جست‌وجوی استاد و پژوهشگر

Huijun Cynthia Chenمشاهده پروفایل

استادیار

• Economics of Ageing
• Healthcare Financing
• Public Health and Ageing
• +۷ مورد دیگر

Dr. Huijun Cynthia Chen is an Assistant Professor at the Saw Swee Hock School of Public Health , National University of Singapore. She specializes in the economics of aging, focusing on retirement, health outcomes, caregiver burden, healthcare expenditure, and policy impacts. Her work bridges public health, biostatistics, and policy evaluation. Education : PhD in Public Health (2014), MSc in Statistics (2011), BSc in Statistics with Mathematics minor (2009) from NUS. Dr. Chen’s research spans aging societies, health economics, and data-driven policy analysis. She investigates gender disparities in aging, caregiver health impacts, and vaccination cost-effectiveness. Her work emphasizes global aging readiness and health equity. Her recent publications analyze societal aging frameworks, dementia risk factors, and workplace health interventions. These studies explore multidimensional aging metrics, racial disparities in cognitive decline, and strategies to reduce sedentary behavior in Asia. Scientific Awards : SSHSPH Young Researcher Award, NUS Overseas Postdoctoral Fellowship, Best Oral Presentation at Universitas 21, and others. Dr. Chen has secured funding from the National Institute on Ageing (USA) and Singaporean institutions. Her teaching includes public health economics, aging, and statistical methods. Media outlets like The Lancet and The Straits Times have highlighted her work on aging preparedness and healthcare cost savings.

• Neurosciences
• Digital health
• Aged health care
• +۴ مورد دیگر

Chao Deng is a Professorial Fellow at the University of Wollongong, affiliated with the School of Medical, Indigenous and Health Sciences within the Faculty of Science, Medicine and Health. He holds a PhD from the University of New England. His research focuses on neurosciences, digital health, aged care, health informatics, psychopharmacology, psychiatry, and artificial intelligence. Key research areas include the molecular mechanisms of antipsychotic-induced metabolic disorders, neurodegenerative diseases like Parkinson’s, and leveraging AI for healthcare data analysis. He has secured grants from NHMRC and internal university funding for projects such as studying RF electromagnetic exposure impacts and developing advanced imaging tools. He actively supervises PhD students in topics like AI-driven health analytics in aged care, behavioral impacts of antipsychotics in juveniles, and non-pharmacological dementia treatments. His work spans interdisciplinary collaborations, integrating clinical, technological, and molecular approaches to address complex health challenges.

James A. Mingoمشاهده پروفایل

استاد

• Free probability
• Random matrices
• Operator algebras
• +۵ مورد دیگر

James A. Mingo is a Professor in the Department of Mathematics and Statistics at Queen's University. His research focuses on free probability, random matrices, operator algebras, and related areas. He holds a Ph.D. from Dalhousie University. Education: Ph.D. (Dalhousie University) Research Interests: Mingo's work explores the interplay between free probability and random matrices, with applications to operator algebras and mathematical physics. Key topics include infinitesimal freeness, asymptotic distributions of random matrices, and combinatorial structures in non-commutative probability. His contributions bridge abstract algebraic frameworks with probabilistic methods, addressing questions in both theoretical and applied contexts. Grants and Collaborations: Mingo collaborates widely, as evidenced by his co-authored papers with researchers like Roland Speicher, Mihai Popa, and Daniel Munoz George. His research has been supported by grants from institutions like the Simons Foundation. Teaching and Service: Mingo has taught courses such as STAT/MTHE 353 and MATH 892 at Queen's University, reflecting his commitment to both undergraduate and graduate education. He also organizes research seminars and workshops in free probability and random matrices.

• Clinical Epidemiology
• Musculoskeletal Disorders
• Rheumatology
• +۳ مورد دیگر

Dr. Helen Myers is a Research Fellow and Trial Manager in the School of Medicine at Keele University, specializing in Clinical Epidemiology of musculoskeletal conditions, particularly focusing on hand and rheumatological disorders. She joined Keele’s Primary Care Sciences department in 2002 after completing a BSc in Occupational Therapy (1991), an MSc in Healthcare Research (1997, Loughborough University), and a PhD (2008, Keele University). She received the UK Occupational Therapy Research Foundation Early Researcher Award in 2010. Her research emphasizes clinical trials and observational studies, including the PANDA-S and CAS-HA projects, which explore shoulder pain prognosis and hand osteoarthritis epidemiology. She has collaborated on trials evaluating corticosteroid injections, night splints for carpal tunnel syndrome, and digital imaging for osteoarthritis progression assessment. Dr. Myers also teaches research methods to third-year medical students. Research Interests: Hand osteoarthritis, carpal tunnel syndrome, musculoskeletal epidemiology, clinical trial design, and primary care interventions. Awards: United Kingdom Occupational Therapy Research Foundation Early Researcher Award (2010). Professional Affiliations: British Association of Occupational Therapists, British Association of Hand Therapists, British Health Professionals in Rheumatology, and registered with the Health Professions Council. Her work spans over 30 peer-reviewed articles, focusing on clinical trial methodologies, osteoarthritis subtypes, and cost-effectiveness analyses. She manages trials like PANDA-S, investigating shoulder pain interventions, and collaborates with NHS trusts through Keele’s Clinical Education Centre.

Muhammad Usmanمشاهده پروفایل

مدرس

• Biostatistics
• Epidemiology
• Health Informatics
• +۶ مورد دیگر

Muhammad Usman is a Lecturer in Biostatistics at Keele University's School of Medicine, UK. He holds an MSc in Applied Statistics and Biostatistics from Hasselt University (Belgium), an MSc in Statistics from the University of Peshawar, and a PhD from the University of Leicester (2020). His research focuses on randomized controlled trials, cohort studies, electronic health records, and systematic reviews/meta-analyses. He is a member of Keele’s Biostatistics Group and teaches the 'Fundamentals of Statistics with Applications in R' module in the BSc Mathematics program. Education MSc in Applied Statistics and Biostatistics, Hasselt University, Belgium MSc in Statistics, University of Peshawar PhD in Biostatistics, University of Leicester (2020) Research Interests Usman’s work emphasizes methodological and applied research in clinical epidemiology, including: Design and analysis of randomized controlled trials Cohort observational studies in healthcare Secondary data analysis using electronic health records Systematic review and meta-analytic techniques Teaching He contributes to the BSc Mathematics curriculum via the 'Fundamentals of Statistics with Applications in R' module, focusing on statistical principles and computational implementation. Labs & Teams Affiliated with Keele’s Biostatistics Group, contributing to interdisciplinary research in medical and health sciences.

• Number Theory
• Algebra
• Dynamical Systems
• +۳ مورد دیگر

Chatzakos Dimitrios is an Assistant Professor at the Department of Mathematics, University of Patras. He holds a Ph.D. in Mathematics from University College London (UK), an M.Sc. and B.Sc. from the National and Kapodistrian University of Athens. His research interests focus on Number Theory, Algebra, and Dynamical Systems, with particular emphasis on hyperbolic geometry and analytic number theory. He teaches undergraduate courses in Algebra I and Real Analysis II, and a postgraduate course on Topics in Analysis. His research addresses prime geodesic theorems, hyperbolic lattice point problems, and quantum ergodicity in arithmetic settings. He has collaborated with researchers such as Olga Balkanova, Giacomo Cherubini, and Niko Laaksonen, producing impactful work published in journals like Mathematische Zeitschrift and Transactions of the American Mathematical Society . His contributions span topics including spectral theory, automorphic forms, and equidistribution phenomena in hyperbolic spaces.

Kevin Haworthمشاهده پروفایل

استادیار بالینی

• Clinical Psychology
• Behavioral Activation Therapy
• Dialectical Behavior Therapy
• +۵ مورد دیگر

Kevin Haworth is a Clinical Assistant Professor in the Department of Psychology at the University of Wisconsin-Milwaukee, part of the College of Letters & Science. He holds a Ph.D. from the same institution (2017). His clinical work focuses on behavioral activation for depression, dialectical behavior therapy for emotion regulation, mindfulness-based approaches for mood disorders, and exposure therapy for trauma. He specializes in clinical supervision of graduate students and teaching didactics in clinical psychology. Dr. Haworth’s research interests include anhedonia treatment mechanisms, therapy homework dynamics, and functional neuroimaging correlates of psychological interventions. Though he does not run a research lab or serve as primary adviser, he contributes as a clinical supervisor and research committee member. His work bridges therapeutic techniques with empirical evidence, emphasizing practical clinical training. Key contributions include randomized trials comparing behavioral activation and mindfulness-based cognitive therapy for anhedonia, neuroimaging studies on default-mode network connectivity, and component-process analyses of social connection in psychotherapy. His scholarship addresses both clinical outcomes and underlying neurobiological mechanisms.

Abhijit Mandalمشاهده پروفایل

دانشیار

• Robust Inference
• Nonparametric Statistics
• Big Data Analysis
• +۴ مورد دیگر

Abhijit Mandal is an Associate Professor in the Department of Mathematical Sciences at the University of Texas at El Paso. He serves as the Director of the Data Analytics Lab and holds multiple coordination roles, including overseeing the Graduate Certificate programs in Applied Statistics and Big Data Analytics. His work focuses on developing robust statistical methods to handle noisy data, particularly in the areas of robust inference, nonparametric statistics, and biostatistics. His research spans robust statistical methodologies, including applications in high-dimensional data analysis, functional regression, and biostatistical modeling of metabolic and inflammatory risks. Key contributions include novel techniques for variable selection, spatial data analysis, and the mitigation of outlier effects in complex datasets. He also explores interdisciplinary applications, such as microglial signaling in metabolic dysfunction and the impact of environmental pollutants on health. Mandal’s recent publications emphasize robust statistical frameworks for functional data, panel data models, and healthcare analytics. His work often integrates computational methods like the Metropolis algorithm and advanced regression techniques to address real-world challenges. He is a UTEP Edge Curriculum Fellow, reflecting his commitment to innovative teaching and curriculum development in data science. While no specific scientific awards are listed, his active roles in directing research labs and coordinating academic programs highlight his leadership in fostering data-driven research and education. In advising, Mandal’s focus is on mentoring students in statistical methodologies applicable to diverse domains. His research teams collaborate across disciplines, including neuroscience and environmental health, as seen in studies linking air pollutants to metabolic disorders through microglial pathways.

• Educational Psychology
• Student Engagement
• Teacher Motivation
• +۵ مورد دیگر

Hye-Ryen Jang is a Lecturer at the Australian Catholic University (ACU), affiliated with the Faculty of Education and Arts and the Institute for Positive Psychology and Education. Her work focuses on educational psychology, particularly the intersection of teacher behavior, student engagement, and classroom climate. She explores how autonomy-supportive teaching strategies influence both student outcomes and broader social dynamics, such as teacher-to-parent spillover effects and peer victimization reduction. Her research also extends to theoretical frameworks like self-determination theory and its applications in education and intervention design. Her research interests emphasize understanding motivational processes in educational settings, including the effects of instructional goals, harmonious passion development among teachers, and reciprocal relationships between agentic engagement and autonomy support. She employs experimental and longitudinal methodologies to investigate these dynamics, frequently collaborating with institutions like the Institute for Positive Psychology and Education. Her articles highlight trends in intervention studies, meta-analytic approaches, and the analysis of prosocial/antisocial behaviors in students. She consistently advocates for autonomy-supportive pedagogical strategies as a cornerstone for fostering positive educational climates.

Tara Chaplinمشاهده پروفایل

دانشیار

• Adolescent Development
• Emotion Regulation
• Psychopathology
• +۴ مورد دیگر

Dr. Tara Chaplin serves as Associate Professor of Psychology at George Mason University, where she directs research on adolescent emotional development, psychopathology, and substance use with emphasis on sex differences and family context. A licensed clinical psychologist, she joined GMU in 2013 after serving as Assistant Professor in Psychiatry at Yale University School of Medicine. Her educational background includes a Ph.D. in Child-Clinical Psychology from Penn State University (2003) and a B.A. in Psychology with Biology minor from the University of Delaware (1997). 2003: Ph.D., Clinical Psychology, Penn State University 1997: B.A., Psychology (Biology minor), University of Delaware Chaplin's research pioneers bio-psycho-social models examining how emotional arousal and emotion regulation interact with parenting dynamics to influence adolescent risk behaviors. Her work uniquely integrates fMRI neuroimaging , cardiovascular measures (heart rate variability), neuroendocrine assessments (HPA axis), and ecological momentary assessment to capture real-time developmental processes. Current focus areas include sex-differentiated neural pathways to substance use and mindfulness-based parenting interventions for stress reduction. Analysis of her publication trajectory reveals increasing methodological sophistication in linking neural mechanisms with behavioral outcomes, particularly through longitudinal designs tracking adolescents from early to middle adolescence. Her work consistently demonstrates how parenting interventions can modify neurobiological stress responses to prevent psychopathology. Her scientific recognition includes: NIH/NIDA Independent Scientist Award (K02 DA058840) NIH/NIDA Career Development Award (K01DA024759) Chaplin has mentored eight doctoral students to completion with diverse research foci spanning adolescent neuroimaging, immigrant parenting, and intervention development. She currently recruits PhD students for Fall 2025. Her NIH-funded research program includes: Active Grants: R01 DA033431: $2.5M study on parent-adolescent interactions and brain mechanisms in substance use R01 DA052427: $3.1M trial of mindfulness intervention for stressed parents K02 DA058840: $500K Independent Scientist Award She leads a multidisciplinary research team conducting four major studies including NIH-funded longitudinal projects examining parent-adolescent neurobiological synchrony, with specialized focus on Latina mothers in pilot work. Her lab combines advanced neuroimaging with ecological assessment to capture dynamic parenting-emotion-behavior pathways.

Juanjuan Fanمشاهده پروفایل

استاد

• Biostatistics
• Survival Analysis
• Machine Learning
• +۳ مورد دیگر

Juanjuan Fan is Professor in the Department of Mathematics and Statistics at San Diego State University, specializing in biostatistics, machine learning, and data science applications in healthcare and education. Her research develops novel statistical methods including survival analysis techniques, random forest variants, and causal inference approaches for complex observational data. Recent publications (2020-2024) demonstrate interdisciplinary applications: machine learning models for economic policy forecasting, educational intervention efficacy, autism diagnosis via neuroimaging, and diabetes management. Methodological innovations include ensemble techniques for causal inference, longitudinal random forests, and optimization algorithms for admission systems.

• Neurophysiology
• Motor Control
• Parkinson's Disease
• +۵ مورد دیگر

Dr. José Andrés Sánchez Molina is an Associate Professor at the University of A Coruña's Faculty of Sports Sciences and Physical Education. He holds roles such as Secretary of the Faculty and Vice President of multiple academic committees. His research focuses on neurophysiological mechanisms in movement control, particularly in Parkinson's disease, motor learning, and the integration of exercise and neuromodulation techniques. He has directed numerous theses on topics like swimming training periodization and badminton technique improvement. His teaching spans master's and undergraduate programs, including courses on motor learning, statistical analysis, and sports science. He leads the 'Grupo de aprendizaje y control del movimiento humano en actividad física y deporte' research group, emphasizing translational research in neurorehabilitation and sport performance. Key projects include evaluating transcranial direct current stimulation combined with exercise for neuroplasticity in Parkinson's patients. His academic service includes roles in faculty governance, curriculum evaluation, and academic quality committees. He has authored over 30 peer-reviewed articles on gait analysis, cognitive-motor interactions, and sport biomechanics, with a focus on translating findings into clinical and educational practice.

Daniel Gerviniمشاهده پروفایل

استاد

• Functional Data Analysis
• Robust Statistics
• Nonparametric Statistics
• +۳ مورد دیگر

Daniel Gervini is Professor and Data Science Undergraduate Coordinator in the Department of Mathematical Sciences at University of Wisconsin-Milwaukee. His research centers on functional data analysis, robust statistics, and point process modeling, with applications to spatial statistics and multivariate analysis. Educational credentials include a Ph.D. in Mathematics from University of Buenos Aires (1999) and M.S. from the same institution (1995). He held postdoctoral positions at University of Zürich Biostatistics Department (2001-2004) and research fellowship at University of Buenos Aires (1996-1999). Research develops novel methods for functional data including warped regression, outlier-resistant estimation, and point process modeling. Recent NSF-funded projects focus on spatio-temporal covariation in replicated point processes and statistical methods for point-process time series. Applications include bike-sharing demand analysis and neuroimaging. Publication trends showcase progression from foundational robust functional methods to advanced spatio-temporal point process modeling. Recent work emphasizes computational statistics applications to urban systems and environmental data. Develops extensive open-source statistical software packages in MATLAB for functional data analysis, point process modeling, and spatio-temporal prediction. Maintains active research blog on statistical analysis of COVID-19 pandemic data.

Kirsti Loughranمشاهده پروفایل

پژوهشگر ارشد

• Respiratory Medicine
• Gerontology
• Physiotherapy
• +۳ مورد دیگر

Kirsti Loughran is a Research Fellow at Teesside University's School of Health and Life Sciences (SHLS), within the Allied Health Professions Centre for Rehabilitation. She holds a PhD in Physiotherapy from Teesside University (2022), an MClinRes in Older People from Newcastle University (2016), and a Bachelor's in Physiotherapy from the University of East London (2003). Her research focuses on chronic respiratory conditions like COPD, emphasizing balance impairment, falls prevention, and patient engagement strategies. She is actively involved in prehabilitation studies for cardiac surgery patients and innovative digital interventions for chronic breathlessness management. **Education**: PhD: An investigation of pain's impact on falls risk in COPD patients (Teesside University, 2022) MClinRes: Older People (Newcastle University, 2016) Bachelor of Physiotherapy (University of East London, 2003) **Research Interests**: Chronic respiratory disease, balance and gait disorders, prehabilitation protocols, patient and public involvement in research, and digital health solutions for chronic conditions. Her work bridges clinical practice and population health, addressing gaps in COPD management and surgical preparation. **Grants & Projects**: Co-Investigator on a Boehringer Ingelheim-funded project developing a digital COPD self-management tool (2021–2022). Lead researcher on the PrEPS Trial, evaluating prehabilitation for cardiac surgery patients. Collaborates internationally on COPD-related studies. **Labs/Teams**: Part of the Allied Health Professions Centre for Rehabilitation at Teesside University, focusing on translational research in respiratory and cardiac health.

Robert Lemke-Oliverمشاهده پروفایل

دانشیار

• Analytic number theory
• Arithmetic statistics
• L-functions
• +۵ مورد دیگر

Robert Lemke-Oliver is an Associate Professor in the Department of Mathematics at Tufts University. His research focuses on analytic number theory and arithmetic statistics, with support from NSF grant DMS-2200760. He explores connections between prime numbers, elliptic curves, and modular forms, emphasizing equidistribution problems and Diophantine equations. Education: PhD, Emory University (2013) MA, University of Wisconsin-Madison (2010) BS, Rose-Hulman Institute of Technology (2008) His work bridges classical number theory with modern applications, particularly through L-functions and modular forms. He investigates how these tools capture prime distribution properties and solve problems related to elliptic curve ranks and class groups. Recent research trends include: Prime number biases in consecutive distributions Galois group structures in number field counting Modular form applications to elliptic curves Equidistribution and arithmetic statistics He has collaborated with institutions such as MSRI and delivered invited lectures at major conferences, including the Maine-Quebec Number Theory Conference and the Automorphic Forms Workshop.