جست‌وجوی استاد و پژوهشگر

Romain Quidantمشاهده پروفایل

استاد

• Nanophotonics
• Optomechanics
• Plasmonics
• +۴ مورد دیگر

Prof. Dr. Romain Quidant is a Full Professor in the Department of Mechanical and Process Engineering at ETH Zürich, where he also serves as Head of the Institute for Energy and Process Engineering. His research focuses on nanophotonics, optomechanics, and plasmonics with applications in quantum optics, biomedical engineering, and thermal control systems. He leads a multidisciplinary team exploring light-matter interactions at the nanoscale, particularly in levitated nanoparticles and plasmonic therapies. Key research interests include quantum optomechanical systems, plasmonic nanothermometry, and targeted photothermal therapies. His work bridges fundamental physics with practical applications such as precision measurement, medical imaging, and energy-efficient materials. Recent studies highlight advancements in optical trapping techniques, thermal wavefront shaping, and robotic surgery guidance using fluorescent nanothermometry. Prof. Quidant’s publications showcase innovations in reconfigurable meta-surfaces, optofluidic platforms for high-throughput analysis, and adaptive thermal microscopy for brain imaging. His lab develops integrated systems for medical diagnostics, environmental sensing, and quantum-enabled technologies. These efforts have been applied to cancer treatment optimization and novel materials for energy systems.

Xuming Heمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۹ مورد دیگر

Xuming He is an Associate Professor at the School of Information Science and Technology (SIST), ShanghaiTech University, where he leads the PLUS Lab. His research spans computer vision and machine learning with a focus on developing algorithms that operate effectively under limited supervision and evolving data conditions. His core research interests include weakly-supervised and few-shot learning for scenarios with sparse annotations, continual learning frameworks for knowledge retention during sequential task acquisition, semantic segmentation techniques for scene understanding, and multimodal vision-language representations. He emphasizes interpretable machine learning to build transparent AI systems capable of human-understandable reasoning, addressing critical challenges in model trustworthiness and deployment reliability. Recent publications reveal strong trends toward novel class discovery in long-tailed recognition scenarios, physics-informed generative modeling for scientific applications, and robust segmentation under distribution shifts. His work increasingly integrates large language models for multimodal reasoning while maintaining focus on efficiency in resource-constrained environments like robotic grasping and medical imaging analysis. He actively mentors students, having supervised Qian He to PhD completion and Chuanyang Hu to Master's degree in 2023. He welcomes prospective graduate students through ShanghaiTech's Computer Science & Technology program and offers undergraduate research projects requiring minimum six-month commitments. The PLUS Lab under his direction drives innovation in learning under supervision constraints, with recent work spanning medical tumor analysis, cross-view geolocation, photonic computing, and semiconductor design verification. The lab's research bridges theoretical advances with practical applications across healthcare, robotics, and scientific discovery domains.

David Atienzaمشاهده پروفایل

استاد

• Embedded Systems
• Low-Power Computing
• Edge AI
• +۳ مورد دیگر

David Atienza is a Professor in the Department of Electrical Engineering at the School of Engineering, Swiss Federal Institute of Technology in Lausanne (EPFL), renowned for pioneering embedded systems education and research in ultra-low power computing. His innovative teaching methods, including using Nintendo DS consoles and smartphones to teach embedded systems, earned him the 2015 EPFL Teaching Award in Electrical Engineering. His research focuses on Embedded Systems , Edge AI , and Wearable Healthcare , with breakthroughs in energy-efficient hardware-software co-design for biomedical applications. Key contributions include open-source platforms like X-HEEP and HEEPocrates for ultra-low power edge computing, and frameworks like SzCORE for seizure detection benchmarking. His work bridges computer architecture with real-world healthcare challenges, emphasizing privacy-preserving algorithms and sustainable computing. Recent publications (2023-2025) reveal a dominant trend toward biomedical edge AI and sustainable computing , with 70% of articles targeting healthcare wearables (seizure detection, cough monitoring) and 30% addressing energy efficiency in data centers and edge devices. His research consistently integrates open-hardware principles (RISC-V) with novel algorithm-hardware co-design. Awards include: 2015 EPFL Teaching Award in Electrical Engineering section While specific advising details are unreported, his extensive publication record and leadership in multi-partner projects like Sustainable Textile Electronics (STELEC) indicate active graduate supervision and significant research funding. His group develops open-source hardware frameworks used globally in academia and industry. He leads the Embedded Systems Laboratory at EPFL, driving projects in ultra-low power RISC-V architectures, biomedical wearables, and sustainable computing. Current initiatives include carbon-aware data center frameworks and multi-modal health monitoring systems deployable on commercial wearables.

• Biotechnology
• Bioplastics
• Biocompatibility
• +۳ مورد دیگر

Manfred Zinn serves as a Professor at the University of Applied Sciences and Arts Western Switzerland (HES-SO), specifically within the School of Chemistry and Life Sciences. He leads the Biotechnology and Sustainable Chemistry research group at the Life Science Engineering department in Sion, Switzerland. His academic position includes significant research leadership responsibilities and active contributions to the field of bioplastics and sustainable materials. Professor Zinn's research focuses primarily on biotechnology applications for sustainable materials, with particular expertise in polyhydroxyalkanoates (PHAs) and other bioplastics. His work spans microbial biosynthesis, material characterization, and industrial applications of biodegradable polymers. He investigates the metabolic pathways of PHA-producing microorganisms, develops novel analytical methods for biopolymer characterization, and explores practical applications of bioplastics in medical and industrial contexts. His research integrates microbiology, polymer chemistry, and process engineering to address challenges in sustainable materials development. Analysis of his recent publications (2019-2024) reveals a strong focus on advancing the science and technology of bioplastics, particularly polyhydroxyalkanoates. His work addresses key challenges in monomer composition control, polymer characterization, biosynthesis optimization, and industrial applications. A significant trend in his research involves developing sophisticated analytical methods for biopolymer production monitoring and exploring novel applications for biodegradable materials in medical and industrial contexts. His collaborative work spans multiple countries and institutions, reflecting the international nature of bioplastics research. Professor Zinn has secured significant research funding through multiple competitive grants, including Innosuisse and Swiss National Science Foundation projects. His research portfolio includes projects on biosynthesis of Chlorella, electroplating processes for biodegradable materials, and online flow cytometry analysis for microbial bioplastic production. These projects demonstrate his ability to secure funding for interdisciplinary research at the intersection of biotechnology, materials science, and sustainable chemistry. His collaborations extend to institutions including the Frauenhofer Institute and Chulalongkorn University in Bangkok. The Biotechnology and Sustainable Chemistry research group led by Professor Zinn maintains strong laboratory facilities for microbial cultivation, biopolymer synthesis and characterization. The group utilizes advanced equipment including bioreactors, flow cytometry systems, and polymer analysis instrumentation. Their research bridges fundamental science with practical applications, focusing on developing sustainable alternatives to conventional plastics while addressing technical challenges in production, characterization, and implementation.

• Soft Robotics
• Musculoskeletal Robotics
• Biohybrid Robotics
• +۵ مورد دیگر

Robert Katzschmann is an Assistant Professor of Robotics (tenure-track) at ETH Zurich's Department of Mechanical and Process Engineering , leading the Soft Robotics Laboratory . He is also the co-founder and scientific advisor of Mimic Robotics , focused on dexterous manipulation solutions. His research spans Soft Robotics , Musculoskeletal Robotics , Biohybrid Systems , and Underwater Robotics , with breakthroughs like the autonomous soft robotic fish SoFi and biohybrid actuators. He holds a PhD from MIT (2018), a Master's from Stanford (2013), and a Diplom-Ingenieur from KIT (2013). Research Interests: His work emphasizes compliant, bioinspired robots capable of safe human interaction and complex environmental navigation. Key areas include soft material fabrication, biohybrid tissue integration, and dynamic control algorithms. Recent innovations include electrohydraulic actuators and vision-controlled printing for robotic components. Grants & Recognition: Secured funding from SNSF, NSF, and industry partners. Recognitions include a TED Fellowship (2022), Outstanding Paper Award (IEEE RoboSoft 2019), and Redtenbacher-Prize (2014). He serves on editorial boards for Advanced Robotics Research and npj Robotics , and chairs conference workshops globally. Labs & Teams: Directs the Soft Robotics Lab with 17 PhD students and 2 postdocs. Collaborates with leading institutions like MIT, Harvard, and the Weizmann Institute on biohybrid systems and robotic actuation.

Urs Hilberمشاهده پروفایل

استاد

• Plant Pathology
• Fungicide Resistance
• Sustainable Development
• +۶ مورد دیگر

Prof. Dr. Urs Hilber is the Dean of the School of Life Sciences and Facility Management at ZHAW Zurich University of Applied Sciences. He has held leadership roles such as Head of the ZHAW Sustainable Development Focus and Director of multiple Swiss agricultural research institutions. Current affiliations include Au-Konsortium, Eidgenossenschaft, Fructus, grow Cluster, and ZKSD (President of Board of Directors) Education: PhD and MSc in Biology from University of Basel His research focuses on plant pathology , particularly fungicide resistance mechanisms in pathogens like Botryotinia fuckeliana (gray mold) and Venturia inaequalis (apple scab). He pioneered biolistic transformation techniques for fungal genetic studies and developed resistance monitoring strategies for anilinopyrimidines, phenylpyrroles, and dicarboximides. The 15 most recent publications highlight his work on: Fungal taxonomy (Pseudomonas species) PCR-based resistance diagnostics Integrated disease management Genetic variability in plant pathogens

Christina Haagمشاهده پروفایل

پژوهشگر

• Mental Health
• Natural Language Processing
• Activity Sensing Data
• +۳ مورد دیگر

Dr. Christina Haag is a postdoctoral researcher at the Institute for Implementation Science in Health Care , affiliated with the Faculty of Medicine at the University of Zurich . She leads interdisciplinary projects at the intersection of mental health, digital health, and computational linguistics, focusing on chronic illnesses like multiple sclerosis (MS). Her work leverages free text, sensor data, and advanced analysis techniques such as hierarchical modeling and natural language processing (NLP). Doctorate from the Institute of Psychology, University of Zurich Research experience at the MRC Cognition & Brain Sciences Unit, University of Cambridge Her research explores: Daily-life mental and physical health indicators in MS Development of NLP methods for text classification and topic modeling Digital biomarker creation using wearable sensor data Mindfulness interventions for affective executive control Implementation of remote monitoring tools in healthcare Her recent publications highlight trends in applying NLP and machine learning to unstructured health data, analyzing MS activity patterns, and refining interdisciplinary research methodologies. She contributes to DSI communities including AI & Law , Health , and Ethics , and collaborates on projects like BarKA-MS and DSI-Approach . She is a core member of the UZH Digital & Mobile Health Group , working under Prof. Viktor von Wyl.

Günter Hochمشاهده پروفایل

مدرس ارشد

• Tree ecophysiology
• Carbon allocation in trees
• Drought stress physiology
• +۳ مورد دیگر

PD Dr. Günter Hoch is a Senior Lecturer in the Department of Environmental Sciences – Botany at the University of Basel , Switzerland. His research centers on the ecophysiology of trees , with a particular emphasis on carbon storage dynamics , drought stress responses , and the resilience of forest ecosystems to climate change. Research Focus: Carbon allocation and storage in trees under carbon limitation Physiological controls of non-structural carbohydrate reserves (e.g., starch, lipids) Drought-induced tree mortality and recovery mechanisms Whole-tree carbon balance and growth under environmental stress Scaling from individual tree responses to ecosystem-level processes Approach: His team integrates field observations , experimental manipulations , and biophysical modeling to understand how trees regulate carbon reserves and water relations under stress. A key goal is to identify biomarkers (e.g., starch concentrations in sapwood) that reflect the carbon status and health of trees. Recent Work: His publications span high-impact journals like Nature Reviews Earth & Environment , New Phytologist , and Global Change Biology , addressing topics such as hydraulic failure, carbon starvation, and the impacts of extreme droughts (e.g., 2018 Central European drought) on forest ecosystems. Collaborations: He contributes to large-scale networks like TreeNet , a Swiss initiative monitoring drought and growth indicators in forests, and collaborates internationally on projects linking plant ecophysiology to biogeochemical cycles. Contact: guenter.hoch@unibas.ch | Tel: +41 (0)61 207 35 14

• Management Accounting
• Controlling
• Financial Planning
• +۴ مورد دیگر

Viviane Trachsel is a Lecturer at the Lucerne School of Business (HSLU W) within the Institute of Financial Services Zug (IFZ), specializing in Controlling and Accounting. She holds a Master of Arts in Business and Economics from the University of Zurich (UZH) and has completed certifications in university didactics. Her professional roles include leading the Major in Accounting, Finance & Banking for the BSc in International Business Administration since 2018, and heading the Controlling & Accounting Major in the BSc in Business Administration since 2008. Education: Master of Arts in Business/Economics (UZH, 1998), Teaching Diploma (UZH, 2000) Key Roles: Director of Studies, Project Manager, and Academic Leader Her research focuses on management accounting , decentralized controlling systems , and cyber risk governance . Notable projects include the CODEZ study on decentralized organizational control, ESG Monitor , and investigations into Cyber Risk Management in Swiss enterprises. She advocates innovative educational tools like the Controlling-Wiki for blended learning. Trachsel has authored/co-authored over 20 publications, including peer-reviewed articles in Controlling & Management Review and ZfKE . She actively contributes to academic conferences (e.g., CARF Luzern) and editorial roles in financial management education.

Alexander Dammمشاهده پروفایل

استاد

• Remote Sensing
• Earth Observation
• Imaging Spectroscopy
• +۷ مورد دیگر

Alexander Damm is a Professor and head of the Remote Sensing of Water Systems (RSWS) group, holding a joint appointment between the Department of Geography at the University of Zurich (UZH) and the Swiss Federal Institute of Aquatic Science and Technology (Eawag). His research integrates advanced Earth observation technologies with environmental science to study water systems under changing climatic and anthropogenic pressures. University: University of Zurich Institutional Affiliation: Swiss Federal Institute of Aquatic Science and Technology (Eawag) Department: Department of Geography Alexander Damm obtained his MSc and PhD in remote sensing from Humboldt-University Berlin. Since 2008, he has been contributing to UZH’s leadership in imaging spectroscopy and Earth observation science. MSc, Remote Sensing, Humboldt-University Berlin PhD, Remote Sensing, Humboldt-University Berlin His research focuses on the fundamentals of remote sensing as applied to terrestrial and aquatic ecosystems, particularly in studying water dynamics and environmental change impacts. He specializes in sun-induced chlorophyll fluorescence (SIF), imaging spectroscopy, and the development of methods to monitor ecosystem productivity, drought responses, and biogeochemical cycles. His work bridges physics, ecology, and environmental engineering to improve understanding of plant-water relations and ecosystem resilience. The recent publications highlight a strong trend in using airborne and satellite-based spectroscopy to assess vegetation health, water stress, forest dynamics, and atmospheric constituents. Key themes include SIF retrieval, drought monitoring, canopy structure modeling, and air quality estimation. These works span applications from croplands and forests to tundra and inland waters, reflecting a broad interdisciplinary approach grounded in quantitative remote sensing. Alexander Damm is involved in several high-profile research initiatives, including: ESA’s FLuorescence EXplorer (FLEX) mission SNSF projects: FLUO4ECO, Spatial-sustainable-finance, DeltAs MeteoSwiss: UrbanNature EU Horizon: NextGenCarbon He leads the RSWS group, which develops and applies cutting-edge remote sensing methodologies for water system monitoring. The team collaborates across disciplines and institutions, focusing on integrating field measurements, airborne campaigns, and satellite data for environmental assessment. Damm’s leadership in projects like FLEX and HyPlant underscores his role in advancing spectroscopic remote sensing for global ecosystem monitoring.

Thilo Stadelmannمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Representation Learning
• +۳ مورد دیگر

Thilo Stadelmann is the Founding Director of the Centre for Artificial Intelligence at the Zurich University of Applied Sciences (ZHAW) . A computer scientist by training, he earned his Doctor of Science degree from Marburg University, Germany, and has held engineering and leadership roles in the automotive industry before transitioning to academia. His research interests lie at the intersection of representation learning and the societal implications of artificial intelligence . He is particularly focused on understanding how AI systems can be designed to enhance human capabilities while addressing ethical concerns and societal challenges. Stadelmann is a prolific speaker and educator, delivering TEDx talks and lectures on topics such as "How Not to Fear AI" , "AI vs Human: Understanding the Fundamental Differences" , and "Decoding AI Fear: The Philosophy Behind It" . His work emphasizes the importance of demystifying AI and fostering a balanced perspective on its potential and limitations. His recent publications span a wide range of AI applications, from safety-critical network infrastructures and medical imaging to industrial process control and AI governance . Notable works include studies on AI risk assessment for public policy, document recognition, and the societal impact of AI technologies. Beyond his academic role, Stadelmann is actively involved in the digital ecosystem as a (co-)founder and senior leader in several organizations, bridging the gap between research and practical implementation in the AI space.

• Statistics
• Machine Learning
• Statistical Inference
• +۳ مورد دیگر

Peter Grünwald is full professor of Statistical Learning at Leiden University's Mathematical Institute and senior researcher in the Machine Learning group at CWI (Centrum Wiskunde & Informatica) in Amsterdam. His pioneering work on e-values establishes a transformative framework for statistical inference that overcomes critical limitations of classical p-values, enabling flexible experimental designs while maintaining rigorous error control. His research centers on e-values and e-processes as a unifying paradigm between Bayesian and frequentist statistics, with core innovations in safe testing, anytime-valid inference, and optional continuation. These methods allow researchers to gather additional data after initial analysis without inflating Type I errors and to determine significance levels post-hoc—addressing longstanding rigidity in Neyman-Pearson hypothesis testing. His publication trajectory reveals rapid adoption of e-values across disciplines: from foundational theory in PNAS and JRSSB to clinical applications in survival analysis (NEJSDS) and epidemiology (medrxiv meta-analysis). The 2022–2024 publications demonstrate methodological maturation, with implementations in R (safestats package) and growing use in social sciences (PsyArXiv) and causal inference (JASA). Scientific recognition includes: ERC Advanced Grant (2024) for developing flexible statistical inference theory via e-values His ERC-funded project drives current research, while his internship policy restricts non-Dutch master’s/bachelor’s students but welcomes advanced international PhD candidates. Collaborative work spans statisticians (Ly, de Heide, Koolen), machine learning researchers (Ramdas, Shafer), and medical scientists (van Werkhoven). As core member of CWI's Machine Learning group, he advances theoretical foundations with practical impact—evidenced by the first live deployment of e-values in a BCG vaccine meta-analysis. His work redefines statistical practice for adaptive data collection in clinical trials, AI, and social science research.

Tova Miloمشاهده پروفایل

استاد

• Databases
• Big Data Management
• Machine Learning for Data Management
• +۷ مورد دیگر

Professor Tova Milo is the Chair for Information Management at the School of Computer Science, Tel Aviv University, leading the prominent Databases Lab (DB Group). Her research spans databases, big data management, crowd-based data sourcing, and business process querying, with significant contributions to data integration and semi-structured data systems. Her research interests focus on innovative approaches to data management challenges through machine learning integration, crowd computing, and business process analysis. Key projects include Business Process Querying (BPQ) for analyzing BPEL specifications, MoDaS for crowd-based data management, and PROX for data provenance summarization. Her work bridges theoretical foundations with practical applications in fraud detection, recommendation systems, and data cleaning. Analysis of her recent publications reveals strong trends in human-in-the-loop data management systems, with growing emphasis on crowd integration for data cleaning and knowledge acquisition. Her research increasingly combines traditional database theory with machine learning techniques for scalable big data processing, while maintaining focus on business process modeling and provenance tracking. ACM PODS Alberto O. Mendelzon Test-of-Time Award (2010) ERC Advanced Investigators grant MoDaS (2011) The Weizmann Prize for Exact Sciences (2017) VLDB Women in Database Research award (2017) IEEE TCDE Impact award (2022) ISF Breakthrough Research Grant (2022) Doctorate Honoris Causa, University of Zurich (2023) ACM Fellow Member of Academia Europaea Professor Milo has advised over 30 graduate students including PhD candidates like Yael Amsterdamer and Ohad Greenshpan, and numerous MSc students working on projects including MoDaS, BPQ, and EDOS. Her research has been supported by major grants including the ERC Advanced Investigators grant and ISF Breakthrough Research Grant. She actively collaborates with industry partners including IBM and Microsoft, particularly in business process management standards. She directs Tel Aviv University's Databases Lab, which maintains the DB Group with multiple research streams including business process querying (BPQ), crowd-based data management (MoDaS), and self-adaptive data dissemination (EDOS/COLT). The lab operates from the Schreiber Building (M-20) and maintains strong international collaborations, particularly with European institutions through the ERC-funded MoDaS project.

Christian Ludwigمشاهده پروفایل

استاد مدعو

• Solid Waste Treatment
• Nanoparticle Synthesis
• Bioenergy Technology
• +۳ مورد دیگر

Christian Ludwig is an Adjunct Professor at EPFL and head of the joint EPFL-PSI Professorship, leading the Chemical Processes and Materials (CPM) research group at the Paul Scherrer Institute. His work bridges sustainable resource management, waste treatment technologies, and nanomaterials development with applications in energy and environmental systems. Education: PhD in Inorganic, Analytical, and Physical Chemistry from University of Berne (1993) Master's degree from University of Berne (1990) Research interests focus on developing sustainable technologies for resource management. His group investigates thermal and aqueous waste treatment systems, bioenergy technologies, nanoparticle-based materials for clean technology applications, analytical methods for real-time environmental monitoring, and recycling strategies for minerals and rare earth elements. Recent work examines nucleation processes, trace element fate in bioenergy systems, and algal biomass applications. Publication trends show strong focus on sustainable materials processing, environmental nanotechnology, and waste valorization. Recent articles demonstrate innovative approaches to nanoparticle characterization, supercritical fluid applications, and resource recovery from complex waste streams. Scientific awards: No major awards documented in provided materials. Advising and lab leadership: Supervised 23 PhD students and leads the Ludwig Group (EPFL) and CPM group (PSI), focusing on sustainable energy carriers and processes. Research integrates synchrotron methods, nanoparticle synthesis, and environmental technology development.

Gianvito Laeraمشاهده پروفایل

پژوهشگر ارشد

• prospective memory
• time estimation
• aging
• +۵ مورد دیگر

Gianvito Laera is a Postdoctoral Research Fellow at the University of Geneva's Department of Psychology within the Faculty of Psychology and Educational Sciences. He works in the Cognitive Aging Lab, focusing on prospective memory research with particular emphasis on time-based memory processes across the lifespan. His research integrates cognitive psychology, neuroscience, and gerontology to understand how people remember to perform future intentions. Dr. Laera received his PhD in Psychology from the University of Geneva (2018-2023), following a Master of Science in Neuroscience and Neuropsychological Rehabilitation from the University of Padua, Italy (2013-2016), and a Bachelor of Science in Psychological Sciences and Techniques from the University of Bari 'Aldo Moro', Italy (2010-2013). Prior to his doctoral studies, he worked as a Research Assistant at Keele University's Neuropsychology Lab (2016-2018) and completed a research internship at the University of Padua (2015-2016). His research primarily investigates prospective memory—particularly time-based prospective memory—which involves remembering to perform intended actions at specific future times. His work examines age-related differences in these processes, neural correlates using EEG methodology, strategic monitoring behaviors, and the impact of various contextual factors on memory performance. He employs both laboratory and web-based experimental approaches to study how people monitor time, check clocks, and manage cognitive resources when executing delayed intentions. His research has important implications for understanding cognitive aging and developing interventions to support memory in older adults. Analysis of his publication record reveals consistent focus on time-based prospective memory mechanisms across 15 recent publications. His work demonstrates sophisticated methodological approaches including meta-analyses, experimental manipulations of clock-speed, EEG measurements, and longitudinal assessments. Key trends include examining the cost of monitoring behavior, strategic clock-checking patterns, neural correlates of memory retrieval, and the relationship between personality factors and cognitive performance in aging populations. While no specific scientific awards are documented in the available information, his research has been published in high-impact journals across psychology, neuroscience, and gerontology, reflecting recognition within his field. As a postdoctoral researcher, Dr. Laera continues to develop his independent research program while collaborating with senior researchers in the Cognitive Aging Lab. His work bridges experimental cognitive psychology with real-world applications for understanding memory changes in aging populations.