جست‌وجوی استاد و پژوهشگر

• Machine Learning
• DevOps
• Distributed Computing
• +۵ مورد دیگر

Roland Christen is a Senior Research Associate at the Lucerne School of Computer Science and Information Technology, part of the Lucerne School of Applied Sciences and Arts (HSLU). He specializes in software architecture, DevOps, distributed systems, and machine learning applications across healthcare and commerce. Christen actively contributes to STEM outreach initiatives like RobertaRegioZentrum Luzern and YoungTech@hslu, emphasizing education and technology accessibility. His professional expertise spans software design, microservices, agile methodologies, and database technologies. He leads research projects in quantum cryptography, medical image analysis (e.g., psoriasis detection), AI-driven e-commerce, and predictive modeling for tourism markets. Notable outputs include peer-reviewed work on machine learning for dermatology and conference presentations on quantum privacy amplification and GPU computing. Christen holds a Roberta® Teacher Certification from the Fraunhofer IAIS and has contributed to interdisciplinary projects like Deep Neural Yodeling and Skin-App: Medical Severity Grading of Hand Eczema. He also maintains strong ties to applied fields through lab collaborations and industry partnerships, bridging academia and practical innovation.

• Digitalization in Architecture
• Building Information Modeling (BIM)
• Programming and Software Engineering
• +۳ مورد دیگر

Frank Thesseling is a Lecturer at the Institute of Building Technology and Energy (IGE) and the Center for Integrated Building Technology at Lucerne School of Engineering and Architecture (HSLU). He holds a Master of Advanced Studies in Computer Aided Architectural Design from ETH Zurich (2005-2006) and a Graduate Engineer Degree in Architecture from the University of Siegen (1995-2001), recognized as Best Diploma 2001. His professional experience spans academic research and architectural practice, including roles as Researcher at ETH Zurich (2005-2011) and scientific assistant at the University of Siegen (1997-2000). Professionally, he founded KEOTO AG in 2009, serving as CEO, and previously held leadership roles in BIM implementation at firms like Amstein + Walthert AG. His expertise centers on digitalization in architecture, BIM methodologies, energy-efficient construction, and software engineering applications in design processes. He actively contributes to the Verein Innovationspark Zentralschweiz and integrates industry insights into his academic work.

• Computer Vision
• Machine Learning
• Deep Learning
• +۲ مورد دیگر

Thomas Koller is a Professor and Head of the Master's Program in Engineering at Lucerne University of Applied Sciences and Arts, affiliated with the School of Computer Science and Information Technology. His research focuses on computer vision, machine learning, and medical image analysis applications. His primary research domains include: Computer Vision and Image Processing Deep Learning and Reinforcement Learning Medical Imaging and Diagnostic Applications His publications demonstrate strong focus on applying computer vision and deep learning techniques to medical challenges, particularly in dermatology and vascular imaging. Recent work shows increasing emphasis on real-world healthcare applications and interactive systems. Scientific Awards: Best Poster Video Award (2022) aha! Award des Allergiezentrums Schweiz (2017)

Hanna Krasnovaمشاهده پروفایل

استاد

• Social Media
• Digital Integration
• Privacy
• +۴ مورد دیگر

Prof. Dr. Hanna Krasnova is a Professor of Information Systems at the University of Potsdam, specializing in Social Media and Data Science. She previously held an Assistant Professorship at the University of Bern. Her research focuses on the societal impact of social media, including phenomena like 'phubbing' (smartphone-induced snubbing), digital integration of refugees, privacy concerns, and the psychological effects of social media use. Her work has been widely recognized, including a Best Paper Award at ICIS 2013 and extensive media coverage (e.g., CNN, BBC). Her key research areas include digital well-being, privacy calculus, and the sharing economy. She leads projects at the German Internet-Institute on topics like 'Digital Technologies and Well-Being' and 'Digital Integration,' exploring how technology aids refugee integration. Krasnova advises numerous PhD and Master’s students, including Dr. Katharina Baum and Dr. Olga Abramova. Her contributions extend to academic leadership, serving as Doctoral Consortium Co-Chair at ECIS 2018 and Track Chair at multiple conferences. Over 3,000 citations on Google Scholar highlight her scholarly impact. She is also noted for accessible outreach, with her findings featured in global media.

• Architecture
• Building Information Modeling (BIM)
• CAD Software
• +۳ مورد دیگر

Elise Geneviève Hautecoeur is a Lecturer in the School of Architecture, Civil and Environmental Engineering (ENAC) at EPFL, specializing in teaching and research-adjacent roles. She also serves as an Assistant in the Laboratory of Arts for Sciences - Archives of the Imagination. Her expertise focuses on advanced computer-aided design (CAD), integrated DIM modeling, and Building Information Modeling (BIM), emphasizing interdisciplinary collaboration and digital tools in architectural education. Her teaching portfolio includes courses such as 'Advanced CAD and Integrated DIM Modeling' and 'Introduction to BIM,' which emphasize practical skills and software transitions. She contributes to curricula that bridge theoretical concepts with real-world applications in construction and engineering. No scientific awards or research articles are explicitly listed in the provided materials, suggesting her contributions may be primarily pedagogical or administrative. She is affiliated with the Laboratory of Arts for Sciences, which likely explores intersections between artistic and scientific communication in technical fields.

Bertrand Lacourمشاهده پروفایل

مدرس

• Mechanical Engineering
• Design
• Computer-Aided Design (CAD)
• +۲ مورد دیگر

Bertrand Lacour is a Lecturer at the School of Engineering (STI) at EPFL, holding positions in the PAT-GE, SMT-ENS, and SGM-ENS units. He specializes in Mechanical Engineering education, focusing on design, technical communication, and CAD software (CATIA V5). His roles include teaching core courses such as Mechanical Construction I/II and Introduction to Mechanical Design for both Mechanical Engineering (ME) and Microengineering (MT) students. Education: Master of Mechanical Engineering (Dynamique de la Locomotion) from INSA-Lyon (1993-1998). Research interests align with his teaching, emphasizing practical applications of mechanical design and technical communication standards in engineering education. His courses integrate theoretical foundations with hands-on projects to develop students' technical skills.

• Computer Graphics
• Geometry Processing
• 3D Reconstruction
• +۳ مورد دیگر

Dr. Jing Ren is affiliated with the Department of Computer Science at ETH Zürich, holding a role within the Professorship for Computer Science. Their research focuses on computational geometry, 3D reconstruction, and computer graphics, with notable contributions to shape analysis, non-rigid matching, and fabric modeling. Dr. Ren’s work bridges theoretical advancements with practical applications in textile design, architectural modeling, and medical imaging. They collaborate extensively on projects involving functional maps, optimization algorithms, and geometric morphometrics. Key research interests include: Non-rigid shape correspondence and matching Computational modeling of woven fabrics and textiles 3D face and building reconstruction techniques Efficient spectral and discrete optimization methods Recent publications (2022–2024) emphasize innovations in fabric parameterization, Gaussian noise distribution, and rethinking 3D face reconstruction benchmarks. Their work often employs machine learning and functional map frameworks to solve geometric problems across disciplines. Laboratory and team affiliations are not explicitly detailed in the provided materials, but their research aligns with ETH Zürich’s broader initiatives in computer science and engineering. No grants or advising activities are specified in the current data.

• Translational Neuromodelling
• Computational Psychiatry
• Wearable Sensor Technology
• +۴ مورد دیگر

László Demkó is a Researcher at ETH Zürich, affiliated with the Department of Translational Neuromodelling and Computational Psychiatry. His work focuses on integrating wearable sensor technology with clinical rehabilitation, particularly addressing spinal cord injuries and neuromotor disorders. Demkó’s research emphasizes data-driven approaches to gait analysis, upper limb movement assessment, and wheelchair usability optimization. He collaborates across disciplines to develop predictive models for neural networks and biomedical devices. Key research interests include translational neuromodelling, computational psychiatry, and biomechanical engineering. His contributions span sensor validation for clinical use, robotic orthosis design, and modular microstructure fabrication for neuronal networks. Demkó’s methodologies often bridge engineering principles with neuroscientific insights, aiming to improve patient outcomes through technology. Publications highlight advancements in gait characterization post-spinal injury, wearable sensor reliability, and neural stimulation techniques using FluidFM technology. His work demonstrates a commitment to both theoretical innovation and practical clinical applications in neurorehabilitation.

Yijiang Huangمشاهده پروفایل

پژوهشگر

• Robotics
• Structural Engineering
• Automation
• +۳ مورد دیگر

Yijiang Huang is a Researcher affiliated with the Department of Computer-Aided Robotics at ETH Zürich. His work focuses on advancing computational robotics, with a particular emphasis on structural design optimization, robotic assembly processes, and algorithmic fabrication methods. He holds a position within the Professorship for Computational Robotics and contributes to cutting-edge research in multi-robot systems, topology optimization, and sustainable construction techniques. His research integrates robotics with structural engineering to enhance automation in manufacturing and construction. Key areas include non-repetitive robotic assembly, cooperative multi-arm systems, and the development of frameworks for high-performance design optimization. Huang has published extensively on topics such as task and motion planning (TAMP), deflation methods for non-convex optimization, and bespoke interlocking connections for timber structures. His articles highlight innovations like the CantiBox project, which explores robotic assembly of interweaving timber elements, and protocols linking algorithmic design with construction intent. These contributions aim to bridge gaps between computational methods and real-world applications, emphasizing efficiency, sustainability, and precision in robotic fabrication systems.

Sachin Jogمشاهده پروفایل

پژوهشگر ارشد

• Process Modeling
• Optimization
• Sustainable Chemical Processes
• +۳ مورد دیگر

Dr. Sachin Jog is a researcher at ETH Zürich, affiliated with the Department of Chemistry and Applied Biosciences and working within the Professorship for Chemical Systems Engineering. His research focuses on sustainable process systems engineering, with particular emphasis on developing innovative modeling and optimization techniques for chemical processes. His educational background includes: Doctoral Degree from ETH Zürich (2021-2025) under Prof. Gonzalo Guillén Gosálbez Master of Science in Process Engineering from ETH Zürich (2019-2021) Bachelor of Chemical Engineering from Institute of Chemical Technology (ICT), Mumbai (2015-2019) Dr. Jog's research interests span several critical areas in modern chemical engineering: Hybrid modeling techniques combining first-principles and data-driven approaches Optimization of integrated chemical clusters with heat, mass, and power integration Accounting for renewable energy intermittency in chemical process design Multi-objective optimization considering both economic and environmental metrics Sustainable process design aligned with Sustainable Development Goals (SDGs) His recent publications demonstrate a strong progression from fundamental modeling approaches to their application in specific sustainable chemical processes like methanol production from CO2. His work consistently bridges traditional chemical engineering with modern sustainability requirements, showing how renewable carbon technologies can be designed for true sustainability rather than focusing solely on climate change mitigation. Dr. Jog's scientific contributions include: Development of hybrid modeling methodologies for process optimization Frameworks for sustainable process design incorporating SDGs Optimization approaches for integrated chemical clusters using renewable energy His research is supported by the Swiss National Science Foundation (SNF) through the 'Bayesian symbolic learning to aid in the design of sustainable chemical clusters (LEARN-D)' project. Dr. Jog works within the Chemical Systems Engineering group at ETH Zürich, contributing to research on sustainable chemical processes and systems engineering approaches for the chemical industry's decarbonization.

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.

• Embedded Systems
• RF Technologies
• Bluetooth Low Energy (BLE)
• +۴ مورد دیگر

Boegli Alexis is an Associate Professor at Haute Ecole Arc - Ingénierie (HES-SO) since 2018, with a PhD in Science from the University of Neuchâtel. Specializing in embedded systems, RF technologies, and energy-efficient electronics, he focuses on applications requiring high constraints such as energy autonomy and compactness. His research spans BLE-based localization, dielectric elastomer actuators, and energy harvesting for biomedical devices. His educational background includes a BSC in Computer Science and Communication Systems from HES-SO and advanced studies in Microengineering at EPFL. He teaches courses like Electrotechnics I and co-supervises doctoral students in interdisciplinary projects. Key research areas include: RF Localization Systems (BLE AoA/AoD) High-Voltage Electronics for Capacitive Actuators Zero-Power Wearable Energy Harvesting Smart Sensor Networks Recent work demonstrates sub-meter accuracy in IoT localization systems using BLE and developed ultra-high-voltage (7kV) converters for dielectric elastomer actuators. His 2025 research explores inverted actuation cycles for facial prosthetics, reducing energy consumption by 1.5%. Patents include a BLE-based access control system combining RF positioning and video analysis (2022) and a real-time regulatory compliance method for wireless transmitters (2013). Collaboration with EPFL and CSEM drives technology transfer in industrial and biomedical applications. His projects often involve Innosuisse, SNSF, and industry partners.

• Medical Imaging
• Artificial Intelligence
• Image Processing
• +۵ مورد دیگر

Prof. Jérôme Schmid is a Professor at the Geneva School of Health Sciences (Haute école de santé - Genève) in the Department of Medical Radiology Techniques. He specializes in medical image processing, artificial intelligence applications in healthcare, and computer-aided diagnosis systems. His work focuses on improving diagnostic accuracy through machine learning, deformable models, and multimodal imaging fusion. Education includes a Master of Science (MSc) in Health Sciences from HES-SO/UNIL and a Bachelor of Science (BSc) in Medical Radiology Techniques from HES-SO. He also contributed to advanced education programs in 3D technologies in orthopedics and sports medicine through collaborations with the Geneva University Medical Faculty. Research interests revolve around AI-driven medical imaging analysis, specifically in breast lesion detection via MRI, Parkinson's disease diagnosis through SPECT imaging, and fracture recognition in radiographs. He leads projects addressing global healthcare challenges such as affordable imaging systems for low-resource countries and AI integration into radiology education through platforms like AIRx and ImmeRgaMe. Current projects (2022-2025) include DeepDAT (AI for Parkinson's diagnosis using SPECT) and SUBREAM (ultrafast breast MRI protocols). Completed projects span hip arthroplasty planning (MyHip), thermal-tolerant X-ray detectors, and FAI impingement modeling. His work is funded by Swiss National Science Foundation, Innosuisse, and private sector partnerships. Publications span 2015-2025, focusing on image segmentation, AI integration in diagnosis, and medical education innovations. He collaborates with academic partners like Hôpitaux Universitaires de Genève and industry leaders such as Medacta International.

Martin Schützمشاهده پروفایل

مدرس

• Engineering Design
• Computing in Engineering
• CAD
• +۳ مورد دیگر

Martin Schütz is a Lecturer at the Department of Mechanical and Process Engineering at ETH Zürich, where he is affiliated with the Engineering Design and Computing Laboratory. He is responsible for CAD development and integration within the lab, contributing to engineering design and computational methods in mechanical systems. His research interests lie in the domain of engineering design and computing, with a strong focus on computer-aided design (CAD), digital product development, and industrial application of engineering software. His work bridges academic research and industrial practice through hands-on development and system integration. The trend in his professional focus, though not detailed in publications, centers on applied engineering computing and design methodologies, particularly in mechanical systems and industrial collaboration. Scientific awards: None listed. There is no public information on student advising or research grants. Martin Schütz has a strong industry background, having co-founded Tribecraft AG and served as CTO for a decade, which informs his current academic and technical role. He is part of the Engineering Design and Computing Laboratory at ETH Zürich, a research group focused on digital engineering, design automation, and computational tools for mechanical systems.

• Synthesis and Catalysis
• Stereoselective synthesis
• Functional materials
• +۵ مورد دیگر

Prof. Olimpia Mamula Steiner is an Ordinary Professor at the Haute école d'ingénierie et d'architecture de Fribourg (HEIA-FR), part of the University of Applied Sciences and Arts Western Switzerland (HES-SO). She leads research in synthesis, catalysis, and functional materials development from her office in Fribourg, Switzerland. Her educational background includes: BSc HES-SO in Chemistry from HEIA-FR, specializing in Organometallic Catalysis and Organic Chemistry MSc HES-SO in Life Sciences, focusing on Asymmetric Synthesis Bachelor in Chemistry from the University of Fribourg, with emphasis on Chemistry of d and f metals Prof. Mamula Steiner's research spans multiple chemistry domains with strong focus on stereoselective synthesis, nanoparticle development, and functional materials. Her work bridges fundamental chemical research with practical applications in medical diagnostics, environmental monitoring, and advanced manufacturing. She has pioneered innovative approaches to chiral metal complexes, sensors for hazardous compounds like phosgene, and novel materials for electroluminescent displays, demonstrating exceptional interdisciplinary integration. Her publication record reveals consistent expertise in rhenium anticancer complexes, pinene-based ligand systems, and sensor development. Recent work shows increasing focus on medical applications, particularly in cancer research and diagnostic tools, while maintaining strong foundations in synthetic methodology and materials characterization. The interdisciplinary nature of her research is evident in collaborations spanning chemistry, medicine, engineering, and environmental science. Prof. Mamula Steiner actively mentors students and researchers, having supervised PhD work on pinene-pyridine derivatives and their applications. Her laboratory emphasizes sustainable chemistry approaches, including waste-to-resource conversion and eco-friendly manufacturing processes, reflecting contemporary priorities in green chemistry.