جست‌وجوی استاد و پژوهشگر

Latifat Cabirouمشاهده پروفایل

استادیار

• Cultural Psychology
• Mental Health
• Acculturation
• +۴ مورد دیگر

Dr. Latifat Cabirou serves as Assistant Professor in the Department of Special Education, Rehabilitation, and Counseling at Auburn University's College of Education, a position held since 2021 following a Visiting Assistant Professor appointment (2020-2021). Her office is located in Haley Center 2060 with contact email loc0005@auburn.edu . Her academic credentials include: Ph.D. in Counseling Psychology, Loyola University Chicago M.A. in Clinical Psychology, Benedictine University Research centers on cultural experiences of racial/ethnic minorities and immigrants, with emphasis on acculturation processes , racial/ethnic identity development , socialization practices , and mental health literacy . This work bridges cultural psychology and clinical practice to address mental health disparities in immigrant communities through mixed-methods approaches. Recent publications (2019-2023) reveal consistent focus on cultural adaptation mechanisms, with dominant themes including acculturation-enculturation dynamics , racial/ethnic identity intersections , and mental health correlates among Asian American and Black African immigrants . Methodologically, her work employs meta-analysis, content analysis, and preliminary investigations to advance understanding of immigrant psychological adaptation. No scientific awards were documented in available materials. Information regarding student advising, grant funding, and laboratory affiliations was not specified in the provided texts.

Paul Midgleyمشاهده پروفایل

استاد

• Electron Microscopy
• 3D Imaging
• Nanomaterials
• +۴ مورد دیگر

Paul Midgley is the Professor of Materials Science at the University of Cambridge , affiliated with the Department of Materials Science & Metallurgy . His research focuses on advancing electron microscopy techniques for nanoscale structural analysis. BSc, MSc, PhD from the University of Bristol Research Interests: Development of 3D electron tomography, precession electron diffraction (PED), and multi-dimensional imaging techniques to study materials at atomic and nanoscale resolutions. Applications span semiconductor nanowires, catalysts, pharmaceuticals, and metal-organic frameworks (MOFs). Notable Trends: Recent work emphasizes nanoscale heterogeneities in halide perovskites, mechanochemical amorphisation of MOFs, and structural analysis of pharmaceutical formulations using 3D electron diffraction. Collaborations integrate machine learning and advanced reconstruction algorithms. Scientific Awards: Fellow of the Royal Society (FRS) Honorary Fellow of the Royal Microscopical Society (HonFRMS) MAE (Materials Ageing and Environment) Award Labs & Teams: Leads the Electron Microscopy Group at Cambridge. Research involves dual beam SEM-FIB, EDX, and EBSD techniques for mesoscale tomography. Collaborates with institutions in the UK, Europe, and globally.

Arno Onkenمشاهده پروفایل

استادیار

• Data Science
• Machine Learning
• Computational Neuroscience
• +۷ مورد دیگر

Dr. Arno Onken is a Lecturer (Assistant Professor) in Data Science for Life Sciences at the School of Informatics, University of Edinburgh, where he is also affiliated with the Institute for Adaptive and Neural Computation. He leads a research group focused on developing machine learning and statistical methods for modeling neural activity and analyzing large-scale neuroscience data. His work bridges artificial intelligence and computational neuroscience. His research interests lie at the intersection of machine learning, statistics, and neuroscience. He develops flexible probabilistic models such as copulas and Gaussian processes, deep learning architectures like Vision Transformers for brain activity prediction, and matrix/tensor factorization techniques for dimensionality reduction in neural datasets. His group aims to uncover interpretable structure in complex neural recordings and understand how behavior and cognition are encoded in population activity. The recent publications reflect a strong trend in combining modern deep learning with classical statistical modeling to analyze large-scale neural recordings. His work spans from foundational methods in copula modeling and information theory to applications in predicting visual cortex responses and modeling brainstem-hippocampus interactions across sleep states. The research has been published in top venues including NeurIPS, CVPR, eLife, and PLoS Computational Biology. Dr. Onken actively supervises PhD students and has developed several open-source scientific software packages, including the Mixed Vine Toolbox and Population Spike Train Factorization Toolbox. He teaches core courses in Machine Learning and Pattern Recognition and Data Mining and Exploration at the University of Edinburgh.

Matt C. Howardمشاهده پروفایل

دانشیار

• statistics and methodology
• health and well-being
• personality and individual differences
• +۳ مورد دیگر

Dr. Matt C. Howard is an Associate Professor at the University of South Alabama , specifically in the Mitchell College of Business under the Department of Marketing, Supply Chain Management, and Analytics . He also serves as the Interim Chair for his department. Ph.D. and M.S. in Industrial-Organizational Psychology from Pennsylvania State University B.S. in Psychology and B.A. in English from Virginia Tech Dr. Howard’s research focuses on statistics and methodology , health and well-being , personality and individual differences , and technology-enhanced training and development . His work often involves developing psychological scales and measurement tools for workplace behavior, such as the Workplace Social Courage Scale (WSCS) and a multidimensional persistence measure . These tools have been published in journals like the Journal of Business and Psychology and Personality and Individual Differences . He serves on the editorial boards of several journals, including Human Resource Management and Journal of Health Psychology . Notable scientific recognitions include being named an Association for Psychological Science Rising Star and appearing on the Clarivate Highly Cited List . He also acknowledges other unspecified awards and recognitions. For direct inquiries, Dr. Howard can be reached at mhoward@southalabama.edu or MHoward@SouthAlabama.edu .

Vagelis Papalexakisمشاهده پروفایل

دانشیار

• Data Science
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Dr. Vagelis Papalexakis is an Associate Professor and Ross Family Chair in the Computer Science & Engineering Department at the University of California, Riverside. His research focuses on data science, machine learning, and tensor methods, with applications in multi-aspect/multi-modal data analysis. He holds a Ph.D. from Carnegie Mellon University and a Diploma/M.Sc. from the Technical University of Crete. Affiliations: Ross Family Chair, Bourns College of Engineering, UCR Education: Ph.D. in Computer Science, Carnegie Mellon University M.Sc./Diploma in Electronic & Computer Engineering, Technical University of Crete His work emphasizes interpretable insights from complex datasets, including tensor-based defenses against adversarial attacks, graph representation learning, and scalable algorithms for high-dimensional data. Notable awards include the NSF CAREER Award (2021), IEEE DSAA Next Generation Award (2021), and ICDM Tao Li Award (2022). Grants include NSF funding for railway safety (CISE MSI: RPEP CPS), USDOT transportation research, and NVIDIA GPU grants. He leads projects in AI ethics, misinformation detection, and gravitational wave analysis. His lab collaborates with industry (e.g., Cisco, Instacart) and national labs (e.g., Lawrence Livermore).

Robert D. Zettleمشاهده پروفایل

استاد

• Contextual Behavioral Science
• Acceptance and Commitment Therapy
• Clinical Psychology
• +۴ مورد دیگر

Robert D. Zettle is a Professor of Psychology in the Clinical-Community Psychology Program at Fairmount College of Liberal Arts and Sciences, Wichita State University. He directs the Contextual Behavioral Science Lab and teaches Abnormal Psychology, Cognitive Behavioral Therapy, and Ethical and Professional Issues in Clinical Psychology. Dr. Zettle's educational background includes: Ph.D. in Psychology from University of North Carolina-Greensboro (1984) M.A. in Psychology from Bucknell University (1976) B.A. in Psychology from Wilkes College (1974) His research centers on Contextual Behavioral Science , examining how languaging and verbal behavior contribute to human suffering. Key areas include: Developing measures of psychological flexibility and self-as-context Experimental manipulation of processes in anxiety and mood disorders Comparing traditional CBT with Acceptance and Commitment Therapy (ACT) for depression Investigating mechanisms like defusion and acceptance in ACT Current projects focus on dissociative symptom induction, mood-enhancing versus value-congruent behavioral activation, and client treatment preferences in spider fear interventions. Dr. Zettle's recent publications (2019-2025) reveal a strong emphasis on self-as-context measurement , cross-cultural adaptations of ACT tools, and depression relapse prevention . His work increasingly integrates attention bias modification with ACT and explores client preference dynamics, while expanding applications to university counseling centers and international contexts. He mentors graduate students including Nakisha Carrasquillo, Angela Cathey, Suzanne Gird, Angie Hardage-Bundy, Sarah Staats, and Jeff Swails. His research is supported by ongoing projects in the Contextual Behavioral Science Lab investigating core ACT processes and clinical applications. The Contextual Behavioral Science Lab, directed by Dr. Zettle, maintains a collaborative team environment focused on both experimental psychopathology and clinical treatment development. Current work spans measurement validation, interoceptive exposure techniques, and comparative treatment studies for depression and anxiety disorders.

• Pain Management
• Opioid Therapy
• Substance Abuse
• +۳ مورد دیگر

Maryam Kazemitabar is an Associate Research Scientist in the Department of Internal Medicine at Yale University's School of Medicine. She holds a Ph.D. in Psychometrics from the University of Tehran (2020). Her work bridges research and clinical practice to improve patient outcomes in pain management, opioid therapy, and substance abuse. She collaborates with multidisciplinary teams to develop evidence-based interventions, leveraging her expertise in psychometric evaluation. Education: Ph.D. in Psychometrics (Measurement and Evaluation), University of Tehran, 2020 Research Interests: Pain management strategies and opioid-related risks Substance use disorders and comorbid mental health conditions Psychometric validation of health assessment tools Health equity in marginalized populations Research Trends: Recent work focuses on opioid overdose epidemiology, disparities in healthcare for migrant populations, and psychometric rigor in cross-cultural mental health measurement. Key methodologies include latent class analysis, scale validation, and mixed-methods approaches. Advising & Grants: While specific grants are not listed, her collaborative projects imply institutional and federal funding support. No formal advisees are documented here.

Jason M. Robertsمشاهده پروفایل

استاد

• American political institutions
• U.S. Congress
• congressional elections
• +۱ مورد دیگر

Jason M. Roberts is a Professor of Political Science at the University of North Carolina at Chapel Hill, specializing in American political institutions with an emphasis on the U.S. Congress. He maintains an office in Hamilton Hall and communicates via jroberts@unc.edu. His academic credentials include: B.S. in Political Science from the University of North Alabama (1998) M.A. in Political Science from Purdue University (2000) Ph.D. from Washington University in St. Louis (2005) Professor Roberts' research centers on congressional procedures, electoral systems, and institutional dynamics within the U.S. Congress. Current projects investigate interpersonal relationships among legislators and election administration practices in North Carolina, building on prior work like his 2020 book The Politics of Ballot Design . His scholarship consistently bridges historical analysis and contemporary political challenges. Analysis of his 15 most recent publications (2022-2006) reveals enduring focus on congressional institutionalization, party strategy in lawmaking, and electoral competition. Recurring themes include the impact of procedural rules on legislative outcomes, historical evolution of congressional practices, and methodological rigor in studying roll call voting—demonstrating both longitudinal depth and methodological sophistication. No scientific awards or honors were documented in the source materials. His teaching portfolio spans undergraduate courses including American Democracy in Changing Times and The U.S. Congress, alongside graduate seminars in American Politics and Congressional studies. While student advising details were unspecified, his extensive publication record and active research agenda suggest ongoing mentorship of emerging scholars.

Marc Olanoمشاهده پروفایل

دانشیار

• Computer Graphics
• Real-Time Rendering
• Graphics Hardware
• +۴ مورد دیگر

Marc Olano is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC), and serves as the Associate Dean of Academic Programs and Learning in the College of Engineering and Information Technology. He leads the Computer Science Game Development Track and co-directs the VANGOGH lab. His research focuses on interactive 3D computer graphics, programmable shading, graphics hardware, and surface appearance modeling, with contributions to foundational graphics technologies like procedural shading and normal mapping. Research Interests: Olano’s work spans real-time rendering, GPU algorithms, texture compression, and procedural shading. He has pioneered techniques such as LEAN mapping and variable bitrate texture compression, significantly impacting game development and real-time graphics. His research often explores the intersection of hardware capabilities and algorithmic innovation, with applications in medical visualization, visualization of scientific data, and haptic interaction. Key Contributions: Olano’s accomplishments include pioneering procedural shading on graphics hardware, developing homogeneous rendering techniques, and advancing normal mapping. His work on GPU-based curvature estimation and BT volumes for volume rendering exemplifies his focus on leveraging GPU parallelism for real-time visualization challenges. He has also contributed to standards in shading languages and GPU programming. Teaching & Mentorship: Olano teaches courses in computer graphics, game development, and advanced computer architecture. He mentors students in independent studies and has advised numerous MS theses exploring topics like GPU random number generation, volume rendering, and soft shadow algorithms. His students’ work often bridges theoretical research and practical GPU implementations. Labs & Projects: The VANGOGH lab under his co-direction focuses on advanced visualization and graphics research, including real-time rendering techniques, GPU algorithms, and interactive data visualization. His research collaborations span industry partners like Firaxis Games, contributing to titles such as Civilization V through texture compression innovations.

• Computational Fluid Dynamics
• Discontinuous Galerkin Methods
• Finite Volume Methods
• +۶ مورد دیگر

Michael Dumbser is a Full Professor at the University of Trento's Department of Civil, Environmental and Mechanical Engineering. His research focuses on computational fluid dynamics, numerical methods for hyperbolic conservation laws, and high-performance computing. He specializes in developing structure-preserving numerical schemes such as discontinuous Galerkin and finite volume methods for continuum mechanics, relativistic fluid dynamics, and multiphase flows. Teaching responsibilities include courses like Calcolo numerico e programmazione , High-Performance Computing for Multi-Functional Metamaterials , and Metodi numerici per l'ambiente . His work emphasizes thermodynamically compatible formulations and adaptive numerical methods for complex physical systems. Recent research trends involve hyperbolic reformulations of classical models (e.g., Navier-Stokes-Korteweg, Einstein equations), staggered semi-implicit schemes for incompressible flows, and GPU-accelerated algorithms. His publications span topics from geophysical fluid dynamics to relativistic astrophysics, with a focus on maintaining physical conservation principles in numerical implementations. No scientific awards are explicitly listed in the provided information. His advising record is not detailed here, though his courses suggest involvement in student mentorship. Research collaborations include projects on metamaterials and computational geophysics. Current initiatives include developing unified models for earthquake rupture dynamics, non-Newtonian fluid simulations, and adaptive mesh refinement techniques. His lab work involves high-performance computing frameworks like ExaHyPE for large-scale wave propagation studies.

Christian Liebscherمشاهده پروفایل

استاد

• Advanced Transmission Electron Microscopy
• Materials Science
• Energy-Related Materials
• +۶ مورد دیگر

Prof. Christian Liebscher is a Professor of Advanced Transmission Electron Microscopy at the Ruhr University Bochum , affiliated with the Faculty of Physics and Astronomy and the Research Center Future Energy Materials and Systems (RC FEMS). His work focuses on developing cutting-edge TEM techniques to understand energy-related materials' atomic-scale structure-functionality relationships. He combines aberration-corrected scanning TEM (STEM), 4D-STEM, and in-situ microscopy with machine learning to analyze complex material datasets. Education and Career: 2000–2006: Study of Materials Science at the University of Bayreuth. 2006–2010: PhD at the University of Bayreuth (summa cum laude) with a thesis on phase and dislocation analysis in superalloys. 2011–2014: Postdoc at the University of California, Berkeley, and the National Center for Electron Microscopy (Lawrence Berkeley National Laboratory). 2014–2015: Staff scientist at the University of Duisburg-Essen. 2015–2024: Group leader at the Max Planck Institute for Sustainable Materials in Düsseldorf. Research Interests: Prof. Liebscher’s research bridges microscopy innovation and materials understanding. He emphasizes atomic-scale characterization of interfaces, defects, and grain boundaries in metals and alloys using advanced STEM and 4D-STEM. His work addresses how structural features—like segregation, strain, and phase transitions—impact material properties. He also pioneers machine learning tools to automate data analysis from microscopy and tomography, advancing materials dataspaces. Key topics include energy materials (e.g., PEM fuel cells), high-entropy alloys, and nanomaterials for applications like semiconductors and electromagnetic absorption. Scientific Contributions: His publications highlight trends in grain boundary phase transitions, microstructure-property correlations, and integration of AI into microscopy. For example, recent work explores how grain boundary complexions affect mechanical strength in alloys and how in-situ TEM reveals deformation mechanisms under realistic conditions. He has contributed significantly to methodologies like scanning precession electron diffraction tomography and unsupervised machine learning for atomic-resolution datasets. Labs and Collaborations: Prof. Liebscher leads the Advanced Transmission Electron Microscopy group at RUB, building on his previous leadership at the Max Planck Institute. His lab collaborates with institutions like the Lawrence Berkeley National Laboratory and integrates interdisciplinary approaches combining experimental microscopy with computational modeling.

Joel Talcottمشاهده پروفایل

استاد

• Developmental Dyslexia
• Reading Acquisition
• Cognitive Neuroscience
• +۳ مورد دیگر

Joel Talcott is Professor of Developmental Cognitive Neuroscience at Aston University, specializing in dyslexia and language disorders. His research examines genetic, neural, and cognitive foundations of reading development using methods including neuroimaging, genetic analysis, and large-scale behavioral assessment. Leadership Roles: Vice President of the British Dyslexia Association (2010-present), Fellow of the Royal Society of Arts (2012), and IBRO-UNESCO Science of Learning Fellow (2020). Editorial responsibilities include service for Dyslexia and Annals of Dyslexia journals. Research: Leads the Aston Brain Centre's investigations into neurocognitive trajectories of reading skills. Current projects include the ECCaToN transdiagnostic protocol for neurodevelopmental characterization and analysis of literacy development datasets (LIBS Dataset). Awards: IBRO-UNESCO Science of Learning Fellow (2020) Fellow of the Royal Society of Arts (2012) Honorary Vice-President, British Dyslexia Association (2010)

Steven Paul Reiseمشاهده پروفایل

استاد پژوهشی

• Quantitative Psychology
• Latent Variable Modeling
• Structural Equation Modeling
• +۳ مورد دیگر

Steven Paul Reise is a Research Professor in Quantitative Psychology at the University of California, Los Angeles (UCLA), where he has been a faculty member since 1998. He co-directs the Advanced Quantitative Methods training program, supporting graduate students in measurement, latent variable modeling, and modern experimental design. Dr. Reise earned his Ph.D. in Psychology from the University of Minnesota (1990), mentored by IRT pioneer David Weiss and personality researcher Auke Tellegen. Dr. Reise specializes in applying latent variable measurement models—including Structural Equation Modeling (SEM) and Item Response Theory (IRT)—to personality, psychopathology, and health outcomes research. His methodological work focuses on hierarchical models, MIMIC modeling, person-fit statistics, and bifactor modeling. He has been recognized with prestigious awards, including the Raymond B. Cattell Award (1998), UCLA Psychology Department Distinguished Teaching Award (2008), and University of California Campus-Wide Distinguished Teaching Award. His recent publications explore multidimensionality in SEM, bifactor modeling, person-fit indices, and applications to psychopathology and health outcomes. Dr. Reise collaborates on projects spanning gene-to-phenotype modeling, impulsivity, and advanced psychometrics. Scientific Awards : Raymond B. Cattell Award (1998), UCLA Psychology Teaching Award (2008), UC Campus-Wide Teaching Award, Outstanding Paper of the Year (2012).

Chun Wangمشاهده پروفایل

استاد

• Quantitative Research Methods
• Item Response Theory (IRT)
• Computerized Adaptive Testing (CAT)
• +۳ مورد دیگر

Chun Wang is a Professor in the Department of Measurement & Statistics at the University of Washington's College of Education. His research focuses on advancing quantitative methods in educational and psychological measurement, with expertise in item response theory (IRT), computerized adaptive testing (CAT), and cognitive diagnostic modeling. He holds affiliate faculty status at the Center for Statistics and the Social Sciences. Education: B.S. in Psychology, Peking University (China) M.S. and Ph.D. in Quantitative Psychology, University of Illinois at Urbana-Champaign Research Interests: Development and validation of multidimensional/mixture IRT models Computerized adaptive testing optimization Cognitive diagnostic modeling for classroom applications Health measurement and bias detection in assessments Recent Trends in Articles: His work bridges statistical innovation with practical applications, emphasizing fairness and efficiency in assessments. Notable areas include: - Healthcare : Predictive models for discharge disposition and functional outcomes - Education Technology : Adaptive learning systems and diagnostic feedback mechanisms - Methodology : Bias detection (DIF), Bayesian estimation techniques, and computational efficiency Scientific Awards : Includes the Anne Anastasi Award (2020), McKnight Presidential Fellowship (2017), and multiple best reviewer recognitions from leading psychometrics journals. Advising & Grants: Supervised students including Xiao J., Zhu R., and Lu J.* in high-impact projects. Co-led a $10M NIH grant (AmplifyGAIN Center) to advance Gen AI in STEM education. Published extensively in Psychometrika , Journal of Educational and Behavioral Statistics , and other top outlets. Labs/Teams: Directs the Pmetrics Lab ( https://sites.uw.edu/pmetrics/ ), collaborating on cutting-edge measurement tools for education and healthcare.

Prateep Nayakمشاهده پروفایل

استاد

• Political Ecology
• Environmental Justice
• Social-Ecological Systems
• +۷ مورد دیگر

Prateep Nayak is a Professor at the School of Environment, Enterprise and Development within the University of Waterloo. His academic focus combines political science, environmental studies, and international development through transdisciplinary research on human-environment connections. With expertise in commons governance, social-ecological resilience, environmental justice, and political ecology, he has taught courses like INDEV 100: Introduction to International Development SUSM 675: Governing the Commons INDEV 617: Environmental Change and Governance He has received prestigious awards including the Trudeau Scholarship, Harvard Giorgio Ruffolo Fellowship, Canada's Governor General Academic Gold Medal, and SSHRC Banting Fellowship. Professor Nayak's research explores social-ecological systems, emphasizing vulnerability-to-viability transitions in small-scale fisheries, gender dynamics in dried fish value chains, and multidimensional justice in coastal governance. His Google Scholar publications since 2017 highlight Asia-Africa comparative studies, marine protected areas, and policy frameworks for adaptive management. Article keywords reveal engagement with climate resilience, equity in resource access, and institutional pluralism in governance systems. Scientific awards include Trudeau Scholar Harvard Giorgio Ruffolo Fellow in Sustainability Science Canada's Governor General Academic Gold Medal SSHRC Banting Fellow His fieldwork experience includes development projects in India focusing on community-based governance of land, water, and forests at the research-implementation-policy interface. Current teaching aligns with his expertise in international development and environmental governance, while historical publications show long-term engagement with coastal systems analysis and regime shifts.