جست‌وجوی استاد و پژوهشگر

Shilin Zhaoمشاهده پروفایل

استادیار

• Artificial Intelligence in Digital Pathology
• Spatial Transcriptomics Analysis
• Kidney Disease Morphomics
• +۴ مورد دیگر

Shilin Zhao is an Assistant Professor of Biostatistics at Vanderbilt University Medical Center, specializing in artificial intelligence applications for digital pathology and multi-omics integration. His work bridges computational methodology development with clinical pathology to address challenges in kidney disease, gut microbiome research, and metabolic disorders. Education PhD in Bioinformatics, Shanghai Institutes for Biological Sciences Research Focus Dr. Zhao's research centers on AI-driven pathology and spatial omics , with primary emphasis on: Glomerular and kidney layer segmentation using cross-species data integration Foundation model assessment for cell nuclei analysis in renal histopathology Multi-omics approaches to colitis, atherosclerosis, and metabolic diseases Development of graph networks for spatial transcriptomics prediction His methodologies frequently combine deep learning with biostatistical rigor to translate computational insights into clinical pathology applications. Publication Trends Dr. Zhao's 2025 publications demonstrate intense focus on AI pathology tools (14/15 articles), particularly glomerular analysis and spatial transcriptomics. Key themes include cross-species model adaptation (GLAM), multi-level attention networks (MagNet), and clinical validation of AI foundation models in kidney pathology. His work consistently targets diagnostic precision through computational innovation. Scientific Recognition No specific awards or honors were documented in the provided materials. Academic Contributions While student advising details are unavailable, Dr. Zhao actively contributes to methodological advances in biostatistics through high-impact publications. His involvement in the KPIS 2024 challenge indicates leadership in establishing glomerular segmentation benchmarks for the pathology AI community. Research Environment As primary faculty in Vanderbilt's Department of Biostatistics, Dr. Zhao likely collaborates with institutional resources including the Vanderbilt Biostatistics Data Coordinating Center (VBDCC) and Vanderbilt Technologies for Advanced Genomics Analysis and Research Design (VANGARD), though specific affiliations aren't explicitly stated.

Wei Wuمشاهده پروفایل

استاد

• Clinical Psychology
• Quantitative Psychology
• Longitudinal Data Analysis
• +۳ مورد دیگر

Wei Wu is a Professor in the Department of Psychology at Indiana University, specializing in quantitative methodology for psychological research. His work bridges clinical applications with advanced statistical techniques, particularly in longitudinal study designs. His academic credentials include: Ph.D. in Quantitative Psychology from Arizona State University (2008) M.S. in Personality Psychology from East China Normal University (2003) B.Ed. in Special Education from East China Normal University (1997) Professor Wu's research focuses on developing and refining statistical methods for psychological inquiry, with emphasis on missing data handling, growth curve modeling, and model fit evaluation. His clinical psychology background informs applications in educational and developmental contexts, particularly regarding grade retention effects. Methodological rigor defines his contributions, advancing best practices for longitudinal data analysis in social sciences. Analysis of his publication record reveals consistent innovation in missing data techniques and experimental design optimization. His work demonstrates increasing sophistication in planned missing data approaches, with growing emphasis on computational efficiency and real-world applicability across psychology subfields. Recent publications integrate SEM and multilevel frameworks to solve complex modeling challenges. Professor Wu has secured substantial research funding through competitive grants: NSF grant ($422,900, 2011-2016) as PI for planned missing data designs in longitudinal research NIH grant ($1.7M, 2010-2014) as Statistical Consultant for resilience determinants study PCORI grant ($1.5M, 2013-2016) as Statistical Consultant for burnout impact research New Faculty General Fund ($8,000, 2010-2013) for model fit evaluation methods NICHD grant (2004-2008) as Research Assistant for grade retention study He actively mentors graduate researchers, with documented advisees including A. I. Carroll, P-Y. Chen, F. Jia, R. Kinai, F. Gu, P. R. Miller, and P. Pornprasermanit across multiple publications. While no formal lab structure is specified, his extensive grant collaborations indicate active participation in interdisciplinary research networks focused on methodological advancement.

Oleg Kitovمشاهده پروفایل

استادیار

• Time-series Econometrics
• Empirical Macroeconomics
• Income Distribution
• +۱ مورد دیگر

Oleg Kitov serves as an Assistant Teaching Professor and Robert Martin Fellow in Economics at Selwyn College, University of Cambridge, where he also acts as Convener of Undergraduate Admissions for the Faculty of Economics. His academic profile centers on rigorous econometric methodology applied to macroeconomic phenomena and distributional economics, with significant contributions to time-series analysis and income inequality research. Kitov's primary research domains include Time-series Econometrics, Empirical Macroeconomics, and Income Distribution and Inequality. His methodological innovations focus on structural break detection in linear models using multiplicative indicator saturation, generative modeling of age-income dynamics, and cross-national Phillips curve analysis. His work bridges theoretical econometrics with empirical applications, particularly examining inflation-unemployment relationships across diverse economies and modeling long-term trends in income distribution using historical datasets. His publication trajectory reveals consistent methodological advancement from 2012-2022, with core themes spanning structural break detection in economic time series, generative income distribution modeling, and comparative Phillips curve analysis across 15+ countries. The research demonstrates increasing sophistication in handling non-stationary economic data while maintaining strong policy relevance for central banking and inequality measurement. Scientific Awards: Cambridge Centre for Teaching and Learning Technology-enabled Learning Prize (2021) As Convener of Undergraduate Admissions, Kitov shapes the academic cohort for Cambridge's Economics program while teaching advanced econometrics. His office hours (Tuesdays 11:15am-12:15pm in Room 79) support student engagement with complex quantitative methods, reflecting his dual commitment to research excellence and pedagogical innovation recognized by the 2021 teaching prize.

• Geochemistry
• Climate change science
• Hydrology
• +۹ مورد دیگر

Gabriel Bowen is a Professor in the Department of Geology & Geophysics at the University of Utah, where he has held academic positions since 2012, advancing to full Professor in 2016. His work is centered on isotope geochemistry and its applications to Earth system science, climate, hydrology, and environmental change. His research spans climate change science, hydrology, atmospheric sciences, paleoclimatology, ecology, and forensic geolocation . He uses stable isotopes (oxygen, hydrogen, carbon, strontium) to investigate paleoenvironments, animal and human movement, groundwater dynamics, and land-atmosphere interactions. His work integrates field data, modeling, and large-scale data synthesis. His recent publications (2024–2025) reveal a strong focus on isotopic methods in environmental reconstruction , including evapotranspiration partitioning, urban water isoscapes, strontium provenance models, and paleo-CO2 reconstructions. He leads major collaborative initiatives such as IsoBank and CO2PIP , which aim to standardize and centralize isotopic and paleoclimate data. Scientific Awards: Distinguished Research Award, University of Utah (2025, 2024) Distinguished Visiting Fellowship, Tongji University (2019) Fellow, Geological Society of America (2016) James B. Macelwane Medal, American Geophysical Union (2012) Fellow, American Geophysical Union (2012) He has secured numerous grants from the National Science Foundation, American Chemical Society, and US Environmental Protection Agency , supporting research on paleoclimate, isotope systems, and environmental monitoring. He teaches courses such as Isoscapes , Carbon Cycle , and Thesis Research at both Master’s and PhD levels. He also engages in community outreach, including collaborative research with the Jordan Valley Water Conservancy District. He is actively involved in professional service, including membership on the Petroleum Research Fund Advisory Board (ACS) and the Urbino Summer School on Paleoclimatology Board of Directors .

Melanie Dirksمشاهده پروفایل

استاد

• Clinical Psychology
• Developmental Science
• Peer Relationships
• +۶ مورد دیگر

Professor Melanie Dirks is the Department Chair of Psychology at McGill University, specializing in Clinical Psychology and Developmental Science . Her research focuses on mapping social and emotional skills across childhood, adolescence, and young adulthood, with emphasis on peer/sibling relationships and their impact on psychological symptoms. Uses multimodal methodologies: observational studies, daily diaries, emotion recognition tasks Current projects: friendship quality maintenance, interpersonal victimization in youth, emotional communication dynamics Key research themes from publications include: Peer Relationships : Dissolution patterns, prosocial behavior, bullying, and dating aggression Emotional Processing : Vocal emotion recognition, neural reward responses, stress-neuroimaging links Contextual Influences : Family dynamics, socioeconomic status, post-pandemic social changes Her lab ( CASC Lab ) trains students in advanced social-emotional assessment techniques, with notable advisees including *Morningstar, *Gilbert, and *Santucci. Google Scholar articles (2014-2025) demonstrate expertise in developmental psychopathology, social neuroscience, and cross-cultural mental health determinants.

Yann Quilcailleمشاهده پروفایل

پژوهشگر

• Climate Extremes
• Climate Emulators
• Climate Modeling
• +۳ مورد دیگر

Dr. Yann Quilcaille is a Researcher at ETH Zurich's Department of Environmental Systems Science, affiliated with the Professorship for Land Climate Dynamics. His work focuses on climate extremes, climate emulators, and socio-economic integration of climate models. He holds a PhD from Université Paris-Saclay and previously served as a research scholar at IIASA (Austria), advancing the OSCAR climate model. Key contributions include the MESMER-X emulator for spatially resolved climate extremes and research on fire weather, extreme event attribution, and climate overshoot scenarios. Dr. Quilcaille's research integrates physics-based and statistical approaches to develop low-cost climate emulators, aiming to bridge climate modeling with socio-economic frameworks. His expertise spans heatwaves, droughts, and fires, with a focus on global and regional climate impacts. Notable projects include analyzing fire weather overlaps between continents and quantifying carbon majors' contributions to historical heatwaves. His academic journey includes studies at Ecole Normale Supérieure de Paris-Saclay (Theoretical Physics), AgroParisTech (Economics of Sustainable Development), and Université Pierre & Marie Curie (Ocean, Atmosphere, Climate). He has authored over 50 publications on climate modeling, emulation techniques, and policy-relevant climate science.

Claudia Kuenzerمشاهده پروفایل

پژوهشگر

• Remote Sensing
• Environmental Science
• Geoscience
• +۵ مورد دیگر

Claudia Kuenzer is a Senior Researcher and Head of the 'Land Surface Dynamics' Research Group at the German Earth Observation Center (EOC) of the German Aerospace Center (DLR). She serves as the Overall Scientific Project Coordinator for initiatives such as WISDOM, DELIGHT, and DRAGON-3. Her expertise spans multispectral, thermal, and radar remote sensing, with a focus on environmental monitoring, land surface dynamics, and capacity-building in geosciences and resource management. She has held leadership roles in projects addressing coal fires, forest fires, and integrated watershed management in Asia. Dr. Kuenzer holds a PhD in Earth Sciences and has conducted research at institutions including the University of Trier (Germany), Western Washington University (USA), and Beijing Normal University (China). Her work integrates remote sensing with GIS to address global challenges like climate change impacts, disaster response, and sustainable resource management. She has coordinated large-scale international collaborations, notably in Southeast Asia and Europe. Key areas of focus include satellite-based monitoring of vegetation, surface water dynamics, and coastal changes. She has pioneered methodologies for analyzing long-term environmental trends using multi-decadal satellite datasets. Her contributions extend to policy-oriented applications, such as vulnerability assessments and knowledge systems for adaptive management in regions like the Mekong Delta. Her research outputs include over 150 peer-reviewed articles, focusing on remote sensing applications in forestry, hydrology, and climate science. She leads DLR’s efforts in developing innovative tools for Earth observation data analysis, including deep learning approaches for glacier monitoring and supraglacial lake dynamics. Her team also explores offshore wind energy infrastructure tracking and permafrost erosion monitoring in Arctic regions.

• Psychology
• Neuroscience
• Attention-Deficit/Hyperactivity Disorder (ADHD)
• +۶ مورد دیگر

Assoc. Professor Adam Clarke is an Associate Professor at the School of Psychology, University of Wollongong. He specializes in electrophysiological research, focusing on ADHD, dementia, mindfulness meditation effects, and neurocognitive mechanisms. His work integrates EEG analysis with behavioral studies to explore attentional processes, arousal dynamics, and developmental psychophysiology. Research Interests: Professor Clarke’s research spans clinical and developmental psychophysiology, including EEG biomarkers for ADHD and dementia, meditation-induced neural changes, and age-related cognitive decline. He leads studies on gait analysis linked to cognitive impairment and employs advanced neuroimaging techniques to investigate attentional disorders. Funding Highlights: He has secured grants totaling AUD millions, including projects on dementia diagnosis via EEG-gait integration, ADHD neurodevelopment, and mindfulness-based interventions. Notable grants include the ARC-funded studies on ADHD central nervous system dynamics (2009–2013) and the 2023 UOW grant on gait-stability biomarkers for dementia. Key Projects: Biofeedback for dementia patients, EEG coherence in ADHD/autism comorbidity, and mindfulness-induced EEG spectral changes Labs: Centre for Psychophysics, Psychophysiology, and Psychopharmacology; Collaborative gait-neuroimaging lab Teaching & Supervision: Current PhD supervision includes dual-task biofeedback protocols and mindfulness EEG studies. Over 10 completed PhDs cover topics like ADHD EEG development, schizotypy stress responses, and gambling physiology.

MEHMET DİKİCİمشاهده پروفایل

دانشیار

• Hydrology
• Flood Modeling
• Drought Analysis
• +۲ مورد دیگر

Mehmet Dikici serves as Associate Professor in the Department of Civil Engineering at Alanya Alaaddin Keykubat University's Faculty of Engineering, specializing in hydrological systems and water resource management with 15+ years of academic experience. His academic credentials include: Doctorate in Civil Engineering from Istanbul University (2011-2016) focusing on Hydrodynamic modeling of Alibeyköy Basin and flood risk mapping Master's in Hydraulic and Water Resources Engineering from Istanbul Technical University (2006-2009) with thesis on Dry period analysis of Istanbul rainfall Non-thesis Master's in Urban Studies and Management from Istanbul Sabahattin Zaim University (2014-2015) Bachelor's in Civil Engineering from Istanbul Technical University (1986-1990) Research centers on flood/drought dynamics using remote sensing and hydromechanical modeling , with significant focus on Turkish basins including Alibeyköy, Seyhan, and Ceyhan. His work integrates geospatial technologies for risk assessment and numerical simulation for urban water management challenges, particularly in Mediterranean coastal regions. Recent publications demonstrate methodological evolution from traditional hydrological modeling (2018-2020) toward integrated remote sensing approaches (2021-2024), with increasing emphasis on climate change impacts and post-disaster flood analysis. Key trends include multi-index drought assessment, fire-flood interactions, and basin-specific flood probability frameworks. As Department Head (2018-2020), he led research projects including Impacts of Low Impact Developments on Surface Flow in Alibeyköy Watershed (2016) and Calibrated Hydrological Model for Alibeykoy Watershed (2018-2019), plus national initiatives like the IPCC Turkey report (2024) and 1st Water Council (2021). His applied work connects academia with disaster response through Turkish Red Crescent leadership (Alanya Branch Head since 2019) and board memberships in CEKUD and BAMDER (since 2012), focusing on coastal erosion studies and ancient city infrastructure evaluation.

Jörg Henselerمشاهده پروفایل

استاد

• Structural Equation Modeling
• Partial Least Squares Path Modeling
• Composite-Based Structural Equation Modeling
• +۸ مورد دیگر

Prof. Dr. Jörg Henseler is Full Professor and Chair of Product–Market Relations at the Department of Design, Production and Management, Faculty of Engineering Technology, University of Twente, Netherlands. He also holds visiting positions at NOVA Information Management School, Universidade Nova de Lisboa, Portugal, and as Distinguished Invited Professor at the University of Seville, Spain. University: University of Twente School: Faculty of Engineering Technology Department: Department of Design, Production and Management Chair: Product–Market Relations Visiting Professor: NOVA Information Management School, Portugal Distinguished Invited Professor: University of Seville, Spain His research focuses on composite-based structural equation modeling (SEM) , particularly partial least squares (PLS) path modeling , emergent variables , and methodological innovations in empirical research. He bridges design and behavioral sciences through advanced statistical modeling, with applications in marketing, management, and information systems. His recent publications emphasize methodological rigor in PLS-SEM, including consistent PLS (PLSc) , confirmatory composite analysis (CCA) , HTMT for discriminant validity , and second-order modeling . These works highlight trends toward improved model assessment, validity testing, and theoretical integration in composite-based approaches. Highly Cited Researcher by Clarivate/Web of Science Ranked among the top 100 most influential researchers in the Stanford/Elsevier Top 2% Scientists List 2024 Repeated 'Teacher of the Year' award recipient Prof. Henseler contributes extensively to the scientific community as a reviewer, editorial board member, and guest editor. He chairs the scientific advisory board for the ADANCO software and organizes the PLS School , offering seminars on PLS path modeling. He has authored over 130 journal articles and the authoritative book Composite-Based Structural Equation Modeling . His work supports researchers in applying robust, theory-driven methods in empirical studies. He leads methodological innovation in composite-based modeling, with strong ties to software development and global academic outreach. His research group and collaborations focus on advancing SEM techniques for complex, real-world applications in business and engineering contexts.

Shusen Puمشاهده پروفایل

استادیار

• Computational Neuroscience
• Mathematical Biology
• Mathematical Statistics
• +۷ مورد دیگر

Dr. Shusen Pu is an Assistant Professor in the Department of Mathematics and Statistics at the University of West Florida (UWF) , within the Hal Marcus College of Science and Engineering . He joined UWF in 2022 after serving as a Lecturer at Vanderbilt University. His academic journey includes a Ph.D. in Applied Mathematics from Case Western Reserve University (2020), advised by Dr. Peter J. Thomas, and postdoctoral research with Dr. Christos Constantinidis. Dr. Pu's educational background includes: Ph.D. in Applied Mathematics, Case Western Reserve University B.S. in Mathematics and Statistics, Beijing Normal University His research spans computational neuroscience , mathematical statistics , data analytics , and deep learning . He investigates neural network models, working memory, stochastic processes in biological systems, and generalized statistical distributions. He collaborates with biologists to analyze experimental data and integrates deep learning into neuroscience applications. His work aims to bridge microscopic neural activities with macroscopic behaviors. His recent publications (2024–2018) reflect a strong focus on both neuroscience modeling and statistical distribution theory . Articles in journals like Nature Communications , Entropy , and Biological Cybernetics demonstrate expertise in prefrontal neuronal dynamics, neural noise modeling, and novel distribution generators. The consistency in topics indicates a dual research thrust: understanding brain function through computational models and advancing statistical tools for real-world data analysis. Scientific contributions include: Published in high-impact journals such as Nature Communications , Neural Computation , Eneuro , and Biological Cybernetics Reviewer for multidisciplinary journals including iScience (Cell Press) Active participant and presenter at international conferences in Canada, China, and the USA Organizer of academic conference sessions and workshops Dr. Pu is deeply involved in academic mentoring and teaching. He advises students in capstone projects integrating mathematical modeling, data science, and statistical analysis. He teaches courses such as Analytic Geometry and Calculus, Linear Algebra, Deep Learning, and Mathematical Statistics. He emphasizes problem-solving methodology, collaborative learning, and real-world applications. He leads the Computational Statistics and Data Analytics (CSDA) Lab , hosting weekly lab meetings and Python/data science tutorials, fostering a collaborative research environment. His lab and team activities include: Weekly lab meetings (Fridays 9:00–10:00, Building 4, Room 212) Weekly Python and Data Science Tutorials (Fridays 10:00–11:00, same location) Supervision of capstone projects in data science and mathematical modeling Active research in neural connectivity inference and statistical distribution development

• Database Systems
• Data Privacy
• Machine Learning
• +۴ مورد دیگر

Zhenjie Zhang is a Professor in the Department of Computer Science at East China Normal University's School of Computer Science and Software Engineering, with a distinguished research career spanning nearly two decades. His work bridges theoretical computer science with practical industrial applications, maintaining strong international collaborations with researchers from TU Wien, National University of Singapore, and industry partners including ByteDance. Dr. Zhang's research focuses on the intersection of database systems, machine learning, and industrial applications. His early work centered on database privacy and query processing, evolving toward causal inference, fault diagnosis systems, and industrial AI applications. His recent publications demonstrate a strategic shift toward solving real-world engineering problems using advanced machine learning techniques, particularly in manufacturing, transportation, and cloud systems. The consistent publication trajectory across top venues like IEEE TKDE, VLDB, and ACM Transactions shows sustained research excellence and adaptability to emerging technical challenges. His publication record reveals significant contributions to causal inference methods, evidenced by multiple papers on causal discovery and transfer learning. The research demonstrates practical impact through industrial collaborations, particularly in fault diagnosis systems for mechanical equipment and adaptive control for unmanned vehicles. The recent work shows increasing focus on deploying AI models efficiently in resource-constrained environments, reflecting awareness of practical implementation challenges. Dr. Zhang has mentored numerous junior researchers who have become active contributors in the field, including Ruichu Cai and Zining Zhang. His collaborative network spans multiple continents, indicating strong research leadership and international recognition. The consistent flow of publications in top venues suggests successful grant funding and research group management, though specific grant details aren't provided in the source material.

Jan Helmdagمشاهده پروفایل

استادیار

• Social Policy
• Political Economy
• Welfare State Dynamics
• +۴ مورد دیگر

Jan Helmdag is an Assistant Professor at the Swedish Institute for Social Research (SOFI) and Managing Director of the Social Policy Indicators (SPIN) database . His work focuses on taxation, social policy design, and political economy , with particular emphasis on income inequality mitigation through institutional data analysis. SPIN's collaboration with the Democracy, Environment, Migration, Social Policy, Conflict, and Representation (DEMSCORE) infrastructure highlights his cross-domain engagement. Research Interests : Helmdag investigates how social policy architecture affects income inequality , notably through his Benefit Dualization Index (BDI) which quantifies welfare state disparities between labor market insiders and outsiders . His EU pension reform analysis reveals systemic prioritization of financial sustainability over benefit adequacy and gender modernization in socio-economic governance. Helmdag has conducted comparative studies across OECD countries on unemployment benefit dynamics and active labor market policies , demonstrating conditioned policy learning among welfare regimes . His 2024-26 FORTE-funded project on Swedish social rights dualization builds upon his extensive work in benefit replacement rate analysis and policy indicator development .

• Statistical Science
• Quality Control
• Robust Parameter Design
• +۳ مورد دیگر

Yasushi Nagata is a Professor at Waseda University's School of Creative Science and Engineering. With a Doctor of Engineering from Osaka University, he specializes in statistical quality control, Taguchi methods, and multivariate analysis. Key affiliations: Japan Society for Quality Control Japan Statistical Society Japan Behaviormetrics Society Research Interests: His work focuses on advancing Taguchi's robust parameter design, Mahalanobis-Taguchi systems, and statistical anomaly detection. He has developed novel methods for handling missing data, high-dimensional datasets, and non-normal distributions in quality control contexts. Scientific Awards: He has received multiple Best Paper Awards at ANQ Congresses (2017-2024) Deming Prize for Individuals (2019) Waseda University Teaching Awards (2018, 2022) Nikkei Quality Control Literature Prizes Publications: His recent studies examine non-stationary extreme precipitation data, robust parameter design for multilevel systems, and EM-λ algorithm integration with MT methods. These works bridge theoretical statistics with practical engineering applications.

• Environmental Chemistry
• Pollution Assessment
• Geochemistry
• +۴ مورد دیگر

Dubravka J. Relić is an Associate Professor at the University of Belgrade's Faculty of Chemistry , Department of Applied Chemistry. She specializes in environmental chemistry with a focus on pollution assessment in sediments, soils, water, and air. Her work addresses contamination from industrial, agricultural, and urban sources, emphasizing heavy metal speciation and environmental risk evaluation. Education: BSc Chemistry (1998), University of Belgrade Faculty of Chemistry MSc Chemistry (2006), University of Belgrade Faculty of Chemistry PhD Chemistry (2012), University of Belgrade Faculty of Chemistry Research Interests: Her studies examine contamination pathways in aquatic and terrestrial environments, including heavy metal mobility, pollution indices, and bioavailability in agricultural systems. She applies advanced analytical techniques like microwave digestion and sequential extraction to evaluate element fractionation. Current projects include EU-funded initiatives on PFAS contamination and cross-border pollution analysis. Research Projects: EU Horizon 2022-2025: Addressing PFAS challenges in Serbia (Principal Investigator) Bilateral 2021-2022: Organophosphate flame retardants exposure assessment (PI) International 2019: Soil and food sample pollution in Serbia/Slovakia Professional Activities: Member of Faculty Promotion Committee (2019-2021) and Exams Recognition Committee (2018-2021). Teaches courses like Environmental Chemistry and Chemodynamics of Pollutants . Active in international collaborations through Erasmus+ programs. Lab Affiliation: Conducts research in Department of Applied Chemistry laboratories, focusing on sediment/water analysis and environmental sampling techniques.