جست‌وجوی استاد و پژوهشگر

• Biomedical Informatics
• Artificial Intelligence in Healthcare
• Machine Learning
• +۱۲ مورد دیگر

Dr. Shahzad Mumtaz is a Lecturer at the School of Natural and Computing Sciences, University of Aberdeen, where he contributes to research and education in computational health and data science. His work bridges artificial intelligence and healthcare, focusing on real-world applications in medical data modeling and digital health tools. Research Interests: His research spans biomedical informatics, machine learning, natural language processing, electronic health records (EHR), phenotype libraries, and medical image analysis. He is particularly active in developing tools for clinical data standardization, such as the Carrot tool for OMOP CDM, and in AI-driven solutions for fraud detection, deepfake identification, and clinical decision support. His interdisciplinary work integrates computer science with public health and clinical medicine. Publication Trends: His recent publications (2023–2025) emphasize AI applications in healthcare, including deep learning for fake medical image detection, NLP for financial text analysis, and vision transformers for weather and skin cancer classification. He frequently collaborates on large-scale health data initiatives like CO-CONNECT and the UK Phenotype Library, reflecting a strong focus on scalable, interoperable digital health infrastructure. Scientific Contributions: Core contributor to the CO-CONNECT project for national health data access during the pandemic. Developer of the Carrot tool for improving OMOP data curation. Active in advancing phenotype library standards and EHR-based research. Advising and Grants: While no formal students or grants are listed in the provided text, his extensive collaborative work suggests active involvement in research teams and potential supervision of graduate researchers. He is likely engaged in funded projects related to health data science and AI, given the scale and scope of his publications. Labs and Teams: Dr. Mumtaz is affiliated with research initiatives at the University of Aberdeen focused on biomedical informatics and trusted research environments. He collaborates with multidisciplinary teams across the UK, particularly in projects involving NHS data, digital phenotyping, and AI safety in healthcare.

Simon Placeمشاهده پروفایل

مدرس ارشد

• Air Transport Safety & Investigation
• Airworthiness
• Aviation Management & Operations
• +۷ مورد دیگر

Dr Simon Place is a Senior Lecturer at Cranfield University, affiliated with the National Flying Laboratory Centre. He holds a PhD in reliability and safety assessment of helicopter transmission systems and is a Chartered Engineer (CEng) and Member of the Institute of Mechanical Engineers (MIMechE). His expertise lies in air transport safety, airworthiness, aviation operations, and maintenance human factors. PhD, Cranfield University (research on helicopter transmission reliability) MSc in Flight Dynamics, Cranfield University BSc in Engineering Science & Technology, Loughborough University Dr Place's research focuses on safety and risk assessment, reliability analysis, and human factors in aviation maintenance. He has led projects for clients such as DSTL, UK Ministry of Defence, QinetiQ, and international civil aviation authorities. His work bridges theoretical modeling with practical applications in aircraft systems and safety. His recent publications (2023–2024) emphasize aerodynamic modeling of the Saab 340B, flight simulation, and landing gear health assessment using flight data and prognostics. These works reflect a strong trend toward data-driven, hybrid approaches combining simulation, optimization, and real-time monitoring for proactive maintenance and safety enhancement. His scientific recognitions include: Chartered Engineer (CEng) Member of the Institute of Mechanical Engineers (MIMechE) Dr Place leads airborne laboratory training and contributes to MSc modules in Airworthiness, Safety Assessment of Aircraft Systems, and Safety & Accident Investigation. He collaborates extensively with researchers like James Whidborne and Mushfiqul Alam. He has no known grants listed, but his applied research suggests active funding from defense and aviation sectors. He advises research students, though specific names are not provided. He is a key member of the Safety and Accident Investigation Centre at Cranfield, leveraging first-hand experience in military and airline operations and accident investigation. His team focuses on real-world aviation safety challenges, certification, and design improvement.

Hans A. Wintherمشاهده پروفایل

دانشیار

• Theoretical Cosmology
• Large-Scale Structure Formation
• Modified Gravity
• +۳ مورد دیگر

Hans A. Winther is an Associate Professor at the Institute of Theoretical Astrophysics, University of Oslo, specializing in theoretical cosmology with a focus on large-scale structure formation. He holds a Master’s (2010) and PhD (2013) from the University of Oslo, followed by postdoctoral research at the University of Oxford and the University of Portsmouth. His work bridges cosmological theory with advanced numerical simulations, emphasizing modified gravity, dark matter models, and N-body codes. Winther leads courses such as AST5220 Cosmology II and AST1010 Introduction to Astronomy , integrating computational tools like FML and MG-PICOLA . His research includes developing simulation frameworks for modified gravity (e.g., ISIS , SCALAR ) and axion-like dark matter. He actively contributes to the Euclid mission through simulations and data analysis, addressing nonlinear cosmological structures and parameter constraints. Notable projects include the FML C++ library for parallel grid-particle algorithms and the MG-PICOLA code for fast modified gravity simulations. His work underscores the interplay between theory and computation in cosmology, aiming to test gravity and dark matter hypotheses using observational data from surveys like Euclid and LSST.

Maicol Ochoaمشاهده پروفایل

پژوهشگر

• Quantum Science
• Applied Mathematics
• Nanoscale Science
• +۶ مورد دیگر

Maicol Ochoa is a Researcher affiliated with the University of Maryland College Park's Department of Chemistry & Biochemistry and the National Institute of Standards and Technology (NIST). His research focuses on quantum science, nanoscale systems, and applied mathematics, with applications in silicon-based quantum devices and quantum simulations. He holds a B.S. in Chemistry and M.S. in Mathematics from Universidad Nacional de Colombia, and a Ph.D. in Chemistry and Chemical Biology from Cornell University. His postdoctoral work included roles at UC San Diego and the University of Pennsylvania. Affiliations: IPST (Institute for Physical Science and Technology), Department of Chemistry & Biochemistry, NIST Research Themes: Quantum thermodynamics, nanoelectronics, electronic structure calculations, and many-body theory in silicon quantum devices His work explores phenomena such as energy conversion in nanoscale systems, quantum coherence effects, and the development of protocols for Fermi-Hubbard model parameter extraction. He has presented at leading conferences like the APS Global Physics Summit and the Silicon Quantum Electronics Workshop, and authored over 20 peer-reviewed publications in journals like Physical Review B and Journal of Applied Physics . He was honored with the 2022 PML Distinguished Associate Award for his contributions to quantum science. He collaborates internationally, including with the Nicolaus Copernicus University in Poland, and mentors students through the MathQuantum RTG and TREND REU programs, focusing on computational methods in quantum device modeling and nanoscale transport.

David M W Powersمشاهده پروفایل

استاد

• Artificial Intelligence
• Cognitive Science
• Robotics
• +۴ مورد دیگر

Professor David M W Powers is a leading academic at Flinders University of South Australia, holding the Professor of Computer and Cognitive Science position. He serves as Visiting Professor at Beijing University of Technology and contributes extensively to editorial and program committees, including as Editor-in-Chief of Springer's Cognitive Science and Technology series. PhD in Computational Psycholinguistics (UNSW) Founding President of ACL SIGNLL and CoNLL conference series Recipient of 15+ major research grants including multiple ARC and NSF awards His research spans Artificial Intelligence, Cognitive Science, Robotics, and Biomedical Engineering with a focus on: Embodied Conversational Agents Brain-Computer Interfaces Parallel Logic Programming Evaluation Metrics in Machine Learning Assistive Technologies for disability support AI in Health and Education Recent publications emphasize optimization algorithms for autonomous systems (AUV routing models) and evaluation methodology advancements . Scientific awards include the Loebner Prize Bronze Medal and multiple ARC grants totaling over $30M in funding. Teaching roles include coordination of courses in Artificial Intelligence, Computational Intelligence, and Human-Computer Interaction . Professional engagements span leadership roles in ACL, ACM, and IEEE, with significant industry collaboration through startups like YourAmigo Pty Ltd.

Kristian Debrabantمشاهده پروفایل

دانشیار

• Numerical Analysis
• Stochastic Models
• Numerical Methods and Simulation
• +۷ مورد دیگر

Kristian Debrabant is an Associate Professor at the Department of Mathematics and Computer Science, Faculty of Science and Engineering, University of Southern Denmark. He is also affiliated with the STEM Center for Educational Research – FNUG, highlighting his dual engagement in research and pedagogical development. His academic credentials include a Dr.rer.nat. degree, reflecting a strong foundation in mathematical sciences. Department: Department of Mathematics and Computer Science Position: Associate Professor in Computational Science Additional Affiliation: STEM Center for Educational Research – FNUG Email: debrabant@imada.sdu.dk ORCID: https://orcid.org/0000-0003-2901-162X His research lies at the intersection of numerical analysis and stochastic modeling, with a focus on developing and analyzing numerical methods for stochastic differential equations (SDEs). Key areas include Runge-Kutta methods, exponential integrators, weak and strong convergence, and applications in computational science. He also contributes to interdisciplinary work, such as urban traffic modeling and environmental systems. Recent publications show a consistent trend in advancing numerical schemes for SDEs, particularly those with non-standard noise (e.g., fractional Brownian motion), stiff systems, and non-globally Lipschitz coefficients. His work spans theoretical developments in convergence and order conditions to practical implementations in finance, ecology, and engineering. The integration of B-series and tamed schemes reflects a deep engagement with both classical and modern numerical frameworks. Kristian Debrabant supervises PhD students, as indicated by the 'PhD supervision (2)' note in his profile. While specific grant details are not listed, his publication record and active research suggest ongoing funding support. His involvement with the STEM Center implies leadership or significant contribution to educational innovation in STEM disciplines.

Philipp Deindlمشاهده پروفایل

پزشک-پژوهشگر

• Neonatology
• Pediatric Intensive Care
• Pain Assessment in Infants
• +۳ مورد دیگر

Dr. Philipp Deindl is a Physician Scientist at the University Medical Center Hamburg-Eppendorf (UKE) , specializing in Neonatology and Pediatric Intensive Care Medicine . He operates within the Faculty of Medicine and contributes to the Section Neonatology and Pediatric Intensive Care Medicine . Academic focus on neonatal pain assessment Research in pediatric sedation protocols Expertise in mechanical ventilation training Editorial contributions to pediatric pain scales His 2025-2024 research includes: AI-based neonatal pain detection systems Gentamicin pharmacokinetics in neonates Impact of maternal thyroid disorders on neonates Standardization of endotracheal tube placement His work appears in Frontiers in Pediatrics , European Journal of Pain , and Pediatric Research . Professional Memberships : Gesellschaft für Neonatologie und Pädiatrische Intensivmedizin (GNPI) Deutsche Gesellschaft für Kinderheilkunde und Jugendmedizin (DGKJ) European Society of Paediatric and Neonatal Intensive Care (ESPNIC) Deutsche Interdisziplinäre Vereinigung für Intensiv- und Notfallmedizin (DIVI)

• Small Animal Breeding and Improvement
• Goat and Sheep Production
• Animal Science
• +۲ مورد دیگر

Füsun COŞKUN is an Assistant Professor at Ahi Evran University's Vocational School of Technical Sciences, Department of Plant and Animal Production, where she has been employed full-time since 2012. She previously served as Department Head from 2012-2013. Education: PhD in Animal Science, Ankara University (2003-2008) MSc in Animal Science, Ankara University (2000-2003) BSc in Animal Science, Ankara University (1995-2000) Research Focus: Her primary expertise is in Small Animal Breeding and Improvement, with specific emphasis on goat and sheep production systems. Research areas include lactation performance in Maltese goats, milk quality assessment, somatic cell count analysis, breeding strategies for Akkeci sheep, and sustainable animal husbandry practices. She employs mathematical modeling for performance prediction and investigates traditional Turkish animal practices. Publication Trends: Her 61 publications demonstrate evolving focus from cultural animal practices (2012-2016) to quantitative animal science (2017-present). Recent work emphasizes dairy goat production, milk composition analysis, and breeding efficiency, utilizing advanced statistical models and sustainable approaches. Awards: Session Best Paper Award, Eminent Association of Researcher in Biological and Medical Sciences (2017) Grants & Projects: Has led 11 research projects including: Malta Keçisi Oğlaklarının Besi Performansının Belirlenmesi (2023-2024) Somatik Hücre Sayısının Keçi Sütü Kalitesine Etkisi (2021-2022) Akkeci Female Kids Early Breeding (2016) Maltese Goat Milk Composition Analysis (2014-2016) Advising: Supervised Master's student Mercan Karakaş (2020) on somatic cell count detection methods in ruminant milk. Collaborations: Extensive work with researchers including Mehmet Ertuğrul (Ankara University) and Orhan Yılmaz (Ardahan University) on animal breeding and ethology projects.

• Distributed Data Management
• Cloud Computing
• Digital Cultural Heritage
• +۴ مورد دیگر

Renata Słota is a Professor at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, where she serves as Vice-Dean of the Faculty of Development. Her office is located at D-17, ul. Kawiory 21, room II, 3.34, with contact details including phone +48 12 328 33 35 and email rena@agh.edu.pl. She also contributes to academic governance as a member of the Disciplinary Council for Technical Information Technology and Telecommunications. Her research centers on distributed data management and cloud computing , with pioneering work in digital cultural heritage systems , blockchain-based decentralized authority , and scientific workflow automation . Notable contributions include integrated frameworks for 3D Cultural Heritage objects management, consensus mechanisms for collaborative data sharing, and multi-cloud data access solutions. Her work bridges theoretical advances with practical applications in cultural preservation and scientific computing. Analysis of her 2020-2026 publications reveals dominant trends in decentralized data governance , cultural heritage digitization , and hybrid cloud workflow management . Key themes include blockchain applications for organizational structures, semantic interoperability for quality-oriented data access, and reproducibility frameworks for computational experiments. Her research consistently addresses real-world challenges in global data accessibility and fault tolerance. Professor Słota actively participates in major research initiatives including the Onedata project for global data federation and the Scalarm platform for distributed parameter studies, demonstrating leadership in data-intensive computing environments and collaborative infrastructure development.

Sun Jingمشاهده پروفایل

دانشیار

• Strategic Decision-Making
• Change Management
• Service Operations Management
• +۵ مورد دیگر

Sun Jing is an Associate Professor at the Department of Management Science and Engineering, School of Economics and Management, Tsinghua University. Her research spans strategic decision-making, service operations management, statistical data mining, and total quality management. She has extensive academic leadership experience, including roles in ISO standardization committees and the Chinese Quality Association. Ph.D. in Management from Beijing University of Aeronautics and Astronautics (1999) M.Sc. and B.Sc. in Technology Economics & Systems Engineering from Tianjin University (1994, 1991) Her recent work focuses on statistical process control for autocorrelated systems, Six Sigma methodologies, and healthcare quality management. She has received multiple national awards for her contributions to quality engineering and education, including the National Standardization Innovation Contribution Award (2014) and Ministry of Education Humanities and Social Sciences Research Award (2009). ISO/TC69/SC7/WG2 Chair (2017–Present) Former ISO/TC69/SC7 Chair (2008–2016) Keynote speaker at international conferences (INFORMS, Korea-China Quality Symposium) She has led technical reports on higher education quality, two-sigma integration performance evaluation, and case studies for organizations like Beijing Daxing International Airport. Her teaching includes courses on data modeling, quality management, and decision analytics.

• Optogenetic Gene Therapy
• Retinal Neurobiology
• Vision Restoration
• +۳ مورد دیگر

Dr. Moritz Lindner is a Senior Postdoctoral Research Fellow at the Nuffield Laboratory of Ophthalmology , part of the Medical Sciences Division at the University of Oxford . Affiliated with St Cross College , his work focuses on optogenetic gene therapy for restoring vision in retinal blindness models. University: University of Oxford Department: Nuffield Laboratory of Ophthalmology College: St Cross College Lindner's research spans retinal neurobiology , visual electrophysiology , and gene therapy . His recent publications analyze trends in vision restoration technology , retinal pathology , and neuroengineering . Scientific Awards: Goodger and Schorstein Postdoctoral Scholarship (2018) Knoop Junior Research Fellow (2016) German Research Foundation Fellowship (2016) BONFOR Gerok Fellowship (2015) Travel Award of the German Retina Society (2015) Doctorate (summa cum laude) (2012) Poster Award of the German Physiological Society (2012) Lindner collaborates with Professor Mark Hankins and is part of the Retinal Neurobiology and Optogenetics Group . He has developed tools like ERGtools2 for visual electrophysiology data analysis.

Svetlana Lazarovaمشاهده پروفایل

استادیار

• Biosorption
• Ecology
• Water Analysis
• +۳ مورد دیگر

Svetlana Lazarova is an Assistant Professor at the University of Architecture, Civil Engineering and Geodesy, affiliated with the Faculty of Hydrotechnics and the Department of Water Supply, Sewerage, Water and Wastewater Treatment. Her research focuses on biosorption, water quality assessment, and circular economy applications in wastewater management. Research Trends: Analysis of municipal wastewater sludge for resource recovery, biosorbent development from agricultural waste, and ecotoxicological evaluation of water systems. Leadership: Head of the Water Analysis Laboratory, overseeing analytical workflows and method development. She has published extensively on wastewater treatment technologies and Bulgarian environmental compliance. Contact: slazarova_fhe@uacg.bg .

Corina Dimaمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Computational Linguistics
• Semantic Composition
• +۴ مورد دیگر

Corina Dima is a Researcher at the University of Stuttgart's Analytic Computing group (KI), specializing in natural language processing and computational linguistics. Her work bridges theoretical linguistics with practical applications in semantic composition, knowledge graphs, and biomedical entity linking, with strong collaborations at both the University of Stuttgart and University of Tübingen. Dr. Dima earned her PhD from the University of Tübingen in 2019 with a dissertation on composition models for nominal compounds. Her research focuses on semantic interpretation of multi-word expressions, distributional semantics, and German language processing, contributing foundational work on transformation weighting models and annotation schemes for compound-internal relations. Her publication trends reveal a strategic evolution from core NLP challenges (prepositional phrase attachment, noun compound interpretation) toward biomedical applications (WikiMed-DE) and knowledge graph evolution (Wikidated). Recent work emphasizes German-language biomedical entity linking and efficient composition models that balance performance with parameter reduction, demonstrating consistent innovation in dataset construction and model design. As part of the Analytic Computing research group, Dr. Dima contributes to the University of Stuttgart's artificial intelligence initiatives, particularly in semantic web technologies and knowledge-driven NLP systems. Her collaborative projects with Steffen Staab and Erhard Hinrichs highlight her integration within a leading European research ecosystem focused on scalable language understanding solutions.

Miek Schlangenمشاهده پروفایل

پژوهشگر

• Food Texture Analysis
• Food Mechanical Properties
• Machine Learning Applications in Food Science
• +۳ مورد دیگر

Miek Schlangen is a postdoctoral researcher at SDU FOOD MATTERS (University of Southern Denmark), specializing in food texture engineering, mechanical properties of meat analogues, and machine learning applications in food science. She obtained her PhD in Food Process Engineering from Wageningen University (2024), focusing on dry fractionation of plant proteins, transglutaminase crosslinking, and structuring into meat analogues. Active in AI-driven hierarchical food structure design (FIBROUSNESS project, 2024-2027) Developed image analysis methods for fibrousness quantification Expert in mechanical anisotropy assessment of meat analogues Research Interests: Her work bridges food biophysics, advanced processing technologies, and computational modeling to create plant-based meat alternatives with optimized structural and textural properties. Key focus areas include: Multiscale fibrousness characterization Enzymatic protein modification Machine learning for rheological prediction Polysaccharide-protein interactions Non-linear food material behavior Endogenous starch utilization Scientific Contributions: Miek's research output includes 11 publications (2025-2021) covering meat analogue development, plant protein structuring, and sustainable ingredient applications. Her work has received significant attention with 3 citations in 2025 and 15 citations in 2024. 2023 - Honorable Mention, Women in Science Rising Talent Prize 2022 - Structural characterization of plant-based meat replacers 2021 - Texture evaluation methodology review Collaborative Network: Maintains active collaborations with researchers at Wageningen University and SDU Biotechnology, with external partnerships across Europe and Asia. Current work focuses on quantitative relationships between mechanical anisotropy, macrostructure, and microstructure in meat analogues.

Tobias Schaeffterمشاهده پروفایل

استاد

• Biomedical Imaging
• Magnetic Resonance Imaging (MRI)
• Biomedical Engineering
• +۴ مورد دیگر

Tobias Schaeffter is a Professor of Biomedical Imaging at Technische Universität Berlin and Head of the Medical Physics and Metrological Information Technology division at the National Metrology Institute of Germany (PTB). His interdisciplinary career bridges engineering, medical imaging, and quantitative diagnostics. PhD in Biochemistry from University of Bremen (1993–1996) Former Head of Biomedical Engineering at King’s College London (2013–2015) Full Professor at King’s College London (2006–2015) His research focuses on quantitative biomedical imaging , particularly MRI techniques for measuring biophysical parameters like blood velocity and tissue stiffness. Recent work integrates deep learning and AI to enhance image reconstruction and motion correction. Selected trends from his 15 most recent articles include: Deep learning frameworks for radial MRI acceleration and U-Net segmentation in MR elastography. Development of quantitative MRI standards for comparative diagnostics and population studies . Advancements in respiratory motion correction and cardiac perfusion quantification using AI. Applications of MRF (Magnetic Resonance Fingerprinting) and golden ratio sampling in high-field MRI. Current collaborations span data science , clinical medicine , and industrial partners to standardize medical imaging data.