Find Academic Supervisors

• Cardiovascular Physiology
• Exercise Physiology
• Chronic Disease Prevention
• +3 more

Winthrop Professor Daniel Green is a leading academic in cardiovascular exercise physiology at the University of Western Australia (UWA), based in the School of Human Sciences. He holds a PhD from UWA and has been a NHMRC Principal Research Fellow (2015-2021). His work focuses on preventing chronic diseases like atherosclerosis, diabetes, and heart failure through exercise interventions, with a focus on translational research and technological innovations such as optical computed tomography for vascular assessment. Prof Green has supervised over 90 thesis students and leads the Cardiovascular Research Group at UWA, collaborating internationally with institutions like Mayo Clinic and the University of Oregon. He has secured $14.9 million in competitive grants and pioneered initiatives like the International Summer School for Ultrasound in Cardiovascular Science and Medicine. His awards include the Vice-Chancellor’s Senior Research Award (2022). Research interests include exercise training effects on vascular health, imaging techniques for disease assessment, and personalized interventions for chronic disease prevention. His lab develops tools to detect early-stage chronic diseases and optimize lifestyle interventions.

Jeremy DawsonView profile

Professor

• Health Management
• Organizational Behavior
• Healthcare Outcomes
• +5 more

Jeremy Dawson is a Professor of Health Management at the University of Sheffield, jointly affiliated with the Institute of Work Psychology (within the Management School) and the School of Health and Related Research (ScHARR). He holds a PhD from Aston University (2011). His research focuses on NHS staff experience, team dynamics, healthcare outcomes, and statistical methodology. Key areas include staff retention, equality/diversity in healthcare, and the impact of organizational practices on patient outcomes. He advises the NHS on staff surveys and diversity initiatives, including roles in the NHS Staff Survey Advisory Group and the NHS Race and Health Observatory. He has led major projects such as the Retention of Mental Health Staff (RoMHS) study and the Multiple Symptoms Study 3 (MSS3), evaluating interventions for persistent physical symptoms. His statistical contributions include methodological work on interaction effects and team behavior analysis. Teaching responsibilities include advanced statistics modules for health science researchers and workshops on research methods. He supervises PhD students in areas like leadership wellbeing, healthcare staff wellbeing, and NHS board diversity. Publications span over 70 peer-reviewed articles in journals like Journal of Applied Psychology and Health Services and Delivery Research . He serves on editorial boards, including Organizational Research Methods . His work bridges organizational behavior and healthcare, emphasizing practical applications of statistical rigor.

Daniel IerodiaconouView profile

Professor

• Marine Ecology
• Environmental Management
• Geology
• +6 more

Professor Daniel Ierodiaconou is a marine ecologist at Deakin University, where he serves as Professor in Marine Science and leads the Deakin Marine Mapping Group. He acts as Victorian Node Leader for the Integrated Marine Observing System (IMOS), Board Director for the Great Ocean Road Coast and Parks Authority, and Coastal Lead Scientist for the CoastRI Initiative. His work combines multi-disciplinary approaches to advance marine ecosystem-based management. Doctor of Philosophy, Deakin University Bachelor of Science (Aquatic Science), Deakin University Bachelor of Science (Fisheries Management & Aquaculture), Deakin University Daniel's research focuses on Benthic Habitat Mapping , Marine Protected Areas , and Coastal Process Monitoring . His work integrates Remote Sensing , Image Classification , and Change Detection techniques to inform marine conservation and climate adaptation strategies. Recent publications highlight advancements in Seafloor Habitat Classification , Coastal Erosion Modeling , and Seagrass Restoration . Scientific awards include: 2020 Eureka Prize for Innovation in Citizen Science 2020 Victorian Coastal Award for Innovative Applied Research 2018 Victorian Coastal Award for Partnership Research 2009 Tall Poppy Award Daniel supervises 10 current doctoral students and has advised 16 PhD completions. His grants portfolio exceeds $7 million, including a $5 million NCRIS-funded CoastRI Coastal Monitoring Network. He specializes in integrating Geospatial Technologies with Marine Conservation through his leadership in citizen science drone programs and Victoria's first wave buoy network.

Elmar TeuflView profile

Senior Lecturer

• Random Walks on Graphs
• Combinatorics
• Probability Theory
• +3 more

Elmar Teufl is a Senior Lecturer in the Department of Mathematics at Eberhard Karls Universität Tübingen. He holds a Doctorate (2002) and a Habilitation (2015) from Graz University of Technology and Tübingen University, respectively. His research focuses on random walks on graphs and groups, combinatorial problems on self-similar structures, asymptotic methods, and fractal geometry. His work bridges probability theory, combinatorics, and graph theory with applications to fractal networks and recursive systems. Teufl has held academic positions across Europe, including visiting professorships at the University of Stuttgart (2012–2013) and a Marie Curie Fellowship at Bielefeld University (2005–2006). His research has been supported by the Austrian Science Fund (FWF) and the EU. Key achievements include contributions to spanning tree enumeration on Sierpinski graphs and resistance scaling in self-similar lattices. His publications span topics like asymptotic enumeration, determinant identities for Laplacian matrices, and structural properties of nilpotent groups. He received the Austrian Mathematical Society's Studienpreis (2003) for his thesis on self-similar graphs and fractals. Teaching responsibilities include advanced courses in combinatorics and probability, with a full teaching record documented in alma.

David LuitzView profile

Professor

• Quantum Many-Body Systems
• Condensed Matter Physics
• Theoretical Physics
• +3 more

David Luitz is a Professor of Theoretical Physics at Bonn University, specializing in quantum many-body systems. His research focuses on fundamental aspects of quantum dynamics, including many-body localization, quantum information spreading, and non-equilibrium thermodynamics. He develops advanced numerical methods and software tools such as the DanceQ library to tackle complex many-body problems. His work bridges theoretical physics with computational techniques, addressing topics like entanglement entropy, out-of-time-order correlators, and phase transitions in interacting quantum systems. Key research areas include the interplay between disorder and thermalization, quantum chaos, and the application of quantum Monte Carlo methods to study correlated electron systems. His contributions have advanced understanding of eigenstate thermalization, dissipative dynamics, and topological phenomena in condensed matter systems. Dr. Luitz’s publications highlight innovations in numerical algorithms for many-body systems and experimental predictions for quantum phase transitions. His work often explores the boundaries between localized and thermalizing regimes, with applications to both theoretical and computational physics.

Bryan WardView profile

Assistant Professor

• Real-Time Systems
• Embedded Systems Security
• Cyber-Physical Systems
• +3 more

Bryan Ward is an Assistant Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. His research focuses on enhancing the security and resilience of real-time and embedded systems in critical domains such as industrial control systems and space systems. Ward holds a Ph.D. in Computer Science from the University of North Carolina at Chapel Hill, along with dual bachelor's degrees in Computer Science and Engineering and Mathematics from Bucknell University. His academic contributions span multiple areas including operating system security, real-time scheduling, and hardware-software co-design for safety-critical systems. Key research themes include control-flow integrity, secure resource management in multi-core environments, and mitigating timing-based attacks in real-time embedded systems. Ward's work has explored advanced defense mechanisms like dynamic address space randomization, tagged architecture implementations, and retry-free transactional memory models. He has also investigated vulnerabilities in kernel scheduling and cache-sharing behaviors in multi-core platforms, proposing novel solutions to ensure predictability and security. Current projects emphasize securing cyber-physical systems through adaptive defenses that maintain strict timing guarantees required for safety-critical applications.

Xiaofeng ZhuView profile

Professor

• Genetic Epidemiology
• Statistical Genetics
• Genetic Association Analysis
• +5 more

Xiaofeng Zhu, PhD is a Professor in the Department of Population and Quantitative Health Sciences at Case Western Reserve University School of Medicine. He also serves as faculty at the Cleveland Institute for Computational Biology. His research focuses on developing statistical methods and computational tools for analyzing genetic and genomic data, particularly in the context of association analysis, admixture mapping, and rare variant identification. He leads the Continental Origins and Genetic Epidemiology Network (COGENT) consortium and has identified multiple genetic loci associated with blood pressure, sleep disorders, and Alzheimer's disease. Education: Ph.D. in Biostatistics, Epidemiology and Biostatistics, Case Western Reserve University (1998) M.S. in Statistics, University of Cincinnati (1994) M.S. and B.Sc. in Mathematics, Peking University (1989, 1986) Research Interests: Dr. Zhu's work emphasizes statistical genetics, including the development of methods to control population stratification, admixture mapping in admixed populations, and cross-phenotype association analyses. His lab integrates deep learning and bioinformatics to study complex traits such as cardiovascular disease, obesity, and sleep disorders. Recent efforts include analyzing whole-genome sequencing data to uncover rare variants influencing phenotypic variation. Publications Trends: His recent work spans Mendelian randomization methods (e.g., MRBEE), gene-sleep interaction studies, and multi-ancestry genomic analyses. Key themes include causal inference, pleiotropy analysis, and leveraging diverse genetic datasets to improve polygenic risk scores. Awards & Memberships: Fellow of the Royal Statistical Society Member, American Society of Human Genetics Member, International Genetic Epidemiology Society Advising & Grants: He has mentored 3 Master’s students, 9/10 PhD graduates, and 11/12 postdoctoral researchers. Notable mentees hold positions at Harvard, Mayo Clinic, and NIH. Active grants include studies on sleep health metrics, lipid loci discovery, and cardiovascular disease genetics. Labs & Teams: Leads COGENT consortium and collaborates with the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. His lab develops software tools for ancestry inference, rare variant analysis, and epigenetic association studies.

Karun AdusumilliView profile

Assistant Professor

• Econometrics
• Causal Inference
• Missing Data
• +6 more

Karun Adusumilli is an Assistant Professor of Economics at the University of Pennsylvania, affiliated with the Department of Economics within the School of Arts and Sciences. He holds a PhD from the London School of Economics (2018), an MSc in Econometrics and Mathematical Economics (2013), and a B.Tech in Engineering Physics from the Indian Institute of Technology, Delhi (2011). His research focuses on advanced econometric methodologies, including causal inference, missing data analysis, dynamic treatment allocation, and reinforcement learning applications in economics. Education: PhD in Economics, LSE (2018) MSc Econometrics and Mathematical Economics, LSE (2013) B.Tech in Engineering Physics, IIT Delhi (2011) Adusumilli’s research interests span Econometrics , Causal Inference , Dynamic Treatment Regimes , and Statistical Learning . He has pioneered work on optimal policy design in bandit experiments, minimax allocation strategies, and addressing unobserved heterogeneity in econometric models. His contributions bridge theoretical econometrics with practical applications in healthcare, education policy, and sequential decision-making frameworks. He has received notable awards, including the Kravis Award for Teaching Excellence (2021) and the John Hicks Prize for his doctoral research (2019). His publications appear in top-tier journals like Econometrica and Review of Economic Studies . Adusumilli teaches graduate and undergraduate courses in econometrics and statistical learning, including Econometrics I and Econometric Machine Learning . He has served on scientific committees for major conferences such as the NBER-NSF Time Series Conference and the AEA-ASSA Annual Meetings .

Livia A. CarvalhoView profile

Senior Lecturer

• Neuropsychopharmacology
• Psychoneuroimmunology
• Precision Medicine
• +7 more

Dr. Livia A. Carvalho is a Senior Lecturer in Neuropsychopharmacology at Queen Mary University of London's Faculty of Medicine and Dentistry, within the Clinical Pharmacology and Precision Medicine department at the William Harvey Research Institute. She holds an honorary Senior Lecturer position at the University of Malaga's Department of Psychobiology and is a Fellow of both the Institute of Clinical Research and the Higher Education Academy. Education: BSc in Pharmacology and Biochemistry from University of São Paulo, Brazil MSc in Neurosciences from University of São Paulo PhD in Pharmacology from University of São Paulo Postdoctoral training at King's College London (with Prof. Carmine Pariante) and University College London (with Prof. Andrew Steptoe) Research Interests: Her work focuses on immunophenotyping depression to improve disease stratification and identify novel drug targets. This involves laboratory-based experiments, clinical trials, and epidemiological studies. Key themes include inflammation-driven mental health pathways, precision medicine for mental illnesses, and translational approaches linking molecular and clinical data. Teaching & Mentoring: Dr. Carvalho leads the 'Brain Behaviour and Immunity' module and co-leads 'Clinical Pharmacology and Drug Safety Assessment'. She advises MBBS and Biomedical Sciences students and has mentored over 20 researchers, many of whom have achieved academic or industry success. Notable trainees include Daisy Fancourt (UCL) and Ann Liljn (University Hospital of Northern Sweden). Awards & Recognition: Young Investigator Awards from NARSAD, ECNP, and the British Association for Psychopharmacology American Psychosomatic Society Award Fellowships in Clinical Research and Higher Education Collaborations & Funding: Her collaborations include Prof. Magdi Yaqoob and Prof. Helen Warren (internal) and Prof. Glyn Lewis (external). Sponsors include Barts Charity. She reviews for journals like Brain, Behavior, and Immunity and evaluates grants for the Medical Research Council and National Institute of Health Research. Labs & Teams: Active in the Psychobiology Group at UCL and the Clinical Pharmacology team at Queen Mary. Her research group includes members like Luis de Souza Teodoro and Christopher Clesse.

• Nutritional Immunology
• Maternal and Infant Nutrition
• Lipid Metabolism
• +3 more

Catherine Field is a Professor in the Department of Agricultural, Food and Nutritional Science at the University of Alberta, affiliated with the Faculty of Agricultural, Life & Environmental Sciences. She holds a PhD from the University of Alberta and is a Fellow of the Canadian Academy of Health Sciences (FCAHS) and a Canada Research Chair (CRC) Tier 1 in Human Nutrition and Metabolism. Her primary research focuses on nutritional immunology, particularly the impact of lipids like docosahexaenoic acid (DHA) and arachidonic acid (ARA) on immune system development, cancer therapy, and maternal-infant health. Key educational background includes her PhD in Nutrition from the University of Alberta. Her work spans clinical and preclinical studies, including investigations into DHA's role in enhancing cancer treatments, maternal nutritional status during pregnancy, and the prevention of allergies through early-life dietary interventions. She leads the Alberta Pregnancy Outcomes and Nutrition (APrON) cohort study, examining maternal and infant nutrition's long-term effects. Research interests include lipid metabolism, nutritional programming of immunity, and the interplay between diet and cancer. Awards include the prestigious CRC Tier 1 Chair, recognizing her leadership in human nutrition research. Her lab is located in the Li Ka Shing Centre for Health Research Innovation. Publications highlight her contributions to understanding DHA's effects on breast cancer cells, immune tolerance in allergy models, and maternal vitamin D and iron status during pregnancy. Collaborations include studies on fiber interventions in pediatric populations and the gut microbiome's role in health outcomes.

• Family Well-being
• Social Policy Analysis
• Health Inequities
• +3 more

Dr. Deanna Williamson is an Associate Professor in the Department of Human Ecology at the University of Alberta, within the Faculty of Agricultural, Life and Environmental Sciences. Her research focuses on family well-being, particularly examining how social, economic, and political conditions influence family functioning in diverse populations. She leads a critical ethnographic project exploring family processes among families with young children facing socioeconomic challenges and ethno-cultural diversity. Williamson has secured significant grants, including a SSHRC grant (2013–2018) totaling $489,000 and a Teaching Enhancement Fund grant for field supervisor engagement in practicum programs. Her work critiques welfare-to-work policies and their impacts on low-income families, emphasizing health inequities, child development, and systemic marginalization. She collaborates with interdisciplinary teams and has contributed to randomized controlled trials evaluating service integration approaches for disadvantaged families. Williamson actively supervises graduate students researching topics like urban Indigenous family dynamics, disability-inclusive family processes, and poverty reduction strategies. Publications span themes such as work-life balance, maternal employment effects, policy fragmentation, and cross-cultural research methodologies. She advocates for participatory approaches in community-based research, particularly with immigrant/refugee populations, ensuring marginalized voices inform policy and practice. Williamson’s scholarship bridges academic research with actionable insights for social and health systems reform.

Javier OrlandiView profile

Assistant Professor

• Neuroscience
• Complexity Science
• Statistical Physics
• +5 more

Javier Orlandi is an Assistant Professor in the Department of Physics and Astronomy at the University of Calgary, where he leads the Complex Neural Systems Lab as a Canada Research Chair. His research bridges systems neuroscience, complexity science, and statistical physics, focusing on understanding distributed coding principles in the brain and their impact on perception and learning. He employs computational and experimental approaches, including large-scale calcium imaging and optogenetic manipulation, in collaboration with institutions such as the Hotchkiss Brain Institute and the Computational Neuroscience Platform. Orlandi earned his Ph.D. in Physics from the University of Barcelona (2015), studying spontaneous activity in neuronal cultures. Subsequent postdoctoral research included work at the University of Barcelona (2015–2016) on Huntington’s disease, followed by the University of Calgary (2016–2019) and RIKEN Center for Brain Science in Japan (2019–2022), where he explored cortical processing during decision-making. His research has addressed criticality in neural systems, network inference, and the impact of genetic mutations on brain activity. Key areas of interest include self-organized criticality, neuro-glia communication, and the development of tools like NETCAL for analyzing calcium imaging data. Orlandi has organized challenges to advance connectomics and holds the Eyes High Postdoctoral Fellowship and Canada Research Chair awards. His work integrates theoretical models with experimental data to uncover fundamental principles of neural computation. Affiliations: Complexity Science Group, Hotchkiss Brain Institute, Computational Neuroscience Platform Education: Ph.D. in Physics (University of Barcelona, 2015) Grants: Canada Research Chair, Eyes High Postdoctoral Fellowship Labs: Complex Neural Systems Lab at University of Calgary

Jeremy FoxView profile

Professor

• Community Ecology
• Ecological Restoration
• Mathematical Ecology
• +4 more

Jeremy W. Fox is a Professor in the Department of Biological Sciences at the University of Calgary. He holds a PhD in Ecology and Evolutionary Biology from Rutgers University (2000) and a BA from Williams College (1995). His work focuses on community assembly processes, combining experimental and theoretical approaches with microbial systems. Key interests include dispersal effects, ecosystem function, and the dynamics of competitive interactions. Research highlights include challenging the Intermediate Disturbance Hypothesis (2013), quantifying biodiversity's role in ecosystem stability (2013), and analyzing meta-analytic approaches in ecology (2022). His lab explores how environmental fluctuations and species traits influence community structure and stability. Fox has been recognized with awards including the British Ecological Society Early Career Award (2007) and Alberta Ingenuity grants (2005-2007). Teaching includes courses on quantitative biology (ECOL 425, BIOL 315). His work emphasizes experimental rigor, theoretical frameworks, and open science practices. The Fox Lab's research spans ecological restoration, food web dynamics, and evolutionary ecology, with a focus on long-term community processes and their applied implications.

Wendy ChanView profile

Assistant Professor

• Educational Statistics
• Generalization of Research Findings
• Statistical Methods in Education
• +3 more

Wendy Chan is an Assistant Professor in the Human Development and Quantitative Methods Division at the University of Pennsylvania's Graduate School of Education. Her expertise lies in educational statistics, focusing on improving statistical models to enhance the generalization of research findings from small-scale studies to broader populations. She holds a Ph.D. in Statistics from Northwestern University and has experience teaching mathematics in New York City through Teach for America. Education: Ph.D. in Statistics, Northwestern University Teach for America, New York City middle school teaching experience Research Interests: Dr. Chan's work addresses challenges in scaling up educational interventions and improving generalization from localized trials. She explores statistical methodologies such as propensity score methods, robust estimation, and small-area estimation to tackle issues like model assumption violations and limited data. Her current projects include assessing generalization assumptions, evaluating robust estimation approaches, and analyzing heterogeneous treatment effects. Grants & Projects: Spencer Foundation: Investigating covariates, matching, and longitudinal population changes in generalization. IES: Conceptual replication of the HOPS program for ADHD organizational skills. PCORI: Reducing disparities in ADHD behavioral therapy access for low-income families. Labs/Teams: Collaborates on interdisciplinary projects, including the longitudinal study of novice teachers' role-identities and behavioral health interventions in pediatric care.

Alexandre PoirierView profile

Associate Professor

• Econometrics
• Causal Inference
• Quantile Regression
• +3 more

Alexandre Poirier is the Provost’s Distinguished Associate Professor of Economics at Georgetown University, where he has held positions since 2018. He previously served as an Assistant Professor at the University of Iowa (2013–2018). He holds a Ph.D. in Economics from UC Berkeley (2013), an M.A. in Statistics (2011), and a B.Sc. in Mathematics and Economics from Université de Montréal (2007). His research focuses on econometric theory, causal inference, and sensitivity analysis, with publications in top journals like Econometrica , Journal of Econometrics , and Quantitative Economics . He develops statistical software tools, including Stata modules regsensitivity and tesensitivity , and serves as an Associate Editor for Journal of Business & Economic Statistics and Econometric Reviews . His work emphasizes robustness to unconfoundedness assumptions and omitted variable bias. He teaches advanced econometrics at the Ph.D. and undergraduate levels, including courses on causal inference and panel data methods. Education Ph.D. in Economics, UC Berkeley, 2013 M.A. in Statistics, UC Berkeley, 2011 B.Sc. in Mathematics and Economics, Université de Montréal, 2007 Research Interests Prof. Poirier’s research bridges econometric theory and applied methods, with a focus on identifying causal effects under relaxed assumptions. Key areas include quantile regression, instrumental variables, sensitivity analysis for unobserved confounding, and panel data models. His work often addresses practical challenges in policy evaluation, such as omitted variable bias and endogeneity. Recent contributions include frameworks for comparing sensitivity parameters and assessing robustness of treatment effect estimates. Grants and Software Developed regsensitivity and tesensitivity Stata packages for regression and treatment effect sensitivity analysis Recipient of grants from the National Science Foundation and UC Berkeley’s Graduate Division Professional Service Associate Editor, Journal of Business & Economic Statistics (2021–present) Associate Editor, Econometric Reviews (2024–present) Moderator, arXiv Econometrics Section (2025–present) Referee for leading journals including American Economic Review , Econometrica , and Journal of the American Statistical Association