جست‌وجوی استاد و پژوهشگر

• Sustainable Construction Materials
• Recycled Concrete Technology
• Machine Learning Applications in Civil Engineering
• +۳ مورد دیگر

Julien Ston is a Researcher and Lecturer at the University of Applied Sciences and Arts of Fribourg, specifically within the School of Engineering and Architecture. His work focuses on advancing sustainable construction materials through innovative research approaches that combine traditional materials science with modern computational techniques. His research interests span sustainable construction materials with particular expertise in recycled concrete technology, machine learning applications in civil engineering, and biomass waste utilization. Ston's work addresses critical challenges in the Swiss construction industry, where natural aggregate resources are becoming increasingly limited while demolition waste presents both a challenge and opportunity for sustainable development. Ston's recent publications demonstrate a strong focus on developing predictive models for recycled concrete performance using machine learning techniques, with particular attention to fine recycled aggregates which represent 70-80% of concrete volume but remain underutilized due to performance uncertainties. His work bridges the gap between theoretical models and practical applications in sustainable construction. His research has been supported by significant funding through multiple projects totaling over 575,000 CHF, reflecting the importance and relevance of his work to the construction industry's sustainability challenges. Current projects focus on developing adaptive tools for concrete formulation, optimizing recycled concrete mix designs using artificial intelligence, and creating new ecological concretes based on bio-based lightweight aggregates. Ston collaborates extensively within the Institut iTEC and with colleagues across the School of Engineering and Architecture, contributing to a vibrant research community focused on sustainable construction solutions. His work has practical applications for concrete producers seeking to incorporate higher percentages of recycled materials while maintaining structural performance requirements.

• Pattern Recognition
• Applied Machine Learning
• Document Analysis
• +۴ مورد دیگر

Andreas Fischer is an Ordentlicher Professor at the Fribourg School of Engineering and Architecture (HES-SO), specializing in Pattern Recognition, Machine Learning, and Document Analysis. His research focuses on handwriting recognition, graph-based methods, and applications in cultural heritage preservation and medical imaging. Education: BSc in Computer Science from Fribourg School of Engineering and Architecture Research Interests: Graph Neural Networks for automata universality analysis Hybrid systems for Vietnamese stele keyword spotting Medical image analysis (colorectal cancer, tumor budding) Large language models for post-OCR correction Key Projects: TAINA Technology (handwriting validation for tax forms) Swisscom (Swiss German to High German translation) Hasler Foundation (Vietnamese stele graph-based analysis) Publications: Over 30 peer-reviewed articles in top journals/conferences (IEEE Access, Medical Image Analysis, Pattern Recognition, etc.), with focus on graph-based methods, handwriting recognition, and medical applications. Grants & Roles: Principal Applicant for multiple industry-funded projects (TAINA, Swisscom) Co-developer of DIVA-DAF deep learning framework

• User Experience Design
• Geospatial Technologies
• Gamification in Education
• +۳ مورد دیگر

Romain Sandoz is an academic Researcher affiliated with the Department of Communication and Media Engineering (COMEM) at the Haute école d'Ingénierie et de Gestion du Canton de Vaud (HES-SO Valais/Wallis). He specializes in interdisciplinary research at the intersection of geospatial technologies, user experience design, and education innovation. His work focuses on applying gamification to enhance learning experiences in technical fields, developing pedestrian mobility solutions for accessibility, and advancing audiovisual production methodologies. Education: BSc in Computer Science and Communication Systems from HES-SO Valais/Wallis. He has contributed to projects like the CrowDPLOS initiative (2017–2018), which addressed disabled pedestrian routing through crowdsourced data, and collaborated on a gamified SQL learning tool (GeoSQL Journey) for geospatial education. Key research interests include: Pedestrian-centric urban mobility systems Accessibility solutions for disabled populations Interactive educational technologies Audiovisual content strategy Recent publications highlight his work on citizen-participatory frameworks for improving walkability (2021), crowdsourced navigation tools for accessibility (2019), and gamified geospatial education (2018). He has collaborated with teams across multiple institutions including the VS - Institut Informatique and Fondation FONSART. Grant participation includes a Hasler Foundation-funded project (CHF 49,300) and a DIVERS-funded media interface development initiative (CHF 50,860).

Gabriele Bavotaمشاهده پروفایل

استاد

• Software Engineering
• Artificial Intelligence
• Data Mining
• +۷ مورد دیگر

Gabriele Bavota is a Full Professor in the Faculty of Informatics at the Università della Svizzera italiana (USI). He holds a Laurea (cum laude) and PhD in Computer Science from the University of Salerno (2013). Before joining USI in 2016, he was an Assistant Professor at the Free University of Bolzano-Bozen (2014–2016) and a research fellow at the University of Sannio (2013–2014). Research Focus: Software maintenance, mining software repositories, empirical software engineering, and AI-driven code analysis. Awarded the 2018 ACM Sigsoft Early Career Researcher Award and leads the ERC Starting Grant project DEVINTA, exploring deep learning applications in software engineering. Authored over 180 publications in top venues like ICSE, FSE, and TOSEM, with multiple best/distinguished paper awards. His work bridges empirical studies, AI tools, and developer-centric solutions, addressing challenges in code quality, refactoring, and automated testing. He has served as program chair for ICPC 2016, SANER 2017, and ICSME 2023, and holds editorial roles in TSE, EMSE, and JSS. Labs/Teams: Principal Investigator of the DEVINTA project and part of the Software Institute at USI, fostering collaborations in AI, software engineering, and empirical research.

• Machine Learning
• Biomedical Informatics
• Medical Genomics
• +۳ مورد دیگر

Prof. Gunnar Rätsch is a Full Professor in the Department of Computer Science at ETH Zürich and Deputy Head of the Institute for Machine Learning. His research focuses on developing machine learning methods for biomedical applications, including genomics, medical imaging, and clinical decision support systems. He specializes in integrating multi-omics data, spatial transcriptomics, and time-series analysis to address challenges in precision medicine and critical care. His work emphasizes ethical AI frameworks, algorithmic fairness, and robust clinical prediction models. Key research areas include: Deep learning for medical imaging and histopathology Single-cell analysis and tumor profiling Reinforcement learning for treatment optimization in ICUs Multimodal data integration for clinical applications Recent work highlights advancements in: Standardizing single-cell cytometry readouts for clinical use Developing foundation models for critical care time-series analysis Creating interpretable survival models for ICU patients His contributions span foundational machine learning theory and applied healthcare technologies, with a focus on translational research to improve clinical outcomes. Current projects include the Tumor Profiler Study for multi-omic tumor analysis and ethical frameworks for clinical AI systems.

Shreyasvi Natrajمشاهده پروفایل

پژوهشگر

• Biomedical Engineering
• Artificial Intelligence
• Neuroscience
• +۳ مورد دیگر

Shreyasvi Natraj is a doctoral student at the Department of Health Sciences and Technology (D-HEST) at ETH Zurich, Switzerland. She holds a Bachelor of Engineering in Biotechnology from R.V. College of Engineering (2015-2019) and a Master of Science in Neuroscience from the University of Geneva (2019-2022). Her interdisciplinary work bridges biomedical engineering, artificial intelligence, and hardware development. Research Interests: Biomedical device prototyping Neural network applications in healthcare Low-cost environmental/safety technologies Human-computer interaction for accessibility Projects: $50 Bacteriological Incubator Assist Bot (AR/VR sensor-based robot) Water purification module Puri-Pod Toxic gas analyzer for salt farmers CovARC (COVID risk calculator web app) Her academic journey includes research assistantships at NCCR Synapsy (2019-2023), technical roles at CERN (2018-2022), and co-founding the EPFL startup NeuralWorks. She actively contributes to GitHub repositories related to medical diagnostics and environmental monitoring.

• Computer Graphics
• Rendering Techniques
• 3D Visualization
• +۳ مورد دیگر

Markus Portmann is a Researcher in the Department of Computer Science at ETH Zürich, specifically within the Computer Graphics group. His affiliation is listed under the Professorship for Computer Science (Computer Graphics). He is based at the Universitätstrasse 6, 8092 Zürich, Switzerland, and can be reached via email at markus.portmann@inf.ethz.ch. While specific research interests are not detailed in the provided text, his affiliation with the Computer Graphics department suggests a focus on areas such as rendering algorithms, 3D modeling, virtual environments, and visualization technologies. No information on academic awards, grants, or advised students is explicitly mentioned in the text.

Kai Hormannمشاهده پروفایل

استاد

• Computational Sciences
• Geometric and Visual Computing
• Informatics
• +۳ مورد دیگر

Kai Hormann is a full professor in the Faculty of Informatics at Università della Svizzera italiana (USI Lugano). He earned his Ph.D. in computer science from the University of Erlangen-Nürnberg in 2002 and has held positions at Clausthal University of Technology, Caltech, and the CNR in Pisa. His research focuses on mathematical foundations of geometry processing, including barycentric coordinates, subdivision algorithms, and rational interpolation. Hormann has authored over 100 publications and serves as an associate editor for journals like Computer Aided Geometric Design and Dolomites Research Notes on Approximation . In 2024, he received the prestigious John A. Gregory Award for his contributions to geometric modeling. Education : Ph.D. in Computer Science, University of Erlangen-Nürnberg (2002) Diploma in Mathematics, University of Erlangen (1997) Abitur, Leibniz-Gymnasium Bad Schwartau (1992) Research Interests : Hormann’s work bridges computer science, applied mathematics, and engineering. His current projects include interactive shape deformations, time-dependent object processing, 3D visualization, and GPU-accelerated algorithms. His research areas encompass geometry processing, computational sciences, and numerical analysis. Publications : His recent articles focus on barycentric coordinates, subdivision schemes, and surface reconstruction. Themes include transfinite coordinates, curvature continuity, and efficient interpolation methods. Awards : John A. Gregory Award (2024) Chair of SIAM Activity Group on Geometric Design (2017–2018) Advising & Grants : He has advised numerous PhD students, including work on barycentric rational curves and subdivision schemes. He has organized conferences such as the SIAM GD and GMP series, reflecting his leadership in computational geometry. Labs & Teams : Hormann is affiliated with the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI), collaborating on interdisciplinary projects in AI and geometry processing.

• Machine Learning
• Artificial Intelligence
• Data Science
• +۳ مورد دیگر

Andreas Fischer is a Full Professor at the Department of Computer Science, University of Fribourg, affiliated with the Faculty of Science and Medicine. His academic work focuses on theoretical and applied aspects of computer science, particularly in areas bridging data-driven methodologies and algorithmic innovation.

• Neuromorphic Computing
• Robotics
• Cognitive Systems
• +۳ مورد دیگر

Prof. Dr. Yulia Sandamirskaya is a faculty member at Zurich University of Applied Sciences (ZHAW) in the School of Life Sciences and Facility Management. She leads the Institute of Computational Life Sciences and is an ORCID-registered researcher with a focus on neuromorphic computing and cognitive systems. Her work bridges computational neuroscience with practical robotics applications. Robotics for dementia care Neuromorphic computing Embodied AI systems Spiking neural networks Industrial force-control systems Human-robot interaction Her recent publications demonstrate expertise in neuromorphic architectures for sensory processing, including visual scene understanding, spectral classification, and real-time control systems. She actively contributes to setting benchmarks in neuromorphic computing and develops practical applications in healthcare robotics. Current projects include RobotCare (service robots for elderly care), Neuromorphic Technology for Embodied AI , and Emerging AI (completed). She collaborates with institutions in Switzerland, UAE, and Italy while working on industrial applications of neuromorphic systems.

Yang Liuمشاهده پروفایل

دانشیار

• Bioinstrumentation
• Optical Imaging
• Augmented Reality
• +۱ مورد دیگر

Yang Liu, PhD is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Iowa . His research focuses on bioinstrumentation, optical imaging, augmented reality, and computer vision, with applications in clinical settings such as Cleveland Clinic. Dr. Liu has secured grants from prestigious organizations including the US Army, US Air Force, NASA, and the Frederick Gardner Cottrell Foundation. His work has been highlighted by national media outlets like DoD Research Highlights and CNBC TV. Education: PhD from Washington University in St. Louis (2013) Awards: Young Investigator award from the International Society of Computer Aided Surgery Collaborations: Emphasizes multidisciplinary teamwork in research

Cinthia Piamontezeمشاهده پروفایل

پژوهشگر

• X-ray absorption spectroscopy
• Correlated magnetic materials
• Complex oxides
• +۵ مورد دیگر

Cinthia Piamonteze is a Senior Scientist at the Laboratory for Condensed Matter within the Center for Photon Science at the Paul Scherrer Institute (PSI) in Switzerland. She is an expert in x-ray absorption spectroscopy applied to correlated magnetic materials and has played a pivotal role in the construction and commissioning of the X-Treme beamline at PSI. Dr. Piamonteze completed her PhD in physics at the University of Campinas, Brazil, working at the Brazilian Synchrotron Light Source (LNLS), followed by postdoctoral research at the Advanced Light Source at Lawrence Berkeley National Laboratory. She joined PSI in 2007 where she continues her research as a senior staff scientist. Her primary research interests include: Discovery and investigation of novel magnetic properties at complex oxide interfaces Control of magnetism by external stimuli such as electric fields or strain Understanding the ground state of van der Waals magnets Application of x-ray absorption spectroscopy, x-ray linear dichroism, and x-ray magnetic circular dichroism techniques Dr. Piamonteze's recent publications (2023-2024) demonstrate a continued focus on two-dimensional electron gases, oxide surface properties, and advanced techniques for x-ray experiments, with significant contributions appearing in high-impact journals like Nature Physics and Nano Letters. Among her institutional responsibilities, Dr. Piamonteze serves as the PSI delegate for the experiment environment workgroup within LEAPS (League of European Accelerator-based Photon Sources) and has been a member of the PSI research committee (Forschungskommission - FoKo) since 2019, which reviews scientific proposals requiring PSI funding.

• Medical Imaging
• Artificial Intelligence
• Image Processing
• +۳ مورد دیگر

Prof. Jérôme Schmid is a Full Professor (Professeur HES ordinaire) at the Haute école de santé - Genève, part of the Faculty of Health. His expertise spans medical image processing, artificial intelligence (AI), and their clinical applications. He leads innovative projects addressing challenges in diagnostics, surgery planning, and medical education. Key roles include Principal Investigator in grants funded by Swiss National Science Foundation, Swiss Innovation Agency, and others. Research Focus: Combines AI with medical imaging for applications such as Parkinson’s disease detection via SPECT, breast lesion analysis using ultrafast MRI, and AI-driven radiography training tools. Projects emphasize interdisciplinary collaboration with hospitals and industry partners. Projects: DeepDAT (2022–2025): AI for Parkinson’s diagnosis via SPECT imaging. SUBREAM (2022–2025): Rapid breast MRI protocols with AI integration. AIRx (2019–2020): AI-based radiography simulation for student training. MyHip (2012–2014): Patient-specific hip arthroplasty planning. Publications: Focus on AI-driven diagnostics, imaging techniques, and medical education. Recent works address drowning detection via post-mortem CT, multimodal AI fusion for breast cancer, and serious games in radiology training. Grants & Partnerships: Swiss National Science Foundation: FAI analysis via multi-modal imaging. Innosuisse: Low-cost X-ray detectors for developing countries (GlobalDiagnostiX). Swiss Cancer Research Foundation: Breast MRI advancements (SUBREAM). Labs/Teams: Collaborates with the Geneva University Hospitals, EPFL, and industry (e.g., Medacta International SA) on hardware and clinical AI solutions.

• Human-Machine Interaction
• Human-Robot Interaction
• Multimodal Interaction
• +۷ مورد دیگر

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

• Computer Vision
• Deep Learning
• Image Processing
• +۳ مورد دیگر

Lettry Louis is an Assistant Professor at HES-SO Valais-Wallis, affiliated with the School of Engineering and the Department of Computer Science and Communication Systems. His research focuses on Computer Vision, Deep Learning, and Image Processing, with applications in intrinsic image decomposition, multi-camera systems, and pattern recognition. He leads projects funded by Innosuisse, including WhiteNightSkEyes (CHF 13'928, 2022–2023) and Calligranalytics (CHF 15'000, 2022–2023), which explore virtual architecture visualization and automated handwriting digitization, respectively. His research contributions include seminal work on unsupervised deep learning methods for image decomposition, adversarial networks, and large-scale pedestrian detection datasets like Wildtrack. He collaborates with academic partners at VS - Institut Systèmes industriels and researchers such as Luc van Gool and Pascal Fua. His projects address challenges in immersive virtual environments and robust computer vision algorithms.