جست‌وجوی استاد و پژوهشگر

Mirela Beloiu Schwenkeمشاهده پروفایل

مدرس

• Forest Ecology
• Remote Sensing
• Climate Change
• +۴ مورد دیگر

Dr. Mirela Beloiu Schwenke is a Lecturer at ETH Zurich's Department of Environmental Systems Science, specializing in forest ecology, remote sensing, and climate change impacts. Her research focuses on understanding forest resilience to climate-driven disturbances like droughts and developing advanced monitoring techniques using remote sensing and machine learning. She contributes to projects such as the SNSF COST Action for tree species identification and the UPSCALE initiative for forest vitality monitoring. Education & Research Interests PhD in Environmental Sciences (implied from professional context) Focus areas: Tree mortality dynamics, drought tolerance mechanisms, and integrating ground-based and remote sensing data Key Projects Leading development of deep learning models for tree species identification in mixed forests Contributing to global forest monitoring frameworks through Sentinel satellite integration Investigating drought impacts on sapling recovery and forest succession patterns Awards & Recognition Recipient of the 2023 Young Scientist Award for her presentation on tree mortality mechanisms at the EARSel Symposium. Teaching Teaches courses on forest ecosystems and practical field methodologies for environmental science students. Grants & Collaborations Swiss National Science Foundation (SNSF) funded projects International collaborations with institutions like the Africa CDC and ICOS Switzerland Labs & Teams Part of ETH Zurich's forest ecology and remote sensing research groups, actively contributing to open-access databases like 'deadtrees.earth'.

• Environmental Systems Science
• Ecosystem Ecology
• Flood Modeling
• +۳ مورد دیگر

Dr. Priyanka Chaudhary is a Researcher affiliated with the Professorship for Global Ecosystem Ecology at ETH Zurich's Department of Environmental Systems Science . Her work focuses on integrating computational methods with environmental science, particularly in flood modeling and disaster risk assessment. She contributes to advancing methodologies for water resource management and urban resilience through deep learning and social media data analytics. Her research interests span ecosystem ecology , flood prediction systems , and environmental monitoring technologies . Notably, she develops innovative approaches using convolutional neural networks and ensemble methods to estimate flood depths and uncertainties. Recent work leverages social media imagery for real-time flood level estimation, enhancing crisis response capabilities. Dr. Chaudhary's publications reflect a strong emphasis on interdisciplinary solutions to environmental challenges, combining hydrology, computer science, and geospatial analysis. Her contributions highlight the potential of data-driven methods in addressing global environmental issues such as climate change impacts and urban flood risk mitigation.

Afef Marzouguiمشاهده پروفایل

پژوهشگر

• Crop Science
• Remote Sensing
• Plant Disease Resistance
• +۳ مورد دیگر

Dr. Afef Marzougui is a Researcher at ETH Zürich in the Department of Crop Sciences. Her work focuses on integrating remote sensing technologies and machine learning to advance crop phenotyping and disease resistance studies. She specializes in developing precision agriculture strategies for pest management and crop yield optimization. Her research interests include crop science, plant disease resistance mechanisms, and the application of high-resolution satellite and proximal sensing techniques in agricultural phenomics. Notably, she has contributed to projects like the Global Wheat Full Semantic Organ Segmentation (GWFSS) Dataset and studies on Aphanomyces root rot resistance in legumes. Her recent publications (2020–2025) emphasize interdisciplinary approaches combining computational methods with field data to address challenges in sustainable crop production. Key themes include disease impact modeling in livestock, multi-scale data fusion for yield estimation, and VOC-based biomarker identification for high-throughput disease detection.

Mikko Tiusanenمشاهده پروفایل

پژوهشگر

• Plant Ecology
• Phenology
• Ecological Interactions
• +۳ مورد دیگر

Dr. Mikko Tiusanen is a Researcher at ETH Zürich's Department of Plant Ecology, focusing on plant communities and ecosystem responses to global changes. His work integrates ecological field studies with advanced data technologies, such as computer vision algorithms for tracking alpine meadow phenology via deployed cameras. He investigates how environmental conditions shape species distributions and interactions, particularly in Arctic and alpine regions. Current research explores phenological shifts, plant-fungal symbiosis dynamics, and pollination network stability under climatic changes. Research interests include understanding environmental drivers of species performance, phenological timing effects on interspecific interactions, and predictive modeling of community changes based on traits and distributions. Methodological innovations include high-resolution ecological data acquisition through automated imaging and DNA metabarcoding for foraging analysis. Recent articles highlight work on plant-pollinator disruption, Arctic microbial networks, and agroecological disease management. While no scientific awards are listed, his contributions to ecological methodology and Arctic-Alpine systems are notable. No advising or grant details are provided here, though his projects likely involve interdisciplinary collaborations within ETH Zürich's ecological research groups.

• Neuroscience
• Visual Perception
• Cognitive Processes
• +۴ مورد دیگر

Michael Schmid is a Professor in the Medicine Section at the Faculty of Science and Medicine, University of Fribourg. His research lies at the intersection of neuroscience, neurology, and cognitive science, focusing on the neural mechanisms underlying vision and their disruption in neurological conditions such as developmental dyslexia. His career includes leadership roles at Newcastle University (2019–2015 as Senior Lecturer), the Ernst Strüngmann Institute (2012–2015 as Emmy Noether group leader), and postdoctoral training at the National Institutes of Health (2007–2010). He earned his PhD in Neuroscience from the Max Planck Institute for Biological Cybernetics and the University of Tübingen (2007). His research explores visual perception in neurological diseases, utilizing techniques such as optogenetics, neuroimaging, and behavioral studies in non-human primates. Recent work examines cortical reorganization, rhythmic neural activity, and sensory processing in macaques, with translational relevance for human vision disorders. Key publications highlight advancements in understanding blindsight, visual network dynamics, and the role of the lateral geniculate nucleus in perceptual suppression. His lab (http://www.optovisionlab.org) investigates how cognitive processes influence visual perception and develops interventions for reading difficulties.

• Accessibility in Computing
• Human-Computer Interaction
• Robotics
• +۳ مورد دیگر

Yong-Joon Thoo is a Researcher at the Department of Informatics , University of Fribourg. His role is supported as a Diploma Assistant funded through third-party grants. His research focuses on accessibility in computing, human-computer interaction, and robotics, with a strong emphasis on blind/low-vision accessibility and augmented reality applications. He has contributed to large-scale analyses of accessibility research trends and innovations in assistive technologies. Education and Background: While specific academic qualifications are not detailed, his current position implies a strong foundation in informatics and research methodologies. His work bridges academic research with practical applications in technology and accessibility. Research Interests: Yong-Joon’s work revolves around enhancing digital accessibility for visually impaired users, leveraging computational methods to analyze research patterns in ACM and IEEE publications. He also explores augmented reality (AR) for robot programming, aiming to improve human-robot collaboration in industrial settings. His interdisciplinary approach combines quantitative analysis with user-centered design principles. Recent Trends in Publications: His recent articles highlight a dual focus: (1) analyzing accessibility research ecosystems and their societal impacts, and (2) advancing AR-based solutions for robotics. These efforts reflect a commitment to both theoretical insights and real-world technological solutions. Grants and Funding: His position is supported by third-party funding, indicating active engagement in externally sponsored research projects. No specific grants or student advisement are listed.

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Donnacha Daly is a Professor of Artificial Intelligence at Lucerne University of Applied Sciences and Arts, leading the Bachelor's Program in Artificial Intelligence & Machine Learning. He co-founded The Applied AI Center and industry ventures like Gopf AG and LAC2 AI-Hub Luzern. His research focuses on AI applications in healthcare, natural language processing, and machine learning. Notable projects include 'Skin-App: Medical Severity Grading of Hand Eczema by Automated Image Analysis' and 'FoodTaxo: Generating Food Taxonomies with Large Language Models.' Publications highlight advancements in diagnosis prediction using EHR data and generative models for food taxonomy creation. He received the ABIZ Team Achievement award for pioneering an AI-generated beer recipe. Advisory roles include program leadership and industry collaborations through his co-founded entities. His work bridges academic research with practical industry applications in AI and data science.

• Machine Learning
• Deep Learning
• Time Series Analysis
• +۳ مورد دیگر

Fabian Gröger is a Research Associate, Doctoral Student, and Lecturer at Lucerne University of Applied Sciences and Arts (HSLU), affiliated with the Lucerne School of Computer Science and Information Technology. He is a Scientific Collaborator at the Algorithmic Business (ABIZ) Research Lab and teaches in the CAS Machine Learning program. His roles include Data Scientist, Research Assistant, and Teaching Assistant in machine learning and artificial intelligence programs. Education: Ongoing PhD in Biomedical Engineering, University of Basel Master of Science in Data Science/ML, HSLU Bachelor of Science in Computer Science, HSLU His research focuses on Machine Learning , Deep Learning , Audio Data , and Self-Supervised Learning , with applications in digital dermatology, bioaerosol monitoring, and medical anomaly detection. His work emphasizes scalable foundation models, data quality audits, and reducing annotation needs in healthcare AI. Recent publications highlight contributions to hyperbolic space applications in medical AI, audio representation learning for hearables, and benchmarking strategies like CleanPatrick. His work spans conferences like MICCAI, NeurIPS, and ECCV. Awards: Outstanding Reviewer (JEADV, 2024) Best Lightning Talk (AI Medicine Symposium, 2024) Best Paper (MICCAI 2023) Best Master Thesis (HSLU, 2023) Gröger leads projects such as SelfClean for Audio and AI for All , and collaborates with industries like Prepress Media AG. He advises on algorithms for small-hotel revenue management and exhibits at events like the Museum Exposition on Food & AI. His lab affiliations include the ABIZ Research Lab and the Digital Dermatology group, where he explores ethical AI, clinical decision support systems, and data-centric healthcare solutions.

Aygul Zagidullinaمشاهده پروفایل

مدرس ارشد

• Data Science
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Aygul Zagidullina is a Senior Lecturer and Researcher at the Lucerne University of Applied Sciences and Arts, specifically affiliated with the Lucerne School of Computer Science and Information Technology. She serves as Head of Applied Data Intelligence in Continuing and Executive Education, contributes to teaching and research in Data Science, Machine Learning, and Artificial Intelligence, and co-organizes academic initiatives like Women in AI and the Women in Data Science (WiDS) conference in Zürich. Ph.D. in Quantitative Methods (specialization: High-Dimensional Covariance Matrix Estimation) Diploma in Applied Mathematics (B.Sc. + M.Sc.) Postgraduate Machine Intelligence Program in Computer Science Certificate in Didactics for Higher Education Her research focuses on data-driven solutions at the intersection of Statistics, Computer Science, and Finance, with applications in portfolio optimization, NLP bias mitigation, and image quality assessment. She emphasizes the societal impact of AI and its integration into industry workflows. Recent projects include hydropower digital twins, AI for procurement documentation, and LLM training via user feedback. She authored a Springer textbook on High-Dimensional Covariance Matrix Estimation in 2021 and has co-authored peer-reviewed articles in the Journal of Financial Econometrics (2021, 2024). Her work spans theoretical rigor and practical implementation across finance, energy, and healthcare domains. Aygul contributes to academic leadership through roles such as Module Responsible in AI Competition (Kaggle Challenge), Co-Head of the CAS Machine Learning and Data Science for Medicine and Health programs, and Thesis Supervisor in AI & ML. She collaborates with industry partners (e.g., Paretolabs, Konplan) and leads research at the AI Robotics Research Lab.

• Sensors and Networks
• Industrial Automation
• Medical Devices
• +۳ مورد دیگر

Daniel Klauser is a Senior Research Associate and Doctoral Student at the Lucerne School of Engineering and Architecture (Lucerne University of Applied Sciences and Arts). He is affiliated with the Institute of Electrical Engineering IET CC Intelligent Sensors and Networks. His research focuses on sensor technology, industrial automation, and medical device development, with projects such as the iLux dermatological examination device and vision-based granular material counting systems. Education details: Currently pursuing a doctoral degree while engaged in advanced research roles. Research interests include embedded systems, 3D TOF sensor integration, and object recognition in industrial contexts. He contributes to projects like miniaturized 3D TOF sensors for automation. No scientific awards or grants explicitly listed in available texts. His work is centered in the Intelligent Sensors and Networks group, addressing practical applications of electrical engineering and sensor technologies.

• 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)

• AI-based Applications
• Computer Vision
• Environmental and Energy Domain
• +۴ مورد دیگر

Prof. Martin Melchior is a Professor at FHNW University of Applied Sciences, serving as Deputy Head of the Institute for Data Science. His primary roles include lecturing in Data Science and Computer Science, supervising thesis projects, and leading research in AI applications for computer vision, environmental energy systems, and astro-informatics. He holds a PhD in Physics from ETH Zurich and has extensive experience in risk modeling and space instrumentation projects. Education highlights include a PhD in theoretical polymer science (1993-1996) and studies in physics/mathematics at ETH Zurich (1986-1992). His research focuses on machine learning in astrophysics, cosmological surveys like Euclid, and large-scale data management for space missions. Key projects include contributions to the Euclid mission's ground segment and SwissPRODEX-funded operations. Recent research interests emphasize gravitational lensing analysis, galaxy clustering, and cosmological parameter estimation via Euclid data. He has led/co-led numerous applied science projects in energy optimization, medical diagnostics, and environmental monitoring technologies. His work bridges academia and industry through collaborations with institutions like EPFL, University of Geneva, and companies such as AINEAS GmbH and Swisens AG.

Lena A. Jägerمشاهده پروفایل

دانشیار

• Computational Linguistics
• Eye Tracking
• Machine Learning
• +۵ مورد دیگر

Lena A. Jäger is an Associate Professor in Digital Linguistics at the School for Transdisciplinary Studies, University of Potsdam. Her research focuses on computational linguistics, eye tracking, and machine learning applications in language processing. She leads the Digital Linguistics group, supervising 11 PhD students and contributing to interdisciplinary projects like the MultiplEYE corpus initiative. Her work bridges cognitive science and AI, with key contributions to eye movement analysis, biometric identification, and LLM interpretability. Her research interests span eye tracking in reading, linguistic predictability modeling, and the alignment of language models with human cognition. Notable achievements include developing the pymovements toolkit for eye movement data processing and pioneering studies on detecting alcohol inebriation via gaze analysis. Awards include best paper honors at ETRA 2023 and 2024. Recent work explores generative models (ScanDL) for synthetic eye movement generation, cross-lingual reading behavior analysis, and fairness in biometric systems. She advises on AI ethics through the DSI initiative and collaborates internationally on projects like the MECO corpus.

Corinna Reinhardtمشاهده پروفایل

استاد

• Greek and Roman Archaeology
• Digital Methods in Archaeology
• Materiality of Writing and Images
• +۴ مورد دیگر

Corinna Reinhardt is a Professor of Mediterranean Archaeology with a focus on Greek and Roman Antiquity at the University of Zurich since 2023. She holds a Magister degree from Ludwig Maximilian University of Munich and a PhD from the same institution, with a doctoral scholarship from the Gerda Henkel Foundation. Her research interests include classical sculpture, digital methods in archaeology, materiality of text and image, and reception history of antiquity. She has led interdisciplinary projects like 'Iconographics' and co-founded the Digital Visualisation Lab at UZH. She was awarded the 2021 Teaching Award at FAU Erlangen-Nuremberg and has published extensively on topics like acroter architecture, inscriptions, and computer vision applications in cultural heritage. Her work bridges traditional archaeology with digital innovation, emphasizing both material analysis and computational methods. Education: Magister (LMU Munich, 2010), PhD (LMU Munich, 2015) Affiliations: Institute of Archaeology, Digital Visualisation Lab (UZH) Her research focuses on the intersection of classical sculpture with architecture, digital methodologies for analyzing artifacts, and the material culture of ancient writing systems. Recent projects include 3D scanning of Hellenistic Nike statuettes and digital exhibitions like 'Kreuz und quer – Lebensgeschichten antiker Objekte'. She has supervised numerous academic courses and taught advanced digital methods in archaeological studies. Publications highlight interdisciplinary approaches, with key works on Greek acroter design, material text culture, and AI-driven analysis of vase paintings. Awards include the 2021 FAU Teaching Prize and recognition for her doctoral thesis.

Jeffrey Huangمشاهده پروفایل

استاد

• Design Thinking
• Artificial Intelligence in Architecture
• Strategic and Experience Design
• +۳ مورد دیگر

Jeffrey Huang is a Full Professor at EPFL, holding joint appointments in the Faculty of Computer and Communication Sciences (IC) and the Faculty of Architecture, Civil and Environmental Engineering (ENAC). He directs the Institute of Architecture and leads the Media x Design Laboratory (MxD Lab). His areas of expertise include Design Thinking, Artificial Intelligence in Architecture, Urban Digital Twins, and Computational Urbanism. Educated at ETH Zurich (DiplArch), Harvard University (Masters and PhD), Huang has held academic roles at MIT, Harvard, Tsinghua University, and the Singapore University of Technology and Design (SUTD). He is a recipient of the Gerald McCue Medal for academic excellence and the 2023 ACSA Best Article Award for his work on GANs and architectural design. Recent research focuses on combining machine learning with architectural design, particularly exploring generative adversarial networks (GANs), spatial analysis, and urban digital twins. His projects include the Blue City Innosuisse Flagship Project and the Singapore Prototypologies initiative. Awards include the 2023 ACSA Best Article Award and the Best Presentation Award at CAAD Futures 2009. He supervises numerous PhD students and has led significant research grants such as the Innosuisse Flagship Project and the MIT-SUTD collaborations. Huang co-founded Convergeo, a strategic design firm, and has been involved in creating new architectural education programs, including the Architecture and Sustainable Design Pillar at SUTD.