جست‌وجوی استاد و پژوهشگر

Timothy W. Koethمشاهده پروفایل

استادیار

• Radiation Science
• Nuclear Technology
• Accelerator Physics
• +۳ مورد دیگر

Timothy W. Koeth is an Assistant Professor at the University of Maryland, affiliated with the Materials Science and Engineering Department and the Institute for Physical Science and Technology (IPST). His research focuses on radiation and nuclear science, including neutron generation/detection, accelerator physics, and energy storage materials. He explores beam optics in electron/ion accelerators and develops radiation-hard devices for advanced applications. His work spans experimental and applied physics, with contributions to fusion energy research and high-power RF sources. Notable research areas include materials characterization under extreme conditions and novel detector technologies. He collaborates on projects involving nuclear fusion, plasma physics, and advanced material systems. Published articles address topics like insulating materials for centrifugal mirrors, jet physics in heavy-ion collisions, and precision measurements of W/Z bosons. His studies often intersect with CMS experiment data, emphasizing detector performance and high-energy particle interactions.

Lianming Wangمشاهده پروفایل

دانشیار

• Survival Analysis
• Longitudinal Data
• Bayesian Methods
• +۲ مورد دیگر

Lianming Wang is an Associate Professor in the Department of Statistics at the University of South Carolina. His research develops statistical methods for biomedical data, particularly survival and longitudinal analyses. Primary research areas include Bayesian approaches for censored data, frailty models, and high-dimensional biostatistical applications. Recent work features genomic co-expression detection and flexible parametric modeling of survival data. He has advised 13+ PhD students and secured NIH funding for projects on cancer prevention and infectious disease modeling.

Laura Amoمشاهده پروفایل

استادیار

• Employee cyberbehavior
• Consumer engagement with gamification
• Cybersecurity awareness, engagement and self-efficacy
• +۲ مورد دیگر

Laura Amo is an Assistant Professor in the Department of Management Science and Systems at the School of Management, University at Buffalo. Her academic journey includes a PhD and MA from the University at Buffalo and a BA from Canisius College. Education: PhD, University at Buffalo MA, University at Buffalo BA, Canisius College Dr. Amo's research focuses on cybersecurity, particularly employee cyberbehavior, consumer engagement through gamification, and cybersecurity awareness and self-efficacy. She also investigates policy analysis in educational contexts and eHealth disparities. Her work bridges information systems, psychology, and public policy to address critical gaps in digital engagement and security. Her recent publications (2013-2016) reveal a strong interdisciplinary approach, combining cybersecurity with education and health. Key themes include gender disparities in cybersecurity, the impact of high-stakes testing, and meta-analyses of teacher efficacy. This body of work demonstrates her commitment to using statistical methods to solve real-world problems in information systems and policy. Funded Projects: 2018-2019: National Security Agency and National Science Foundation ($94,519.27) - Co-PI for GenCyber 2018 2018-2019: Spencer Foundation ($43,260) - Co-PI for 'School Security: Identifying and Addressing Sources of Inequity' 2015-2017: National Science Foundation ($199,759) - Co-PI for 'SaTC EDU Collaborative: Cybersecurity for Middle School students at Museums' 2015-2016: National Science Foundation & National Security Agency, GenCyber ($86,393) - Senior Personnel Dr. Amo teaches courses in Introductory and Advanced Statistics for Decision-Making in Business, Multilevel Statistical Modeling, and Research with Large-Scale Databases. Her research projects often involve collaborations with national agencies and foundations, focusing on cybersecurity education and policy.

Hayley Mountfordمشاهده پروفایل

پژوهشگر

• Genetics
• Developmental Disorders
• Language Acquisition
• +۳ مورد دیگر

Hayley Mountford is a Postdoctoral Research Assistant at the University of Edinburgh, affiliated with the School of Philosophy, Psychology and Language Sciences and the Psychology Department. Her research focuses on the genetics of reading and language disorders, including dyslexia and developmental language disorder. She holds a PhD and a BSc (Hons) in relevant fields. Her work integrates molecular genetics, neurodevelopmental studies, and epidemiological approaches to uncover genetic and environmental factors influencing language acquisition and neurodevelopmental conditions. Key research interests include genetic neurodevelopmental clustering, the molecular basis of speech disorders, and the impact of genetic variants on brain connectivity and structure. She has contributed to studies on epigenetic associations, genome-wide association analyses, and longitudinal measures of reading ability. Her research often explores interactions between genetic factors and environmental exposures, such as prenatal smoke effects on language development. Mountford's publications span genetic studies of motor coordination, mitochondrial disorders, and population genetics. While no scientific awards are explicitly mentioned, her extensive publication record reflects significant contributions to developmental genetics and language-related research. Collaborative work includes investigations into neurodevelopmental disorders such as autism spectrum disorder and the molecular mechanisms underlying specific genetic mutations.

• Lighting Design
• Environmental Psychology
• Human-Centered Lighting
• +۳ مورد دیگر

Kim Do is a Visiting Professor at the Laboratory of Functional and Metabolic Imaging (LIFMET) within the School of Basic Sciences (SB) at École Polytechnique Fédérale de Lausanne (EPFL). His research focuses on the intersection of lighting design, environmental psychology, and human well-being. He leads studies on lighting quality in diverse environments, including healthcare facilities, workplaces, schools, and cultural heritage sites, emphasizing cross-cultural perspectives and occupant-centric approaches. Key research interests include: Lighting's impact on emotional well-being and cognitive function Daylight analysis and glare mitigation strategies Occupant archetype clustering for personalized lighting solutions Cross-cultural comparisons of lighting preferences between South Korea, the Netherlands, and the UK Recent work explores methodologies for optimizing indoor environmental quality (IEQ) in schools and hospitals through participatory design workshops and focus group analyses. His studies often integrate psychological models linking lighting conditions to health outcomes, as demonstrated in projects like the Changdeokgung Palace moonlight tours and London's urban night-time illumination. Kim Do collaborates with interdisciplinary teams across EPFL's LIFMET lab and international institutions, contributing to standards for workplace lighting and public space design. His research bridges engineering, sociology, and psychology to create human-centered lighting solutions.

• Epigenetics
• Genomics
• Bioinformatics
• +۳ مورد دیگر

Dr Hermanus Draisma is a Research Fellow in Statistical Multi-Omics Modelling and Analysis at the University of Surrey, affiliated with the School of Biosciences under the Faculty of Health and Medical Sciences. His career includes postdoctoral roles at Imperial College London (2017-2019), Vrije Universiteit Amsterdam, and Leiden University Medical Center. He holds a PhD in Biomedical Sciences (2010) from Leiden University and a Master's in Biomedical Sciences (2005), both from Leiden University. His research focuses on developing statistical methods for epigenome- and genome-wide association analyses, leveraging phenotypic correlations to detect genotype-phenotype relationships. Key areas include DNA methylation, metabolomics, and bioinformatics-driven approaches to genetic and epigenetic data analysis. His work bridges computational biology with clinical applications, particularly in understanding heritability and disease mechanisms. Dr Draisma has contributed to projects funded by the Wellcome Trust, collaborating extensively with groups such as Dr. Inga Prokopenko and Prof. Philippe Froguel. His expertise spans metabolomic data analysis in twin studies, RNA-seq methodologies, and multivariate longitudinal analysis of epigenetic profiles.

Marieke Timmermanمشاهده پروفایل

استاد

• Multivariate Data Analysis
• Psychometrics
• Statistics & Probability
• +۴ مورد دیگر

Marieke Timmerman is a Professor of Multivariate Data Analysis at the University of Groningen, affiliated with the Faculty of Behavioural and Social Sciences and the Department of Psychometrics & Statistics. Her research focuses on explaining complex psychological data through concise models, particularly in multivariate and longitudinal analyses, with emphasis on latent variable models, test construction, and data reduction techniques. She chairs the Department of Psychometrics & Statistics and is a member of COTAN (Collaborative Organization for Test Norming). Her work spans psychometrics, statistics, and applied psychological testing, with notable contributions to continuous test norming using GAMLSS and multilevel models. Key research areas include cognitive functioning in neurological disorders, emotion dynamics, and recovery trajectories in psychosis. Publications highlight methodological advancements in norming psychological tests, dynamic clustering of longitudinal data, and applications in clinical populations. Awards include the 2017 Kowalski Prize and a 2023 grant for norming research. She supervises PhD students and teaches advanced methods like multilevel analysis and repeated measures. Her ancillary roles include statistical consulting and board memberships, reflecting her interdisciplinary impact. Collaborations bridge clinical, developmental, and computational domains, addressing practical challenges in psychological assessment and intervention.

• Perfectionism
• Statistics Analysis
• Alcohol Use
• +۵ مورد دیگر

Sean Mackinnon is a Senior Instructor (part-time) in the Department of Psychology and Neuroscience at Dalhousie University, Canada. He holds academic roles in teaching statistical methods, personality psychology, and research design. His research focuses on applied statistical analysis, perfectionism as a predictor of psychopathology, and alcohol misuse. He earned his BA (Cape Breton U.), MA (Wilfrid Laurier U.), and PhD (Dalhousie U.) in Psychology. Key research areas include perfectionism’s role in mental health, statistics education innovations, and cross-cultural drinking motives. He has published extensively on personality traits, diary studies of drinking behaviors, and methodological topics like response-order effects in self-reports. His datasets (e.g., on speed-dating studies, pain in youth arthritis) are publicly archived for secondary research. Teaching responsibilities include courses like PSYO 2501 (Statistical Methods I) and PSYO 6003 (Multivariate Methods). He emphasizes open science practices, publishing tools like tutorials for longitudinal analyses using R’s lavaan package. His work often bridges statistical methodology and psychological theory, with a focus on improving reproducibility and reducing bias in research design.

Kai Zhaoمشاهده پروفایل

پژوهشگر ارشد

• Time Series Analysis
• Machine Learning
• Data Mining
• +۳ مورد دیگر

Kai Zhao is a Research Fellow in the Department of Computer Science at the Technical Faculty of IT and Design, Aalborg University, Denmark, specializing in time-series analytics and machine learning applications. Research Interests: Time Series Analysis Machine Learning Data Mining Contrastive Learning Graph Neural Networks Anomaly Detection His recent publications (2023-2025) demonstrate a cohesive focus on graph-based and contrastive learning techniques for time-series challenges, particularly addressing few-shot scenarios, multivariate forecasting, and anomaly detection in IoT contexts. Methodological innovations include dynamic graph modeling and generative contrastive frameworks. Scientific Awards: No awards mentioned in available documentation. As Principal Investigator, he led the project 'Time Series Analyse with Few-shot Learning' (2022-2023), advancing few-shot learning applications for time-series analysis. His collaborative network spans multiple institutions, evidenced by co-authorships with researchers from Aalborg University and international partners. His research integrates theoretical frameworks with practical implementations, showing strong emphasis on robustness and adaptability in real-world time-series applications.

• Mathematics Education
• Data Science
• Computer Science
• +۳ مورد دیگر

Dr. rer. nat. Paul Wolf is an Acting Professor at Stralsund University of Applied Sciences, specializing in Mathematics, Data Science, and Computer Science. He teaches courses such as Mathematics 1/2 for various programs, statistical foundations for MIMEB, programming with Python/R, and multivariate statistics. His research focuses on university didactics in mathematics through the cross-faculty HoDiMa project and statistical consulting for academic analyses. He also contributes to the META project at the University of Augsburg. Education: Holds a Dr. rer. nat. (PhD in Natural Sciences). Teaching & Research: Leads tutor training programs and offers university didactics workshops. Provides statistical consultation services and is actively involved in curriculum development for STEM and business programs. Contact: Reachable via email at paul.wolf@hochschule-stralsund.de or room 103, House 1. Consultations are arranged via email.

Ole Andreassenمشاهده پروفایل

استاد

• Psychiatric Genetics
• Schizophrenia Research
• Bipolar Disorder
• +۵ مورد دیگر

Ole Andreassen is a Professor at the Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, where he leads significant research initiatives at the intersection of psychiatric genetics, neuroimmunology, and brain imaging. His work primarily focuses on severe mental disorders, particularly schizophrenia and bipolar disorder, examining their genetic architecture, inflammatory components, and brain structural correlates. His research interests span psychiatric genetics, neuroimmunology, and brain imaging, with particular emphasis on understanding how immune system dysregulation contributes to the pathophysiology of severe mental illnesses. He has pioneered approaches examining composite immune marker scores, inflammasome activation, and the relationship between inflammatory processes and cognitive impairment in mental disorders. His work frequently employs large-scale genetic analyses, longitudinal study designs, and multimodal assessment strategies. Analysis of his recent publications reveals consistent focus on the immune-genetic interface in mental illness, with growing attention to longitudinal trajectories, sex differences, and transdiagnostic approaches. His research demonstrates how inflammatory markers interact with genetic risk factors to influence clinical presentation and course of severe mental disorders. Dr. Andreassen has received significant research funding supporting his investigations into the biological mechanisms underlying severe mental illnesses, though specific awards aren't detailed in the available information. His work has established important connections between immune system function and psychiatric conditions. His laboratory utilizes advanced methodologies including genome-wide association studies, inflammatory biomarker profiling, brain imaging analysis, and longitudinal clinical assessments to investigate the complex interplay between genetic, immune, and neural factors in severe mental illness. Current research directions appear to be focusing on inflammatory subgroups, treatment response prediction, and developmental aspects of immune-brain interactions in mental disorders.

• Essential Oils
• Phytochemistry
• Pharmacology
• +۳ مورد دیگر

Prof. Betül Demirci is a distinguished faculty member at Anadolu University's Faculty of Pharmacy, Department of Pharmaceutical Sciences, where she has held the rank of Professor since 2010. Her academic journey at Anadolu University includes roles as Associate Professor (2005-2010), Assistant Professor (1999-2005), and Research Assistant (1992-1999). Her educational background comprises: Doctorate in Pharmacognosy from Anadolu University (1999) Postgraduate degree in Pharmacognosy from Anadolu University (1994) Undergraduate degree in Pharmacy from Anadolu University (1992) Prof. Demirci's research focuses extensively on essential oils , phytochemistry , and biological activities of natural products . She investigates the antimicrobial, antiviral, and pharmacological properties of plant-derived compounds, with emphasis on endemic Turkish species. Her work bridges ethnopharmacology and modern drug discovery, particularly in validating traditional plant uses through chemical and bioactivity analyses. Her recent publications (2024-2025) demonstrate a consistent focus on: Chemical profiling of essential oils from diverse plant genera (Salvia, Melaleuca, Origanum, etc.) Evaluation of synergistic antimicrobial/antiviral effects Multivariate statistical analysis of phytochemical data Biological validation of traditional medicinal plants This reflects her interdisciplinary approach combining phytochemistry, microbiology, and data science. Prof. Demirci has advised 13 theses and contributed to 29 research projects. While specific grants are not detailed, her prolific output indicates sustained research funding. No explicit lab/team structures are described, but collaborations are evident in multi-author publications.

Stephen Swiftمشاهده پروفایل

عضو هیئت علمی

• Multivariate Time Series Analysis
• Heuristic Search
• Data Clustering
• +۴ مورد دیگر

Dr. Stephen Swift is a Reader in the School of Information Systems, Computing and Mathematics at Brunel University London within the College of Engineering, Design and Physical Sciences. His research spans multiple domains including bioinformatics, ophthalmology, and software engineering, with a focus on developing computational methods for analyzing complex data. B.Sc. in Mathematics and Computing from University of Kent M.Sc. in Artificial Intelligence from Cranfield University Ph.D. in Intelligent Data Analysis from Birkbeck College, University of London Dr. Swift's research centers on multivariate time series analysis, heuristic search algorithms, data clustering techniques, and evolutionary computation methods. His work applies these computational approaches to real-world problems in bioinformatics (particularly gene expression analysis), ophthalmology (glaucoma progression modeling), and software engineering (code quality metrics). His interdisciplinary research bridges computer science with medical and biological applications, developing novel algorithms for complex data analysis tasks. Analysis of Dr. Swift's recent publications reveals a strong focus on applying computational intelligence to healthcare challenges, particularly in diabetes management, glaucoma progression, and genetic disorders. His work consistently combines machine learning techniques with domain-specific knowledge to develop practical solutions for medical diagnostics and treatment personalization. The publications also demonstrate his continued interest in software engineering methodologies and computer vision applications. Dr. Swift has secured research funding from major UK research councils including EPSRC (Engineering and Physical Sciences Research Council) and BBSRC (Biotechnology and Biological Sciences Research Council), supporting projects such as 'Modelling Short Multivariate Time Series' and 'Analysing Virus Gene Expression Data to understand Regulatory Interactions.' His research has been conducted through collaborations with multiple institutions including University College London, Moorfields Eye Hospital, and Birkbeck College, demonstrating his ability to work across disciplinary boundaries to address complex scientific challenges.

Michael L. Andersonمشاهده پروفایل

استاد

• Philosophy of Neuroscience
• Theoretical Neuroscience
• Computational Neuroscience
• +۴ مورد دیگر

Michael L. Anderson is Professor in the Department of Philosophy within the Faculty of Arts & Humanities at Western University, and serves as Acting Director of the Rotman Institute of Philosophy. Holding the Rotman Canada Research Chair in Philosophy of Science, his work bridges philosophy, neuroscience, psychology, and computer science to develop novel frameworks for understanding brain organization and cognition. His educational background includes a B.S. from Notre Dame and a Ph.D. from Yale University. Key research contributions focus on the theory of neural reuse —the principle that brain regions are dynamically repurposed across cognitive tasks—and its implications for embodied cognition, brain evolution, and cognitive taxonomy. Anderson's publication trends reveal a sustained investigation into how evolutionarily older sensory-motor systems are coopted for higher cognition, with significant methodological innovations in analyzing functional brain diversity. His work spans theoretical neuroscience, philosophical analysis of cognitive architecture, and empirical studies of brain plasticity, consistently challenging modular views of brain organization. Rotman Canada Research Chair in Philosophy of Science Fellow at Center for Advanced Study in the Behavioral Sciences, Stanford University (2012-2013) As Acting Director of the Rotman Institute of Philosophy, Anderson leads interdisciplinary research initiatives connecting philosophy of science with empirical neuroscience. His collaborative work involves developing quantitative methods for mapping brain function and reforming psychological taxonomy through large-scale neuroimaging analyses.

• Social research techniques
• Self-identity
• Electoral studies
• +۴ مورد دیگر

Modesto Escobar Mercado serves as a University Professor in the Department of Sociology and Communication at the Faculty of Social Sciences, University of Salamanca. With 6 six-year terms of academic recognition, he maintains an active presence in both teaching and research. His office is located in room 402 and he can be contacted at modesto@usal.es or through his Twitter profile @modesto_escobar. Dr. Escobar's research program centers on methodological innovations in social sciences, with particular expertise in social research techniques, self-identity, and electoral studies. His work bridges advanced statistical methods with sociological theory, developing novel approaches to measuring social diversity, analyzing network structures in social phenomena, and assessing democratic quality through expert evaluations. He has made significant contributions to graphical and exploratory analysis techniques applied to social data. His publication record shows a clear evolution toward computational social science, with recent work emphasizing network analysis tools like the netCoin R Package. This trajectory reflects his commitment to advancing quantitative methodologies in sociology, moving from traditional statistical approaches to more sophisticated network-based analyses that capture complex social relationships and structures. As principal investigator of the Sociological Analysis Group at the University of Salamanca, Dr. Escobar leads research initiatives that integrate theoretical frameworks with cutting-edge analytical techniques. His teaching portfolio includes Measurement and Social Indicators, Multivariate Analysis Applied to Social Sciences, and Project Development, demonstrating his dedication to training students in rigorous methodological approaches essential for contemporary social research.