جست‌وجوی استاد و پژوهشگر

• Anesthesiology
• Hemodynamic Monitoring
• Perioperative Care
• +۵ مورد دیگر

Karim Kouz is a medical researcher specializing in anesthesiology at the University Medical Center Hamburg-Eppendorf, where he works in the Department of Anesthesiology. With an extensive publication record spanning from 2016 to 2025, Dr. Kouz has established himself as a significant contributor to perioperative medicine research, particularly in hemodynamic monitoring and blood pressure management during surgery. His research interests center on intraoperative hypotension, hemodynamic monitoring technologies, personalized blood pressure management during surgery, and the relationship between hemodynamic parameters and postoperative outcomes. Dr. Kouz has been involved in numerous clinical trials, method comparison studies, and guideline development projects, often collaborating with Professor Bernd Saugel and other prominent researchers in the field. His work bridges clinical practice with technological innovation, examining both traditional monitoring methods and emerging technologies like smartphone-based blood pressure measurement and processed electroencephalography. Dr. Kouz's publication portfolio demonstrates a consistent focus on improving perioperative care through evidence-based approaches. His recent work includes contributions to German clinical guidelines for hemodynamic monitoring during non-cardiac surgery and participation in multicenter trials examining the relationship between blood pressure management and postoperative complications. His research has appeared in leading anesthesiology journals including British Journal of Anaesthesia, Journal of Clinical Monitoring and Computing, and Anesthesiology. As an active researcher in the European anesthesiology community, Dr. Kouz has contributed to the EU-HYPROTECT registry and other collaborative projects examining hypotension prediction and management during surgery. His work represents an important contribution to the evolving understanding of optimal hemodynamic management in the perioperative period.

Paul M.J. Van den Hofمشاهده پروفایل

استاد

• Data-driven modeling
• Control systems
• Dynamic networks
• +۶ مورد دیگر

Paul M.J. Van den Hof is a Full Professor at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e), specializing in data-driven modeling and control of dynamic systems. He leads the Control Systems Group and is affiliated with multiple research centers, including EAISI High Tech Systems, Mobility, and Foundational, as well as the EIRES Research initiative. Research Interests: His work focuses on developing fundamental techniques for dynamic network modeling, closed-loop identification, data analytics, experimental design, and model-based control. Applications span industrial process control, oil reservoir engineering, high-tech mechatronic systems, and cyber-physical systems. Recent projects include SYSDYNET (dynamic network identification), NAPAS (nanometer-accurate actuation), and CADUSY (data-driven modeling using symbolic methods). Scientific Contributions: Van den Hof has authored over 250 research outputs, including foundational work on identifiability in dynamic networks, frequency domain identification, and distributed control algorithms. His 2024-2025 publications address challenges in fault detection, Bayesian network topology identification, and multi-step least squares methods. He emphasizes practical implementation through tools like the SYSDYNET MATLAB toolbox. ERC Advanced Research Grant (2015) Honorary Member, Hungarian Academy of Sciences (2016) IEEE Fellow (2007) and IEEE Life Fellow (2023) IFAC Advisor (2020)

• Biogeochemistry
• Biodiversity
• Artificial Intelligence in Biodiversity Research
• +۳ مورد دیگر

Lara Kösters is a Doctoral Researcher at the Max Planck Institute for Biogeochemistry in Jena, Germany, affiliated with the Biogeochemical Integration department and the Biod.AI.versity Observation & Integration research group. Her work bridges computational methods with biodiversity and biogeochemical research. Ph.D. student (2021–present), Max Planck Institute for Biogeochemistry, Jena, Germany Research assistant (2020–2021), Humboldt-Universität zu Berlin M.Sc. in Life Science (2018–2020), University of Münster B.Sc. in Life Science (2015–2018), University of Münster Her research focuses on Artificial Intelligence in biodiversity studies , biogeochemical integration , and computational biology . She develops AI-driven tools for plant identification and ecological data management, as evidenced by her publications on deep learning for morphometrics, DNA barcoding frameworks, and parasitic plant research. Lara’s recent work involves geometric morphometrics , taxonomic affinity modeling , and DNA barcoding , reflecting a trend toward data science and environmental informatics in her publications.

Karl Wetteمشاهده پروفایل

پژوهشگر ارشد

• Gravitational Waves
• Neutron Stars
• Pulsars
• +۳ مورد دیگر

Dr. Karl Wette is a Research Fellow at the Centre for Gravitational Astrophysics at the Australian National University (ANU). He holds a B.Sc. from the University of Auckland and a Ph.D. from ANU. His research focuses on gravitational waves, neutron stars, pulsars, and data analysis theory, with a particular emphasis on detecting and interpreting gravitational wave signals from compact objects like black holes and neutron stars. Dr. Wette is actively involved in the LIGO Scientific Collaboration, Virgo Collaboration, and KAGRA Collaboration, contributing to the analysis of gravitational wave data from the third observing run. His work bridges theoretical astrophysics with experimental data analysis, aiming to uncover insights into extreme astrophysical phenomena. Research Interests: Gravitational waves, neutron star dynamics, pulsar physics, and data-driven methods for gravitational wave astronomy. Dr. Wette's projects include studying postmerger remnants of black hole-neutron star binaries, constraining ultralight vector boson models, and developing advanced search algorithms for continuous gravitational waves. Collaborations: Engaged with international teams to analyze multi-messenger data from gravitational wave observatories and gamma-ray satellites like Fermi-GBM and Swift-BAT. His contributions have advanced techniques for detecting transient gravitational wave signals and interpreting their astrophysical implications. Education: B.Sc. (University of Auckland), Ph.D. (ANU).

Susan Atheyمشاهده پروفایل

استاد

• Economics of Technology
• Antitrust Economics
• Machine Learning
• +۵ مورد دیگر

Susan Athey is the Economics of Technology Professor at Stanford Graduate School of Business (GSB), holding senior fellowships at the Stanford Institute for Economic Policy Research and the Stanford Institute for Human-Centered Artificial Intelligence. She earned a BA in Economics, Mathematics, and Computer Science from Duke University and a PhD from Stanford GSB. Her research bridges economics and computer science, focusing on digital markets, antitrust policy, and AI-driven social impact solutions. She founded the Golub Capital Social Impact Lab to leverage technology for social sector innovation, developing tools like the CAREER model to analyze labor market dynamics. Her tenure as Chief Economist at the U.S. Department of Justice’s Antitrust Division led to updated merger guidelines integrating modern economic analysis. Athey has pioneered methods for causal inference and policy design, emphasizing iterative, data-driven approaches. Awards include the John Bates Clark Medal (2007), and she serves as President of the American Economic Association. Education: Bachelor of Arts: Economics, Mathematics, Computer Science, Duke University PhD: Stanford Graduate School of Business Research Interests: Economics of technology and digital markets Antitrust policy and merger analysis Machine learning applications in economics Social impact initiatives using AI Health and labor economics Causal inference and policy evaluation Lab Initiatives: The Golub Lab collaborates on projects like AI-driven educational apps, healthcare counseling tools (e.g., Cameroon contraception app), and job market models (CAREER). She teaches the Data-Driven Impact course, emphasizing practical experimentation in social interventions. Grants & Leadership: Led DOJ’s antitrust technology policy team, rebranded the Expert Analysis Group. Collaborates with PayPal, World Bank, and tech-focused NGOs. Her work integrates interdisciplinary teams to address systemic challenges in policy and technology.

Quentin Changeatمشاهده پروفایل

استادیار

• Exoplanets
• Atmospheric Modeling
• Telescope Observations
• +۳ مورد دیگر

Quentin Changeat is an Assistant Professor at the Kapteyn Astronomical Institute, University of Groningen, and an Honorary Research Fellow in the Department of Physics and Astronomy at University College London. His research bridges exoplanet atmospheric studies and computational astrophysics, with affiliations spanning multiple international institutions. Research Interests: Dr. Changeat focuses on the physics and chemistry of exoplanet atmospheres, leveraging data from the James Webb Space Telescope (JWST), Hubble Space Telescope (HST), and Spitzer. His work emphasizes atmospheric retrieval techniques, machine learning applications, and the development of open-source tools like TauREx for spectral analysis. He is actively involved in the ESA Ariel mission, which aims to survey 1000 exoplanets by 2029. Publication Trends: His 15 most recent articles (2019–2024) reveal a strong emphasis on JWST/HST data analysis, atmospheric retrievals of hot Jupiters, and population-level studies. Key themes include thermal inversions, phase-curve degeneracies, and the development of statistical frameworks for large-scale exoplanet characterization. Machine learning and interdisciplinary collaborations feature prominently in his methodology. Awards: Honorary Research Fellow, University College London Academic Contributions: He leads educational initiatives like the ARES Summer School and ORBYTS program, mentors PhD students in exoplanet research, and develops datasets for community use (e.g., Ariel Data Challenge). His lab focuses on atmospheric retrieval algorithms and collaborates with teams at UCL, Flatiron Institute, and ESA.

• Information Retrieval
• XML Search Engines
• Text Search Engines
• +۸ مورد دیگر

Shlomo Geva is an Adjunct Professor in the School of Computer Science at Queensland University of Technology's Faculty of Science. His research focuses on information retrieval systems, particularly in specialized areas including XML search engines, text search engines, link discovery, and document computing. His academic work spans multiple disciplines within computer science, with particular emphasis on information retrieval technologies and their applications. Professor Geva's research interests include clustering algorithms, cross language information retrieval, focused information retrieval, information retrieval systems, link discovery mechanisms, search engine technologies, text indexing and retrieval methods, and XML indexing and retrieval techniques. His work demonstrates a consistent focus on improving the efficiency and effectiveness of information access systems across various data formats and domains. His recent publications reveal a trend toward applications of information retrieval techniques in diverse fields including remote sensing, bioinformatics, and data stream processing. The research shows an evolution from traditional information retrieval problems toward more specialized applications requiring advanced clustering algorithms and efficient data processing techniques for large-scale datasets. Professor Geva has successfully supervised numerous doctoral students whose research topics include indoor environment mapping by robots, cross-language information retrieval, natural language query interfaces for XML, evolvable hardware, and autonomous robot behavior systems.

• Hydrological modeling
• Flood forecasting
• Drought monitoring
• +۴ مورد دیگر

Robert Schweppe is a Researcher at the Department of Computational Hydrosystems , Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany. He has held this position since 2017, following prior roles as Project Engineer at HYDRON GmbH (2014-2017) and Research Assistant at UFZ (2013). Expertise in hydrological modeling using mHM, ECLand, LARSIM Developed pyflow configuration tools and MPR software for environmental data processing Key contributor to 4DHyro project integrating Earth Observation data with hydrological models His research interests span hydrological modeling , drought forecasting , machine learning applications , and climate change impacts on water systems. His 2022 publications on parameter regionalization and floodplain modeling demonstrate methodological innovations in environmental data analysis. Notable scientific recognitions include the Deutschlandstipendium scholarship (2012-2013) and Helmholtz Field Study Fellowship (2022). He collaborates extensively with European institutions on compound environmental risks and smart monitoring technologies .

• Complex Systems
• Dynamical Systems
• Network Science
• +۱۳ مورد دیگر

Luc Berthouze is a Professor of Complex Systems (Informatics) at the School of Engineering and Informatics, University of Sussex, where he leads interdisciplinary research at the intersection of mathematics, engineering, and neurophysiology. He also holds an honorary appointment at the Great Ormond Street Hospital Institute of Child Health, University College London. His educational background includes a PhD in Applied Mathematics and Computer Science from the University of Evry Val d’Essonne (1996), followed by research positions at the Electrotechnical Laboratory (ETL) and the National Institute of Advanced Industrial Science and Technology (AIST) in Japan, before joining the University of Sussex faculty in 2006. His research focuses on dynamical processes on networks, including neuronal synchronization, epidemic spreading, and fault detection in IT infrastructures. He develops mathematical models and analysis methods rooted in dynamical systems, random processes, graph theory, control theory, and signal processing. Applications span neuroscience (EEG, EMG, MEG), robotics, and large-scale network management. The trend in his recent publications reveals a strong emphasis on network dynamics across biological and technological systems. Key themes include functional connectivity inference, metastability in oscillatory networks, epidemic modeling on structured networks, and scalable observability in microservices. His work increasingly bridges neuroscience and computer engineering, exemplified by projects like 'Rethinking large-scale network management through the lens of neuroscience.' Mathematical Neuroscience Mathematical Epidemiology Time Series Analysis Network Analysis Synchronization and Criticality Motor Control and Coordination He has received substantial research funding from EPSRC, Innovate UK, Moogsoft, Aviva, and the Leverhulme Trust, supporting work on network controllability, data-driven decision making, and Bayesian inference. His grants often involve collaborations with industry partners, indicating applied and translational impact. He supervises research projects and teaches courses such as 'Intelligence in Animals and Machines,' contributing to both undergraduate and postgraduate education. His lab and research team work on developing scalable mathematical frameworks for network analysis, with applications in healthcare, robotics, and IT infrastructure.

Stoicuta Olimpiuمشاهده پروفایل

دانشیار

• Control Systems
• Electrical Engineering
• Renewable Energy
• +۴ مورد دیگر

Associate Professor Olimpiu Stoicuta is affiliated with the Polytechnic University of Timișoara's Faculty of Mechanical and Electrical Engineering, Department of Automation, Computers, Electrical and Power Engineering. His research focuses on advanced control systems for electrical motors, renewable energy integration, and econometric analysis of energy policies. He has extensive expertise in sensorless vector control, induction motor modeling, and optical communication technologies. Education details are not explicitly stated in the provided text, but his work indicates a strong background in electrical engineering and control systems. He has published widely on topics including adaptive observers, energy transformation systems, and underground communication solutions. His research interests span multiple domains: (1) Electrical Engineering with emphasis on motor control and power electronics; (2) Renewable Energy focusing on system integration and efficiency improvements; (3) Data Communication involving LiFi and optical networks for industrial applications; and (4) Econometric Modeling related to energy policy analysis in Romania and the EU. Recent publications (2020-2025) highlight trends in AI-driven network optimization, sensorless motor control advancements, and energy policy studies. Articles frequently address practical engineering challenges like underground communication reliability and EV autonomy enhancement. No specific awards or grants are mentioned, though his prolific publication record suggests sustained research activity. Laboratory and team involvement can be inferred through his work on robotics (exoskeleton control) and collaborative projects in industrial automation systems.

Martin Sullivanمشاهده پروفایل

مدرس ارشد

• Statistical Ecology
• Tropical Forest Ecology
• Biodiversity and Ecosystem Function
• +۱۲ مورد دیگر

Dr Martin Sullivan is a Senior Lecturer in Statistical Ecology at Manchester Metropolitan University, Faculty of Science and Engineering, within the Department of Natural Sciences. He previously held a postdoctoral position at the University of Leeds starting in 2014 and completed his PhD at the University of East Anglia. His research is centered on understanding how species and ecosystems respond to environmental change, with a strong focus on tropical forests, statistical modeling, and biodiversity conservation. His research interests span Statistical Ecology , Tropical Forest Dynamics , Biodiversity and Ecosystem Function , Environmental Change , and Conservation Biology . He has a long-standing interest in bird ecology, including non-native species and community changes in the UK. His work integrates large-scale datasets from networks such as Rainfor, AfriTRON, and ForestPlots, and he develops analytical tools like the BiomasaFP R package to support ecological research. The recent research articles highlight a strong trend in tropical forest carbon stocks , disturbance ecology (e.g., lightning) , community-based conservation , and statistical methodology development . His projects often involve international collaborations across Africa and Latin America, focusing on climate change impacts, restoration, and nature-based solutions. Dr Sullivan is actively involved in scientific service, including membership on the British Ornithologists’ Union Grants Committee. He leads and contributes to externally funded projects from NERC, GCRF, and UKRI, demonstrating significant grant acquisition and project leadership. He supervises PhD and MSc students, including Declan Cooper (UCL), Mark Thomas, and Jean d’Amour Maniriho (University of Rwanda), and emphasizes research-informed teaching in statistics and tropical ecology. He is a key contributor to several research networks and initiatives, including the AfriMont network for African montane forests, the WABiLED programme in West Africa, and collaborative mangrove restoration projects with institutions in Sierra Leone, Liberia, and the UK. His fieldwork spans Rwanda, Uganda, DRC, Peru, and Sierra Leone, reflecting a deeply collaborative and globally engaged research program. AfriMont - African montane forest plot network Monitoring Upper Guinean forests (GCRF-funded) Co-designing nature-based solutions in West African mangroves (UKRI-funded) Role of lightning in African montane forest dynamics (NERC-funded)

Clarissa Glaserمشاهده پروفایل

پژوهشگر

• Hydrology
• Hydrogeology
• Groundwater-Surface Water Interactions
• +۷ مورد دیگر

Dr. Clarissa Glaser is a Postdoctoral Researcher in Hydrology at the Institute for Geography, University of Bonn, Germany. She is a member of the Hydrology Research Group led by Dr. Julian Klaus and specializes in groundwater-surface water interactions, ecohydrology, and stream intermittency. Her research spans regional contexts including Southwest Germany, the Eifel/Ardennes, and the USA (Northwest). University: University of Bonn School: Institute for Geography Department: Department of Geography Position: Postdoctoral Researcher (Researcher) Email: cglaser@uni-bonn.de Clarissa Glaser’s research focuses on understanding hydrological processes in headwater streams, particularly how water exchange between groundwater and surface water affects water quality, biogeochemical cycling, and ecosystem health. Her work integrates field measurements, tracer hydrology, and modeling to study solute transport, hyporheic exchange, and the impacts of climate change on streamflow intermittency. She is particularly interested in ecohydrological separation and the critical zone dynamics. Her recent publications span topics such as tracer bias in stream experiments, hyporheic exchange variability, contaminant transport during storms, and greenhouse gas emissions from streams. These works reflect a strong interdisciplinary approach combining hydrology, biogeochemistry, and environmental modeling. Her research is increasingly focused on predicting hydrological responses under changing climate and land use. Dr. Glaser has received several scientific awards and funding, including: Scholarship from the Klaus Tschira Foundation (2023) Athene Program Fellowship for female researchers (2021–2023) DAAD support for international collaboration (2019) Research grant from the German Hydrological Society (2018) Klaus Tschira Boost Fund Fellow She has been actively involved in mentoring students and supervising interns, particularly within collaborative research projects. Dr. Glaser leads multiple third-party funded projects, including those supported by the Klaus Tschira Foundation, Argelander Academy, and the Transdisciplinary Research Area at the University of Bonn. She is also engaged in academic service, having co-organized sessions at major conferences such as the FH-DGGV and EGU, and led the 2024 Hydrology Conference in Bonn on 'Intermittency in Headwater Streams'. Dr. Glaser contributes to teaching and offers consultation hours. She is based in Bonn, Germany, and maintains active profiles on ResearchGate, Google Scholar, and Twitter for scientific outreach.

Anestis Touloumisمشاهده پروفایل

مدرس ارشد

• Biostatistics
• Categorical Data Analysis
• High-Dimensional Statistics
• +۱۳ مورد دیگر

Anestis Touloumis is a Principal Lecturer in the School of Architecture, Technology and Engineering at the University of Brighton, affiliated with the Computing and Mathematical Sciences Research Excellence Group. He holds a PhD in Statistics from the University of Florida and has held postdoctoral positions at the European Bioinformatics Institute and the University of Cambridge before joining Brighton in 2015. Education: PhD in Statistics, University of Florida (2006–2011) MSc in Applied Statistics, University of Piraeus (2003–2006) BSc in Mathematics, Aristotle University of Thessaloniki (1998–2003) His research centers on biostatistics, high-dimensional statistics, and statistical genetics, with a focus on developing methods for correlated responses, covariance matrix estimation, and hypothesis testing in high-dimensional settings. His work is applied in omics, health studies, and social sciences, and he actively disseminates methods through R packages on CRAN and Bioconductor. He teaches a range of statistical modules using R and SAS, emphasizing conceptual understanding and critical thinking. The recent research articles reflect strong trends in biostatistical methodology, particularly in high-dimensional inference, longitudinal and correlated data analysis, and statistical computing. There is a consistent emphasis on developing robust, open-source tools for real-world applications in healthcare and data science. Scientific Awards and Professional Service: Treasurer, British and Irish Region of the International Biometric Society (2020–present) Committee Member, British and Irish Region of the International Biometric Society (2019–present) External Examiner, MSc in Applied Statistics, Birkbeck University of London (2020–present) Member, International Biometric Society He has been active in research supervision and mentoring, with a stated interest in supervising postgraduate students in machine learning, categorical data, and high-dimensional statistics, often involving software development. He has contributed to research grants, notably as a Co-Investigator on the ERDF-funded Digital Research & Innovation Value Accelerator (DRIVA) project (2018–2021). He is involved in multiple research collaborations and has delivered invited talks and peer reviews for leading journals. His work bridges theoretical statistics and practical applications across disciplines.

Thomas Hobigerمشاهده پروفایل

استاد

• Satellite Navigation
• Inertial Navigation
• Sensor Fusion
• +۷ مورد دیگر

Thomas Hobiger is a Professor and Head of the Institute of Navigation at the University of Stuttgart, Germany, and serves as Dean of Studies for Geodesy and Geoinformatics under Faculty 6: Aerospace Engineering and Geodesy. His research focuses on satellite navigation, inertial navigation systems, sensor fusion, and geodetic applications such as precise orbit determination and GNSS meteorology. He leads a team developing high-precision positioning solutions for autonomous vehicles and airspace surveillance systems. Hobiger holds a PhD from Vienna University of Technology (2005) and has held tenured positions at institutions including Chalmers University of Technology (Sweden) and Japan’s National Institute of Information and Communications Technology (NICT). Notable awards include the AGU Geodesy Section Award (2018) and the NVIDIA Global Impact Award (2016 finalist). He is actively involved in editorial roles for journals like Journal of Geodesy and holds leadership positions in international geodetic organizations. Research interests span navigation hardware/software development, real-time kinematic positioning, and interdisciplinary projects combining GNSS with meteorology and oceanography. His work emphasizes practical applications through collaborations with industry and space agencies, such as JAXA and ESA.

• Wireless Communications
• Remote Sensing
• Distributed Systems
• +۶ مورد دیگر

Juan Carlos Merlano Duncan is a Research Scientist at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specializing in the SigCom department. He contributes to the SATSENT project with Prof. Ottersten and Dr. Symeon Chatzinotas, focusing on satellite sensor networks for spectrum monitoring. His roles include advancing technologies in wireless communications, remote sensing, and embedded systems. **Education:** Bachelor's in Engineering from Universidad del Norte (2004) M.Sc. and Ph.D. in Telecommunications from Universitat Politècnica de Catalunya (2009 and 2012) **Research Interests:** Wireless communications, remote sensing, distributed systems, Software Defined Radios (SDR), embedded systems, and AI-driven satellite technologies. His work emphasizes FPGA design, radar systems (e.g., SABRINA project), and cognitive radio networks. **Publications:** Recent work spans AI in satellite communications, digital beamforming, and energy-efficient MIMO systems. Notable themes include STAR-RIS networks, onboard image classification, and THz reconfigurable surfaces. **Grants & Advising:** No explicit grants or advisees listed, though his projects imply collaborative research funding. He has led FPGA implementations for radar and cognitive radio systems. **Labs & Teams:** Core member of SnT’s SigCom group, contributing to satellite telecommunication testbeds using COTS devices and onboard processing architectures.