جستجوی استاد راهنمای دانشگاهی

• Deep Learning
• Statistics
• Data Science
• +۴ مورد دیگر

Matthias Nyfeler is a Lecturer for Physics and Statistics at the Institute of Computational Life Sciences, Zurich University of Applied Sciences (ZHAW), since 2018. He previously served as a Lecturer at Jönköping University (2016-2018) and as a High School Teacher in Physics and Mathematics (2010-2016). His roles include Programme Director for the MSc specialisation in Applied Computational Life Sciences, Head of the Research Group Advance Signal Analytics, and Head of ICLS statistical consulting. Education: PhD in Theoretical Physics (University of Bern, 2005-2010), Master of Science in Physics (University of Bern, 2006-2009), Teaching Diploma for Physics and Mathematics (PHBern, 2010-2011), Postgraduate Studies in Secondary Education (Jönköping University, 2016-2017). His research focuses on Deep Learning and Statistical Signal Processing for applications like Drone Signal Classification and Bioacoustics . He also contributed to Quantum Antiferromagnetism and Cluster Algorithms earlier in his career. His recent publications highlight Robust CNN-based Drone Detection in low SNR environments and Multiscale Deep Learning for RF signal analysis. He led projects such as ChirpNet for AI biodiversity monitoring and TinyML Grasshopper Classifier. Matthias engages in Statistical Consulting and Mathematical Modeling , with a focus on Physical Computing and Radio Signal Processing . His work spans both academic research and applied technology development, including datasets for drone signal classification.

• Natural Language Processing
• Machine Learning
• Computational Linguistics
• +۷ مورد دیگر

Fernando Benites de Azevedo e Souza is a researcher at Zurich University of Applied Sciences (ZHAW) specializing in Natural Language Processing (NLP) and text analytics. He collaborates across disciplines including cultural management, speech recognition, and low-resource language technologies. Key research areas: NLP applications in arts management, speech-to-text systems, and German dialect identification Active in SwissNLP community and VarDial conference series Focus on practical implementations: e-assessment integrity, transliteration resources, and resource-constrained deep learning His work demonstrates technical expertise in: Comparative analysis of ASR systems (CEASR corpus) Transliteration pattern detection (TRANSLIT resource) Dialect identification challenges Combining lexical and sentiment analysis Scientific achievements include: Ranked first in ALTA 2018 patent classification competition Multiple top-three finishes at VarDial evaluations First place in GermEval 2020 low-resource speech recognition task

Jan Pieter Abrahamsمشاهده پروفایل

استاد

• Structural Biology
• Electron Microscopy
• Protein Crystallography
• +۵ مورد دیگر

Jan Pieter Abrahams is a Professor and Group Leader of the Nanodiffraction group at the Laboratory for Multiscale Bioimaging, Paul Scherrer Institute (PSI) in Switzerland. His work focuses on developing electron diffraction technologies for atomic-resolution imaging of frozen hydrated biological samples, leveraging PSI's detector expertise to advance structural biology beyond conventional microscopy limitations. Current applications target mitochondrial stress mechanisms in neurodegeneration and aging, with active collaborations across international institutions. Research Interests: Abrahams pioneers electron diffraction and cryo-EM methodologies, emphasizing computational-phasing innovations and machine learning integration. His group specializes in: Overcoming dynamical scattering for atomic-level cellular visualization Hybrid pixel detector applications (JUNGFRAU, EIGER) in electron microscopy Deep learning frameworks for diffraction data processing (e.g., DiffraGAN) Structural analysis of protein nanocrystals in disease contexts Mitochondrial protease mechanisms in aging Bacterial cell division and sporulation structures Publication Trends: Recent work (2020–2024) reveals heavy emphasis on AI-driven structural biology, including generative networks for diffraction phasing and lossless data compression. Instrumentation advancements (e.g., Boersch phase shifters) and disease-focused studies (Alzheimer’s amyloid-beta, malaria heme processing) dominate, showcasing interdisciplinary convergence of physics, computation, and biomedicine. Scientific Awards: No specific awards or fellowships documented in source text Advising and Collaborations: Abrahams has mentored PhD students including Thakkar, Pooja; Rheinberger, Jan; Schärer, Martin; and Wennmacher, Julian. His team collaborates with PSI's detector group on sensor development (GaAs/CdTe) and international labs for structural studies. Funding likely stems from PSI instrumentation projects and disease-focused research initiatives. Labs and Teams: He directs the Nanodiffraction group under PSI's Center for Life Sciences, comprising scientists (van Genderen, Latychevskaia) and postdocs (Blum). The lab integrates cryo-EM, electron diffraction, and computational modeling to visualize cellular processes at nanometer scales, with strong ties to detector engineering and pharmaceutical structural analysis.

• 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

• Embedded Systems
• Virtualization of Systems
• Data Processing
• +۴ مورد دیگر

Glück Florent is an Associate Professor at the Geneva School of Landscape, Engineering and Architecture (HES-SO), affiliated with the Technical and IT school's Computer Science and Communication Systems department. He specializes in embedded systems, system virtualization, and interdisciplinary projects at the intersection of engineering and healthcare. Affiliations: HES-SO Geneve, hepia inIT, and collaborations with medical and industrial partners. Education: Not explicitly listed, but implied through roles and projects involving systems engineering and computer science. Research Interests: His work spans embedded systems design, real-time data processing, and applied machine learning. Key focuses include secure hardware-software co-design (e.g., FPGA-based security), medical device development (e.g., neonatal monitoring systems), and IoT infrastructure for smart buildings and recycling. Project Trends: Florent leads projects combining engineering with societal impact, such as automated recycling systems (LusTra), secure medical diagnostics (BrainCheckX), and educational virtualization platforms (Nexus VDI). Recent work emphasizes AI-driven solutions for healthcare (e.g., cochlear implant support) and decentralized energy management. Grants and Funding: Multiple projects funded by HES-SO Rectorat, CTI, and industry partners, totaling over CHF 400,000 since 2014. Labs/Teams: Active in distributed embedded systems research, leading teams on projects like DPESI (distributed storage) and HERVA (random number validation platforms).

• Computer Science
• Data Science
• Artificial Intelligence
• +۳ مورد دیگر

Martin Simon is a Scientific Assistant at HES-SO Valais-Wallis, part of the School of Management and Economy and Services department. He specializes in developing data-driven platforms for real estate pricing prediction, hiking safety, and citizen engagement. His work integrates neural networks, geographic information systems, and collaborative frameworks to address societal challenges in tourism, energy, and healthcare. Key projects include: Frepann: A neural network-based real estate price prediction platform. HikeSafe: A web platform assessing hiking trail difficulty and recommending routes based on user profiles. Citoyenne Valais: A digital tool for citizen participation in public policy. His research spans energy data integration (e.g., REDI project), e-government process optimization (SamProC), and smart grid systems (i-BATs). He collaborates with institutions like the CREM and private firms like PostAuto Schweiz AG. Martin’s technical expertise includes Python, PHP, Docker, and RESTful services. His work emphasizes practical solutions for public administration, environmental sustainability, and safety in outdoor activities.

• Machine Learning
• Data Mining
• Artificial Intelligence
• +۷ مورد دیگر

Prof. Alexandros Kalousis holds the position of Ordinarius HES Professor at the Geneva School of Economics and Management (HES-SO). His primary affiliation is within the Department of Management Information Systems under the School of Economics and Services. His research focuses on machine learning, data mining, and their applications in biomedical systems, cybersecurity, and generative modeling. Key projects include SimGait (SNSF-funded), which develops neuromechanical models for pathological gait analysis using machine learning, and RAWFIE (EU-funded), creating a mixed network testbed for autonomous vehicle experimentation. He has also led projects on time series forecasting, olfactory modeling for perfume creation, and metric/kernel learning optimization. Notable contributions span graph generative models like DGAE and GLAD, cybersecurity implications of LLMs, and reproducible indoor positioning systems. His work integrates theory-driven models with deep learning, emphasizing interpretability and extrapolation capabilities. Research collaborations include EPFL's Biorobotics Lab, Geneva University Hospitals, and industry partners like Firmenich. Total funding exceeds CHF 3M across projects like SimGait (CHF 2.1M) and RAWFIE (CHF 623K).

• Machine Learning
• Smart Buildings
• Energy Efficiency
• +۳ مورد دیگر

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.

Konrad Tiefenbacherمشاهده پروفایل

استادیار

• Climate Science
• Remote Sensing
• Artificial Intelligence
• +۵ مورد دیگر

Konrad Tiefenbacher is a dual tenure-track Assistant Professor at the University of Basel and ETH Zürich, holding positions in the Department of Chemistry (Basel) and the Department of Biosystems Science and Engineering (ETH Zürich). He specializes in applying artificial intelligence and remote sensing to study glaciology, climate science, and environmental systems. His research bridges molecular synthesis (from his PhD in natural product chemistry) with cutting-edge AI-driven Earth observation. Education: Chemical studies at the Technical University of Vienna and University of Texas at Austin, followed by a PhD under Prof. Mulzer (University of Vienna) focusing on total synthesis of bioactive natural products. Postdoctoral research in molecular recognition at The Scripps Research Institute (Prof. Rebek). Became an independent researcher at TU Munich in 2012 before his current dual appointment since 2016. Research interests include deep learning for glacier calving front detection, retrogressive thaw slump mapping, GNSS reflectometry, and self-supervised environmental monitoring. His work integrates multi-sensor data and transformer networks for climate foundation models, with projects like AI-CORE addressing Arctic and Antarctic cryosphere challenges. Publications emphasize AI applications in polar regions, such as calving front dynamics in Greenland/Svalbard, permafrost disturbances, and methane detection. His methods combine semantic segmentation (e.g., PixelDINO) and transformer architectures (DDM-Former) for high-resolution Earth surface analysis. Labs/Teams: Leads the Synthesis of Functional Modules group, collaborating on AI-driven environmental monitoring tools and large-scale datasets like DARTS and IceLines.

• Real Estate Management
• Digital Transformation in Real Estate
• Sustainable Urban Development
• +۳ مورد دیگر

Markus Schmidiger is a Lecturer at the Lucerne School of Business, part of the Lucerne University of Applied Sciences and Arts. He is affiliated with the Institute of Financial Services Zug (IFZ) and the Competence Center Real Estate (CC Real Estate). His academic work focuses on real estate management, digital transformation in construction, and sustainable urban development. Schmidiger also leads the MAS Real Estate Management program and contributes to industry research through projects like the Digitalisierungsbarometer for real estate. Education: PhD in Economics (HSG), Master in NLP (Society of NLP), Corporate Real Estate Manager (ebs) Research Areas: Real estate digitalization, circular economy in construction, machine learning for property valuation Projects: NISMO (Spatial ML for real estate), Digitalisierungsbarometer, sustainable development in Uri canton, smart city initiatives His industry mandates include roles on the boards of Utilita Foundation (non-profit housing investments) and Seraina Investment Foundation's Investment Committee, alongside serving on AST Migros Pension Fund's real estate committee. Schmidiger actively engages in media commentary and professional networking through his Immobilienblog and LinkedIn profile.

Markus Meiererمشاهده پروفایل

استادیار

• Marketing
• Network Science
• Computational Linguistics
• +۷ مورد دیگر

Markus Meierer is an Assistant Professor at the Institute of Management, University of Geneva, and serves as an External Lecturer at the Chair of Marketing for Social Impact, Department of Business Administration, University of Zurich. His interdisciplinary work integrates marketing, network science, and data science to study large-scale consumer networks and behavior. His research focuses on understanding how consumers' social ties influence behavior, using advanced methodological tools such as multilevel modeling to account for contextual effects. His expertise spans machine learning, marketing analytics, and computational linguistics, applied to real-world challenges in telecommunications, insurance, banking, and retail sectors. Markus holds a PhD and has an extensive educational background, including studies at the Kellogg School of Management, University of Zurich, and University of Trier. He is fluent in German, English, and French, and brings both academic rigor and industry experience to his roles. He is actively involved in leveraging data science to build customer-centric organizations, leading research initiatives on social networks and consumer behavior at the University of Zurich. Assistant Professor, Institute of Management, University of Geneva External Lecturer, Chair of Marketing for Social Impact, University of Zurich His professional experience includes roles as a Data Scientist and Research Group Leader at UZH, where he collaborates with major industries to apply data-driven strategies. No scientific awards are listed in the provided text. He advises on data strategy and market development, with a strong focus on translating academic research into practical business applications. His teaching includes Machine Learning at UZH. He leads the research group 'Social Networks & Consumer Behavior' at the University of Zurich, fostering interdisciplinary collaboration between marketing and data science.

Edy Portmannمشاهده پروفایل

استاد

• Fuzzy Logic
• Cognitive Cities
• Computational Intelligence
• +۱۲ مورد دیگر

Edy Portmann is a Professor at the Department of Informatics, University of Fribourg, where he leads the Resilient Systems Group at the Human-IST Institute and chairs the Mobiliar Cluster for Resilience. He holds a doctorate in fuzzy logic and has extensive experience in both academia and industry, having worked at Swisscom, PwC, and EY, and conducted research at the National University of Singapore, UC Berkeley, and the University of Bern. His research interests include Fuzzy Logic , Cognitive Cities , Computational Intelligence , Digital Ethics , and Human-Computer Interaction . He explores how fuzzy systems can enhance knowledge representation, decision-making, and urban governance, particularly in smart and resilient city contexts. His work integrates digital humanities and connectivist learning theories to bridge the social and semantic web. The recent publications (2022–2025) highlight a strong trend toward ethical AI , explainable systems , public participation , and the application of fuzzy logic in conversational agents , decision support , and urban informatics . He frequently publishes on topics such as digital ethics, emotional chatbots, and systemic consensus in group decision-making. HMD Best Paper Award 2018 He advises several PhD and research students and collaborates extensively with researchers such as Sara D’Onofrio, Patrick Kaltenrieder, and Luis Terán. His work often involves interdisciplinary grants and partnerships with public institutions like Swiss Post. He leads a dynamic research team focused on resilient, human-centered computing and cognitive city technologies.

Mathilde Dugenneمشاهده پروفایل

استادیار

• Microbiology
• Plankton Ecology
• Aquatic Ecosystems
• +۷ مورد دیگر

Dr. Mathilde Dugenne is an Assistant Professor at the University of Geneva, affiliated with the Faculty of Science and the Department of Biology. Her research focuses on plankton species and their critical role in regulating Earth's climate and supporting aquatic food webs. She is actively involved in the ALGA project (Efflorescences Algales dans le Léman face aux Changements Globaux), which investigates phytoplankton and cyanobacteria blooms in Lake Geneva. Her work integrates microbiology, imaging technology, and machine learning to monitor and understand plankton diversity and dynamics. Using data from the LéXPLORE platform, she develops AI-based tools for real-time classification of phytoplankton, aiming to support early detection of harmful blooms and inform environmental decision-making for lake stakeholders. Research spans microbial ecology, climate impacts on aquatic systems, and AI-driven environmental monitoring. Focus on practical applications for water quality, public health, and ecosystem management in Lake Geneva. Dr. Dugenne has expertise in plankton taxonomy, imaging instruments for species identification, and mathematical modeling. Her interdisciplinary approach combines field observations with computational methods to address pressing environmental challenges. She has not listed any scientific awards in the provided text. Dr. Dugenne is actively mentoring students and leading research initiatives, though specific advisees are not named. Her project ALGA involves collaboration with environmental scientists and stakeholders to develop decision-support tools. She is involved in securing and managing research grants related to environmental monitoring and climate change impacts, although specific grants are not detailed. Her work is closely tied to the LéXPLORE platform on Lake Geneva, a floating observatory dedicated to long-term ecological research. This platform enables high-frequency monitoring of physical, chemical, and biological parameters, forming the backbone of her team's data collection for plankton dynamics and bloom prediction.

Gregory Giulianiمشاهده پروفایل

مدرس ارشد

• Remote Sensing
• Geographic Information Systems (GIS)
• Spatial Data Infrastructure (SDI)
• +۱۵ مورد دیگر

Gregory Giuliani is a Senior Lecturer at the Institute of Environmental Sciences, Faculty of Sciences, University of Geneva. He also serves as Head of the Digital Earth Unit at GRID-Geneva and is actively involved in numerous international research initiatives including GEO, EARSeL, and the International Society for Digital Earth. PhD in Environmental Sciences, University of Geneva (2009–2011) Master in Natural Sciences of the Environment, University of Geneva (1998–2001) Bachelor in Earth Sciences, University of Geneva (1995–1998) His research is centered on Land Change Science, particularly land degradation, and the application of Earth Observations for environmental monitoring and sustainable development. He is a key figure in advancing Spatial Data Infrastructures, Digital Earth, and Earth Observation Data Cubes. His work emphasizes interdisciplinary approaches, open and reproducible science, and the integration of Essential Variables for environmental sustainability. The most recent publications highlight his leadership in the Swiss Data Cube initiative, digital twins for environmental modeling, and the use of machine learning for land cover mapping. His work bridges satellite data, geospatial analytics, and policy support for the Sustainable Development Goals, particularly SDG 15 (Life on Land) and SDG 11 (Sustainable Cities). Associate Editor, Big Earth Data (since 2020) Associate Editor, Frontiers in Environmental Science (since 2022) Editorial Board Member, International Journal of Digital Earth (since 2022) Editorial Board Member, Remote Sensing (since 2019) Guest Editor, special issues on Sentinel ARD, Earth Observation Data Cubes, and Essential Variables Dr. Giuliani supervises numerous PhD and Master’s students and leads major research projects such as SNF DT4LC, Horizon Europe LandShift, Monalisa, and Nostradamus. He has coordinated national and international efforts in geospatial capacity building and data interoperability. He is also involved in citizen science and open-source GIS initiatives, contributing to education and training at multiple levels. He leads the Digital Earth Unit at GRID-Geneva and is a driving force behind the Swiss Data Cube and Living Switzerland digital twin projects, aiming to create integrated, data-driven systems for environmental monitoring and policy support.

Martin Elingمشاهده پروفایل

استاد

• Insurance Economics
• Digitalization
• Artificial Intelligence
• +۸ مورد دیگر

Martin Eling is a Full Professor of Insurance Economics and Director at the Institute of Insurance Economics (IVW-HSG) at the University of St.Gallen, a position held since November 2011. His academic career includes professorships at the University of Ulm (2009-2011) and visiting roles at the University of Wisconsin-Madison (2008) and Italian universities (2010-2011). Education: Dr. rer. pol. (2005), University of Münster Habilitation (2009), University of St.Gallen Research Interests: Eling specializes in empirical research at the intersection of insurance management, mathematics, and economics, with a focus on digitalization (AI, Big Data, Cyber Risk), Microinsurance, Social Security (pensions, healthcare), Asset Management, and Regulatory frameworks. His work explores risk measurement, market discipline, and technological impacts on insurance. Publications: His 15 most recent articles address cyber risk modeling, AI implications, sustainability in insurance, and risk measurement. These span journals like North American Actuarial Journal , Risk Sciences , and Geneva Papers , emphasizing interdisciplinary approaches. Awards: Spencer L. Kimball Award (2010) Shin Research Excellence Award (2014) Top Cited Article (Geneva Papers, 2023) Dean's Wildcard for innovative teaching (2023) Bob Alting von Geusau Prize (2024) Grants: Funded by Swiss National Science Foundation (SNSF) for projects on cyber risk, microinsurance, and regulatory constraints. Collaborative grants with German Research Foundation (DFG) and industry partnerships. Professional Engagement: Active as an invited speaker at global institutions (MIT, NTU Singapore, Sorbonne) and in editorial/referee roles for 30+ journals, including Journal of Risk and Insurance and European Journal of Operational Research .