Find Academic Supervisors

• Bayesian Statistics
• Computational Statistics
• Probabilistic Machine Learning
• +5 more

Professor Sumeetpal Singh holds the Tibra Foundation Chair in Mathematical Sciences at the University of Wollongong's Faculty of Engineering and Information Sciences, School of Mathematics and Applied Statistics (since 2023). Previously, he served as Professor of Engineering Statistics at the University of Cambridge (2007–2023) and as a Fellow and Director of Studies at Churchill College, Cambridge. His research focuses on Bayesian Statistics, Computational Statistics, Probabilistic Machine Learning, and Time-series analysis, with notable contributions to particle filtering, Monte Carlo methods, and statistical inference. He has supervised research on topics like 'American options and their application in political science'. His work has been recognized with awards such as the M. Barry Carlton award (2014). Singh is actively involved in editorial roles, including serving as Associate Editor for the Annals of Applied Probability and Senior Associate Editor for ACM Transactions on Probabilistic Machine Learning . Current research includes grants like the Air Force Office of Scientific Research-funded project on Bayesian Spatio-Temporal Analysis (2023–2025). Teaching includes modules like Statistical Modelling and Analysis of Time-series Data and Statistical Inference and Introduction to Model Building . His publications span computational statistics, signal processing, and machine learning, emphasizing methodological innovation and theoretical rigor.

• Survey Methodology
• Sample Survey Design
• Complex Social and Economic Data Analysis
• +4 more

David Steel is a Senior Professor and Professorial Fellow at the School of Mathematics and Applied Statistics, University of Wollongong. He holds roles such as Director of the Centre for Statistical and Survey Methodology, and has led research on survey methodology and statistical design for over three decades. His career includes significant contributions to the Australian Bureau of Statistics (ABS), where he specialized in sample survey design and analysis for major household surveys like the Monthly Labour Force Survey. Education : BSc in Pure Mathematics and Mathematical Statistics (University of Adelaide, 1973) Masters in Statistics (Australian National University, 1977–78, part-time) PhD in Social Statistics (University of Southampton, 1985) Research Focus : Steel’s work centers on survey methodology, including design and analysis of complex social and economic data, small area estimation, telephone survey methods, and repeated surveys. He emphasizes the interplay between data collection and analytical techniques, particularly in addressing challenges posed by complex population structures. Awards & Leadership : Member of the International Association of Survey Statisticians and former Associate Editor of the Journal of the Royal Statistical Society, Series A. He has secured over ten ARC/NHMRC grants since 1995 and led projects like the Applied Statistics Education and Research Collaboration funded by DEST.

• Corporate Governance
• Strategic Management
• Initial Public Offerings (IPOs)
• +3 more

S. Trevis Certo is the Jerry B. and Mary Anne Chapman Professor of Business at Arizona State University's W. P. Carey School of Business. His research focuses on corporate governance, top management teams, and initial public offerings (IPOs), with emphasis on how these structures influence firm performance. He has held editorial roles at top journals such as the Academy of Management Journal and Strategic Management Journal . Education: Ph.D. (Indiana University, 2000), M.B.A. (University of Florida, 1997), B.A. (Rollins College, 1995). Research Interests: Corporate governance mechanisms, board composition, IPO dynamics, and advanced statistical methodologies for large datasets. His work appears in leading journals and has been featured in major media outlets like the Wall Street Journal and Businessweek . Awards: Includes grants from the W. P. Carey School and Mays Business School, as well as recognition for research contributions. He has advised organizational leaders on strategic planning and serves on multiple editorial boards. Teaching: Focuses on doctoral research and seminars, with courses like MGT 792 Research and MGT 799 Dissertation . His work history includes roles at Texas A&M University, Indiana University, and the University of Florida.

Divya ShuklaView profile

Senior Lecturer

• Systems Thinking
• Leadership (Crisis, Inclusive, Ethical, Sustainable)
• Proactive Work Behaviour
• +6 more

Dr. Divya Shukla is a Senior Lecturer in Leadership & Organisational Behaviour at the Faculty of Business and Law , University of Northampton, UK. With 18 years of experience in teaching, research, and academic administration across India, Thailand, and Estonia, she leads MBA modules and designs courses on Human Resource Management, Leadership, and Organizational Behaviour. She is a Fellow of the Higher Education Academy (UK) and an academic member of the Chartered Institute of Personnel Development (CIPD). Education : PhD and Master's in Business Administration with specialisations in Human Resource Management and Organizational Behaviour from APS University, India. Professional Certifications : Higher Education Teaching and Research (IIM Indore), Quality Assessor (IQAN, Thailand), Case Writing (Munich Business School, Germany), and Didactics of Higher Education (Tallinn University of Technology, Estonia). Dr. Shukla's research spans systems thinking , multilevel leadership , and proactive work behavior , with a focus on crisis, inclusive, ethical, and sustainable leadership. Her work explores organizational culture, well-being, cognition, and employability, often employing fuzzy multi-criteria decision-making and quantitative research methods. Recent publications include studies on net-zero emissions in aviation, collective wellbeing during crisis in higher education, and digital communication strategies. Her research output (17 publications) and peer-review activities (23) reflect engagement with Scopus-indexed journals and British Academy of Management (BAM) initiatives. Scientific Awards : Fellow of the Higher Education Academy (HEA), UK Peer Review : Active reviewer for journals like British Journal of Management and International Journal of Organizational Analysis Supervision : Supervised PhD, master’s, and undergraduate students She contributes to the Systems, Analytics and Business Intelligence Research Group and remains a keynote speaker at international institutions, including Kyrgyz Economic University and PIBM Pune.

Qingshan ChenView profile

Associate Professor

• Fluid Dynamics
• Geophysical Flows
• Geometric Mechanics
• +4 more

Qingshan Chen is an Associate Professor in the Department of Mathematical and Statistical Sciences at Clemson University, part of the College of Science. His research focuses on fluid dynamics, geophysical flows, geometric mechanics, and turbulence, with expertise in numerical methods for geophysical and climate modeling systems. He develops conservative numerical schemes for complex fluid dynamics problems, including shallow water equations, quasi-geostrophic flows, and multi-layer models. His work emphasizes computational accuracy, stability, and applications in oceanography and atmospheric science. Chen’s research interests span applied mathematics, computational physics, and geophysical modeling. He has contributed to advancing finite volume methods, error analysis on unstructured meshes, and stochastic approaches like the multilevel Monte Carlo method for turbulent flow simulations. His studies often address challenges such as corner singularities in partial differential equations and incompatible initial-boundary conditions. Key applications include climate system modeling with frameworks like E3SM and MPAS, as well as glaciology and ocean circulation dynamics. His publications highlight innovations in numerical schemes for geophysical flows, including energy-conserving methods, optimal dispersive wave relations, and adaptive grid techniques. These contributions aim to bridge mathematical rigor with practical computational tools for environmental and engineering challenges. Chen’s work is disseminated through high-impact journals in applied mathematics, computational physics, and geosciences.

Monica MagadiView profile

Professor

• Epidemiology
• Global Health
• Maternal and Child Health
• +6 more

Monica Magadi is a Professor of Epidemiology and Global Health at Keele University's School of Medicine. She joined in October 2022 after serving as Professor of Social Research and Population Health at the University of Hull since 2012. Her academic background includes a PhD in Social Statistics (University of Southampton, 1999), MSc in Demography (University of Nairobi, 1989), and BEd in Mathematics and Statistics (Kenyatta University, 1987). Her research focuses on maternal/child health, adolescent sexual/reproductive health, and HIV/AIDS in sub-Saharan Africa, employing statistical modeling and mixed-methods approaches. Her teaching spans 25+ years, covering research methods, statistical analysis, and demography at undergraduate/postgraduate levels. She has supervised eight PhD students and served as an external examiner for 13 PhDs globally. Key grants include funding from the UK Medical Research Council (HIV/AIDS research), WHO (adolescent safe motherhood), UNICEF (maternal mortality), and USAID (HIV-fertility linkages in Kenya). Recent projects under the Global Challenges Research Fund (GCRF) have established interdisciplinary networks in sub-Saharan Africa. Notable collaborations include studies on rural community health workers during the pandemic, barriers to sexual education in Malawi, and ethnic variations in HIV prevalence in Kenya. Her work aligns with UN Sustainable Development Goals, emphasizing women and children's health in resource-limited settings.

• Quantitative Methods
• Organizational Psychology
• Statistical Modeling
• +1 more

Patrick Rosopa is Professor of Psychology at Clemson University, specializing in quantitative methods and organizational behavior. With industry experience in HR management, his NSF/DoD-funded work develops statistical models for safety, team dynamics, and human-AI collaboration. Research innovations include heteroscedasticity management techniques and multilevel safety compliance frameworks. He co-authored the textbook Statistical Reasoning in the Behavioral Sciences and serves on multiple methodology journal boards. Awards: Distinguished Doctoral Mentoring (2022), Outstanding Contributions to Literature (x3)

• Comparative education policy
• Educational equity and access
• P-16 education assessment
• +4 more

Wenfan Yan is a Professor in the Department of Leadership in Education at the University of Massachusetts Boston . He earned his PhD from the State University of New York at Buffalo and teaches courses on research methods, instrument design, program evaluation, and dissertation seminars. Research Interests: Comparative study and policy analysis of P-16 education equity, access, effectiveness, and assessment Chinese education reform Service-learning in higher education Integration of quantitative and qualitative methodologies Advanced statistical techniques including multilevel modeling His recent research focuses heavily on Chinese education reform and service-learning outcomes , particularly among college students. His work spans over three decades, with publications addressing leadership development, faculty diversity, and the impact of educational policies on student outcomes. Research Trends: Yan's scholarly output reflects a consistent emphasis on comparative education policy and student development . His articles explore the intersection of service-learning and student engagement , especially within the context of Chinese higher education . He also investigates faculty experiences , particularly focusing on Asian American faculty and barriers to advancement in academia. Scientific Contributions: While specific awards are not listed, his extensive publication record from 1991 to 2024 demonstrates significant scholarly impact in the fields of educational leadership , comparative education , and service-learning . Teaching and Advising: Yan teaches graduate-level courses in research methods and dissertation seminars, indicating active involvement in mentoring doctoral students. However, specific student names are not provided in the text.

Sarah SchwartzView profile

Academic

• Clinical Psychology
• Neuroscience
• Educational Psychology
• +5 more

Sarah Schwartz is a Research Assistant Professor and Director of the Statistical Consulting Studio at the Department of Psychology, Utah State University, within the Emma Eccles Jones College of Education and Human Services. Her work focuses on interdisciplinary research spanning clinical psychology, neuroscience, and educational psychology with an emphasis on neurodegenerative diseases, autism spectrum disorders, and mental health literacy. She leads statistical consulting efforts, supporting research design and data analysis across disciplines. Key research areas include: Longitudinal analysis of dementia progression and neuropsychiatric symptom trajectories Genetic and environmental influences on neurodegenerative conditions Autism spectrum disorder diagnostics and caregiver assessment tools Impact of racial/gender bias in special education classification Mental health intervention efficacy and mindfulness practices Her recent publications highlight innovative approaches in: Assessing racial disparities in health trajectories Developing validated measurement tools for social communication deficits Exploring neurotrophin genetics and lifestyle interactions Evaluating ACT-enhanced behavioral therapies No formal academic awards are listed, but her extensive publication record reflects sustained contributions to clinical and educational research. She has advised no formally listed students but actively supports interdisciplinary research teams through her statistical consulting role.

Rodney X. SturdivantView profile

Professor

• Biostatistics
• Applied Statistics
• Logistic Regression
• +5 more

Dr. Rodney X. Sturdivant is a Professor of Statistical Science and Director of the Statistical Consulting Center at Baylor University. He has held roles at institutions including The Ohio State University and Azusa Pacific University, and previously served as a U.S. Army Colonel for 27 years. He founded the West Point Center of Data Analysis and Statistics (CDAS) and holds the academic rank of Professor of Applied Statistics. Education: Ph.D. in Biostatistics (University of Massachusetts Amherst, 2005); M.S. in Statistics and Operations Research (Stanford University, 1995); B.S. from U.S. Military Academy (West Point, 1986). His research focuses on applied statistics and biostatistics, with specialties in categorical data analysis, logistic regression, survival analysis, and innovative educational methods using games. He collaborates across disciplines including public health, sports medicine, and ecology. Notable awards include the Army Wilks Memorial Award (2021) and recognition as a top 2% cited researcher (2023). He has authored influential textbooks like Applied Logistic Regression and pioneered game-based learning approaches for statistics education. His advisory and grant activities include leading statistical consulting initiatives and developing academic programs like the M.S. in Applied Statistics and Analytics at Azusa Pacific. He is affiliated with Baylor’s Marrs McLean Science facility and actively contributes to both academic and military research networks.

• Compassion-Focused Therapy
• Clinical Psychology
• Mental Health Interventions
• +2 more

Jaskaran Basran is a Lecturer in Psychology at the University of Derby's College of Health, Psychology and Social Care. His research focuses on compassion-focused interventions, mindfulness, and group therapies for mental health conditions. Dr. Basran's work explores therapeutic applications of compassion in clinical and community settings, including compassion-focused group therapy for bipolar disorder, music-based compassion interventions, and cross-cultural validation of compassion scales. His recent studies examine psychological responses to collective stressors like the COVID-19 pandemic. Analysis of his 15 most recent publications shows consistent focus on developing and validating psychological instruments for compassion and mindfulness, along with interventions targeting mood disorders and social connectedness. Temporal trends reveal increasing methodological sophistication including multinational studies, physiological measurements, and clinical trials. He collaborates extensively with international teams on cross-cultural validation of psychological scales and multi-country studies on trauma responses. Dr. Basran contributes to advancing measurement methodologies in clinical psychology through item response theory and multilevel modeling approaches.

• Environmental Policy
• Public Health
• Social Psychology
• +5 more

Hamid BULUT is a Postdoctoral researcher at the University of Luxembourg's Department of Social Sciences, Faculty of Humanities, Education and Social Sciences. His research focuses on environmental policy, public health, and social psychology, particularly examining how societal factors influence pro-environmental attitudes and policy acceptance. He has conducted significant work on youth behavior during the COVID-19 pandemic and disaster-related environmental shifts, such as the 2021 European floods. Key research areas include the intersection of social justice and environmental attitudes, the design of effective climate policies (e.g., carbon taxes), and the role of trust in government during public health crises. His interdisciplinary approach combines quantitative methods with behavioral analysis, exemplified by tools like PriorDraw for probability distribution modeling. BULUT’s publications highlight trends in vaccination hesitancy across age groups, youth environmental behavior in Luxembourg, and methodological advancements in multilevel modeling. His work bridges theoretical insights with practical policy implications, emphasizing real-world applications of social science research.

Wolfgang MessnerView profile

Clinical Professor

• Cultural Heterogeneity Measurement
• Cross-Cultural Consumer Behavior
• COVID-19 Socioeconomic Impacts
• +1 more

Wolfgang Messner is a Clinical Professor at the University of South Carolina's Darla Moore School of Business, with a PhD in Economics (University of Kassel), MBA (University of Wales), and MSc/BSc in Informatics & Economics (Technical University Munich). His international career spans academia (MYRA School of Business, IIMs) and industry (Capgemini, BMW, Deutsche Bank). Research focuses on measuring cultural heterogeneity using machine learning, cross-cultural consumer behavior, and COVID-19 socioeconomic impacts. He teaches management consulting, data analytics, and intercultural team management, directing experiential projects with UPS, Positec, and SC Small Business Development Centers. Awards include Emerald Literati Awards and the Moore School Research Award. His publications in Journal of World Business, Journal of International Marketing, and PLoS ONE develop novel methods for cultural measurement and analyze pandemic-related behaviors across societies.

Daniel Fernández MartínezView profile

Associate Professor

• Biostatistics
• Categorical Data Analysis
• Clustering and Classification
• +5 more

Daniel Fernández Martínez is a Serra-Húnter Associate Professor in the Department of Statistics and Operations Research at the Polytechnic University of Catalonia-BarcelonaTech . His roles include adjunct professorships at the Geneva Business School, European University Business School, University of Barcelona, and Open University of Catalonia (2017–2020), as well as a Lecturer in the Department of Epidemiology and Biostatistics at SUNY Albany in 2017. He holds certifications such as the Tenure-track lecturer certification (Professor Lector) and Accreditation of research (Professor Agregat) from AQU Catalunya, and is a member of the CIBERSAM research group . Research Focus: Biostatistics, computational statistics, and statistical modeling with specializations in categorical data analysis, clustering, mixture models, and multilevel/hierarchical models. Professional History: Postdoctoral work at NYU’s Center for Data Science (2016), and roles in clinical research at Sant Joan de Déu Sanitary Park (2017–2020). His work bridges statistics and computer science, emphasizing methodological advancements for ordinal data and rater quality evaluation in crowdsourced tasks.

Donna CoffmanView profile

Associate Professor

• Quantitative Methodology
• Behavioral Health
• Mediation Analysis
• +3 more

Dr. Donna Coffman is an Associate Professor in the Department of Psychology at the University of South Carolina's McCausland College of Arts and Sciences. She specializes in quantitative methodology applied to behavioral health research, focusing on developing statistical methods for analyzing intensive longitudinal data from wearable devices and mobile health interventions. Her work emphasizes causal mediation analysis in contexts like smoking cessation, substance use disorder treatment, and physical activity promotion. Dr. Coffman holds a PhD in Quantitative Psychology from the University of North Carolina, Chapel Hill. Prior to her current role, she held academic positions at Temple University and Pennsylvania State University's Methodology Center. Her research bridges statistical innovation with real-world applications, particularly in designing adaptive health interventions. Her research interests include: Developing mediation analysis techniques for time-varying data Improving causal inference methods in health behavior studies Optimizing wearable sensor data integration in clinical research Analyzing mHealth intervention efficacy Recent work focuses on applications like sleep interventions for children's weight management, spinal cord injury recovery tracking via wearable sensors, and causal pathways in substance use policy impacts. She collaborates across disciplines to advance evidence-based prevention strategies through rigorous methodological frameworks. Notable contributions include methodological toolkits for propensity score weighting and mediation analysis, published in journals like BMC Medical Research Methodology and Journal of Medical Internet Research . Her applied research has addressed topics ranging from e-cigarette use trends to environmental health disparities.