging techniques. Dr. Elmer's research spans speech neuroscience, hearing neuroscience, and bilingualism, focusing on neural plasticity in interpreters and musicians. Key studies examine cognitive load during simultaneous interpretation, neural correlates of absolute pitch, and age-related changes in temporal speech processing. His work demonstrates how experience in music or language reshapes brain connectivity in dorsal/ventral streams. Analysis of his 2019-2023 publications reveals consistent themes: neural adaptations in simultaneous interpreters, music-language interactions in word learning, and clinical applications for tinnitus/hearing loss. His research highlights EEG-based biomarkers for individual cognitive profiles and lifespan effects of expertise on auditory processing. Dr. Elmer contributes to ETH Zurich's Computational Neuroscience of Speech & Hearing group, which employs interdisciplinary approaches to unravel auditory processing mechanisms through collaborative projects bridging neuroscience, linguistics, and clinical audiology.
