Find Academic Supervisors

Alexander RobelView profile

Associate Professor

• Climate, Oceanography, and Weather
• Cryospheric Science
• Paleoclimate
• +6 more

Dr. Alexander Robel is an Associate Professor in the School of Earth & Atmospheric Sciences at the Georgia Institute of Technology, part of the College of Sciences. His research focuses on climate, oceanography, and cryospheric science, with a particular emphasis on glaciers, ice sheets, and sea level change. He holds a Ph.D. in Earth and Planetary Science from Harvard University (2015) and a B.S. in Physics and Earth Sciences from Duke University (2010). Research Interests: Dr. Robel’s work addresses critical questions in cryospheric science, including ice-ocean interactions, climate modeling, and the dynamics of ice sheets. His studies integrate computational and mathematical modeling to explore topics such as glacier stability, sea level rise, and the impacts of climate variability on polar regions. Key themes include the stochastic parameterization of ice dynamics, the role of subglacial hydrology, and the statistical analysis of climate forcing on glacial systems. Publications Trends: Recent work emphasizes advancing stochastic models for ice sheet projections, quantifying biases in climate-ice sheet interactions, and analyzing oceanic drivers of glacial retreat. His studies often bridge observational data with theoretical frameworks, offering insights into both near-term and long-term climate impacts. Education: Ph.D., Earth and Planetary Science, Harvard University (2015) B.S., Physics and Earth Sciences, Duke University (2010) Advising & Grants: Specific advising or grant details are not explicitly listed in the provided text. Labs/Teams: Likely affiliated with Georgia Tech’s School of Earth & Atmospheric Sciences research groups, though specific teams are not mentioned here.

Erin SchliepView profile

Associate Professor

• Environmental Statistics
• Bayesian Statistics
• Spatial Statistics
• +3 more

Erin Schliep is an Associate Professor in the Department of Statistics at North Carolina State University (NCSU), with a joint appointment as a Research Associate at Duke University. She holds a Ph.D. in Statistics from Colorado State University (2013). Her research focuses on Bayesian statistics, spatiotemporal modeling, and environmental applications, including ecological dynamics and sports analytics. Her work addresses challenges in climate change impacts, species distribution modeling, and marine conservation. Key research areas include spatiotemporal analysis of ecological systems, data fusion methods for environmental monitoring, and causal inference in spatial contexts. She has contributed to studies on lake productivity responses to climate, whale calling patterns, and NBA player performance metrics. Recent projects include NSF-funded work on modeling and uncertainty quantification in life sciences. Her publications span high-impact journals like JASA, PNAS, and Ecology, addressing topics such as marine mammal abundance estimation, algal biomass changes in lakes, and spatial causal inference for marine protected areas. She advises students and collaborates widely, exemplified by her role in the ContLimno team analyzing freshwater ecosystems. Erin’s expertise extends to methodological advancements, including hierarchical modeling, Hawkes processes, and machine learning integration. She emphasizes interdisciplinary applications, bridging statistics with ecology, environmental science, and sports analytics.

Giuseppe VinciView profile

Assistant Professor

• Astrostatistics
• Bayesian Statistics
• Computational Neuroscience
• +8 more

Giuseppe Vinci is an Assistant Professor at the Department of Applied and Computational Mathematics and Statistics (ACMS) at the University of Notre Dame, within the College of Science. His research focuses on probabilistic graphical models, particularly in neuroscience and genomics applications. He holds a Ph.D. in Statistics from Carnegie Mellon University (2017), and completed postdoctoral research and lecturing at Rice University (2017–2020). Vinci’s expertise spans astrostatistics, forensic science, and geometric data analysis. Education: Ph.D. in Statistics, Carnegie Mellon University (2017) M.Sc. in Statistics, Carnegie Mellon University (2013) M.Sc. in Economics and Social Sciences, Bocconi University (2012) B.Sc. in Economics, University of Catania (2009) Research Interests: High-dimensional statistical theory of graphical models, matrix completion, astrostatistics, neuroscience, genomics, forensic science, and geometric data analysis. His work addresses challenges in neuronal functional connectivity, genomic networks, and climate science. Awards: NeuroNex Postdoctoral Trainee (NSF) Rice Academy Postdoctoral Fellow Three-minute thesis competition (Top-10, Carnegie Mellon University) Advising & Grants: Vinci mentors multiple Ph.D., MSc, and undergraduate students in projects spanning forensic statistics, genomics, and astrostatistics. He has secured funding for undergraduate research programs and participated in NIH-funded interdisciplinary training. Labs/Teams: Involved in collaborative projects with institutions like Baylor College of Medicine and Rice University, focusing on neurotheory and statistical methods in neuroscience.

Eric LambView profile

Professor

• Plant Ecology
• Fire Ecology
• Grasslands Conservation
• +3 more

Eric Lamb is a Professor in the Department of Plant Sciences at the University of Saskatchewan, affiliated with the College of Agriculture and Bioresources. He is also the Curator of the WP Fraser Herbarium. His research focuses on plant ecology, fire ecology, and grassland conservation. He holds a Ph.D. from the University of Alberta, an M.Sc. from Lakehead University, and a B.Sc. from the University of British Columbia. Dr. Lamb teaches undergraduate courses including Plant Ecology, Grassland Soils and Vegetation, and Advanced Plant Ecology, as well as graduate courses in statistical and experimental analysis methods. His research explores ecosystem services, invasive species impacts, soil microbiology, and fire management strategies in grassland ecosystems. Key Research Themes: Fire effects on plant communities, microbial interactions in root systems, and conservation strategies for grassland biodiversity. Notable Contributions: Pioneering studies on prescribed fire reintroduction, microbial community dynamics during invasions, and the ecological impacts of grazing regimes. His recent publications emphasize global grassland drought vulnerabilities, Arctic soil biodiversity under climate change, and the role of microbial networks in ecosystem resilience. Dr. Lamb collaborates widely on interdisciplinary projects bridging ecology, conservation, and land management. Lab/Team Activities: Active in the WP Fraser Herbarium’s specimen curation and fieldwork initiatives, focusing on Saskatchewan’s endemic plant species and Arctic tundra restoration.

Susan J. MazerView profile

Professor

• Botany
• Ecology
• Evolution
• +5 more

Susan J. Mazer is a Professor in the Department of Ecology, Evolution, and Marine Biology at the University of California, Santa Barbara. She holds a B.S. in Biology from Yale University (1981), an M.S. in Botany from UC Davis (1983), and a Ph.D. in Botany from UC Davis (1986). Her research focuses on plant adaptation mechanisms, genetic constraints, and evolutionary ecology, integrating quantitative genetics, plant breeding, and field experiments. She leads the Mazer Lab, which investigates topics like mating system evolution, phenological responses to climate, and floral trait evolution in Clarkia and other species. She co-leads the Virtual Center for the Study of Biotic Interactions (ViCSBI), a multi-campus initiative examining climate impacts on ecological interactions. Dr. Mazer advises numerous graduate and undergraduate students and has published extensively on plant ecology, evolution, and phenology. Her work includes developing tools like PhenoForecaster for phenological prediction and leveraging herbarium data for climate research.

Peter KedronView profile

Associate Professor

• Spatial Analysis
• Economic Geography
• GIScience
• +3 more

Peter Kedron is an Associate Professor in the Department of Geography at the University of California, Santa Barbara (UCSB), and a member of the Center for Spatial Data Science. Previously, he held faculty positions at Arizona State University (2018–2023), Oklahoma State University (2016–2018), and Ryerson University (2012–2016). He earned his Ph.D. in Geography from SUNY Buffalo, an MA in Economics from the University of Michigan, and BAs in Economics and Psychology from SUNY Buffalo. His research focuses on spatial analytical methods, particularly replication in geographic research, and improving evidence accumulation through statistical approaches. Key areas include computational reproducibility, spatial causal inference, and the integration of replication into GIScience education. He has published over 55 peer-reviewed articles and been consistently funded by the National Science Foundation (NSF). Dr. Kedron emphasizes bridging spatial data science with policy relevance, addressing challenges in urban inequality, environmental conservation, and healthcare accessibility. His work often employs cutting-edge techniques like digital twins, machine learning, and multi-source remote sensing to address complex spatial problems. He has supervised over 20 graduate students and post-doctoral scholars, fostering a collaborative environment. Notable contributions include frameworks for reproducible geospatial research and studies on urban-rural disparities, wildfire risk, and renewable energy sector dynamics. Labs/Teams: Active in UCSB’s Center for Spatial Data Science and collaborates with interdisciplinary teams on projects funded by NSF and industry partnerships.

Jayajit ChakrabortyView profile

Professor

• Environmental Justice
• Climate Justice
• Disability Justice
• +7 more

Jayajit Chakraborty is a Professor and Mellichamp Chair in Racial Environmental Justice at the Bren School of Environmental Science & Management, University of California, Santa Barbara. He holds a Ph.D. in Geography and M.S. in Urban & Regional Planning from the University of Iowa. His research focuses on environmental justice, climate justice, disability justice, and disaster vulnerability, employing GIS and mixed-methods approaches. Education: Ph.D. in Geography, University of Iowa M.S. in Urban & Regional Planning, University of Iowa Research Interests: Social dimensions of climate and environmental change Racial/ethnic and disability-based environmental disparities GIScience applications in environmental justice Food security and health equity Grants & Awards: Funded by NSF, EPA, Australian Research Council, and other agencies Recipient of University of Texas System Faculty STARs Award NSF Geospatial Fellowship (2021) Top 2% cited researcher (Stanford-Elsevier ranking) Committee Roles: National Academies Committee on Geospatial Data & Community Investment EPA Science Advisory Board (former member) EPA EJScreen Mapping Tool Review Panel (chair) Health Effects Institute’s CHERI Research Committee Labs & Teams: Former director of the Socio-Environmental & Geospatial Analysis Lab at University of Texas, El Paso. Currently leads interdisciplinary projects at Bren School.

• Spatial Statistics
• Statistical Modeling
• Environmental Statistics
• +3 more

Dr. Emiko Dupont is a Lecturer in the Department of Mathematical Sciences at the University of Bath. Her research focuses on spatial statistics, spatial confounding, and nonlinear covariate effects with applications in environmental systems and river flow dynamics. Her research interests center on developing statistical methodologies for spatial data analysis, particularly addressing challenges in spatial confounding and covariate effects. She investigates both theoretical frameworks and practical applications in environmental statistics. Dr. Dupont's recent publications demonstrate a consistent focus on spatial statistical methods, with emerging applications in hydrological systems and Bayesian frameworks. Her work contributes to methodological advancements in spatial modeling. She is currently involved in research projects including 'New advances in spatial data analysis' (2022-2024) funded by the London Mathematical Society and 'JSM travel' (2025).

Daphne A. HenryView profile

Assistant Professor

• Racial Inequities in Education
• Socioeconomic Status (SES) and Child Development
• Parental Beliefs and Practices
• +4 more

Daphne A. Henry is an Assistant Professor at the University of Pittsburgh, specializing in child development and educational equity. Her research focuses on intersections of race/ethnicity, socioeconomic status (SES), and family dynamics on children’s academic and socioemotional outcomes. She employs mixed-methods approaches, including large-scale data analysis and qualitative studies. Henry’s work emphasizes policy-relevant insights into reducing disparities in early development and long-term well-being. Her education includes a Ph.D. from the University of Pittsburgh. She has received prestigious awards such as the National Academy of Education/Spencer Foundation Postdoctoral Fellowship (2022) and the NSF Graduate Research Fellowship (2012–2015). Her lab investigates topics like parental beliefs, structural inequities, and resilience during crises like the COVID-19 pandemic. Key Research Areas: Racial inequities in education, family resilience, and SES disparities in child development Methodological Toolkit: Statistical analysis, qualitative data, mixed-methods Henry’s recent work explores how socioeconomic and racial factors shape academic achievement gaps and the role of parental practices in mitigating risks. She has published extensively on topics like racial stereotypes, critical consciousness, and family well-being during crises. Awards: Over six major fellowships and awards spanning 2012–2022 Grants: Not explicitly listed but implied through research focus She advises graduate students and is affiliated with the Learning Research and Development Center (LRDC) at the University of Pittsburgh.

Benjamin C. PierceView profile

Professor

• Programming Languages
• Type Systems
• Formal Verification
• +3 more

Benjamin C. Pierce is Henry Salvatori Professor of Computer and Information Science at the University of Pennsylvania, with appointments in the School of Engineering and Applied Science. A Fellow of the ACM, his research spans programming languages, formal verification, and security-privacy technologies. He directs the DeepSpec project on verified systems infrastructure and leads climate computing initiatives. Research interests focus on: Formal methods for reliable software via proof assistants like Coq Bidirectional programming and data synchronization Language-based security and differential privacy Publication trends show consistent contributions to type theory foundations, with recent emphasis on property-based testing methodologies and real-world verification. Articles frequently appear in top PL/SEC venues with practical applications in compilers and secure systems. Scientific Awards: ACM Fellow (systems verification) SIGPLAN Distinguished Educator Award (textbook innovations) Advises graduate students through the Penn PL Club. PI for NSF Expeditions in Sustainable Computing. Leads the VERSE project for verified C code and Unison file synchronizer. Directs the Penn Programming Languages Research Group collaborating with industry partners including Amazon and Microsoft Research.

• Monetary Policy
• Fiscal Policy
• Macroeconomics
• +4 more

Giovanni Di Bartolomeo is the Dean of the Faculty of Economics and a Professor at Sapienza University of Rome. He holds additional positions including Advisor to the European Parliament, Member of the Experts Council of the Italian Ministry of Economy and Finance, Senior Fellow at the Luiss Institute for European Analysis and Policy, and co-founder of the Centre for Investigation and Modelling of Experimental Observations (CIMEO). His research focuses on monetary and fiscal policy, macroeconomics, experimental economics, and environmental policy. Di Bartolomeo studied at Sapienza University of Rome and Pompeu Fabra University (Barcelona), earning an MSc and PhD. His work spans ECB policy analysis, climate change mitigation, and the impact of large-scale events like the Euro 2020 on regional economies. He has contributed to evaluating Italy’s Recovery and Resilience Plan and addressing stagflation risks in the Eurozone. His recent publications examine topics such as carbon taxation, financial dominance in the eurozone, and behavioral macroeconomic modeling. Notably, he explores guilt aversion in experimental settings and the strategic dynamics of scarce resources. Di Bartolomeo’s research emphasizes policy resilience, fiscal-monetary coordination, and the long-term implications of short-term political decisions. He has advised on structural reforms, sovereign debt crises, and pandemic fiscal responses. His contributions to public economics and macroeconomic resilience have been published in specialized journals and policy reports.

Jessie P. BuckleyView profile

Associate Professor

• Environmental Epidemiology
• Children's Environmental Health
• Exposure Assessment
• +7 more

Jessie P. Buckley is an Associate Professor at the Johns Hopkins University's Department of Environmental Health and Engineering. She is affiliated with the Wendy Klag Center for Autism and Developmental Disabilities and the Environmental influences on Child Health Outcomes (ECHO) Data Analysis Center. Her research focuses on early-life environmental chemical exposures and their impacts on children's health, including asthma, obesity, and developmental disorders. Dr. Buckley holds a PhD from the University of North Carolina at Chapel Hill (2014), an MPH from George Washington University (2007), and an AB from Bowdoin College (2002). Her work integrates epidemiologic methods with exposure assessment, examining chemical mixtures such as phthalates, PFAS, and organophosphate esters. Key themes include understanding how prenatal and childhood exposures to endocrine disruptors influence growth, metabolic health, and neurodevelopment. She has led studies on the health implications of ultra-processed food consumption and environmental pollutants in vulnerable populations. Publications highlight her contributions to understanding preterm birth disparities linked to phthalate exposure, the role of environmental exposures in pediatric asthma, and the application of statistical methods like item response theory to analyze chemical mixture effects. Collaborations span institutions including the NIH's ECHO Program and international cohorts in Bangladesh. Dr. Buckley's research has informed policy discussions on reducing chemical exposure risks, particularly for pregnant women and children. She advises on environmental health projects and mentors teams exploring innovative approaches to exposure burden measurement. Current initiatives focus on longitudinal studies of chemical mixtures and their interactions with genetic and social factors.

Ioannis KyriakouView profile

Professor

• Actuarial Science
• Quantitative Finance
• Financial Mathematics
• +13 more

Professor Ioannis Kyriakou is a leading academic in actuarial finance and quantitative methods at Bayes Business School, City St George's, University of London, where he serves as Professor of Actuarial Finance and Director of the MSc in Actuarial Science and MSc in Actuarial Management. He holds a visiting professorship at the University of Eastern Piedmont and has previously served as affiliate faculty at the Cyprus International Institute of Management. His research spans actuarial science, derivatives pricing, risk management, computational finance, and machine learning applications in finance and insurance. His research interests focus on quantitative finance , stochastic modeling , numerical methods , and machine learning , particularly in the context of derivative pricing , pension product design , energy and commodity markets , and investor sentiment . He has developed advanced computational techniques such as moment-based approximations and transform methods for financial modeling. His work integrates simulation, optimization, and data-driven approaches to solve complex financial and actuarial problems. The recent publications reflect a strong trend toward interdisciplinary research, combining machine learning with financial economics , energy efficiency forecasting , mutual fund performance , and climate risk . His work frequently appears in top journals like Operations Research , Journal of Financial and Quantitative Analysis , and European Journal of Operational Research , showcasing expertise in both theoretical and applied finance. European Journal of Operational Research (2020) Editors' Award for Excellence in Reviewing Cass Business School (2014) Prize for Excellence in Teaching and Learning Dimitris N. Chorafas Foundation (2009) Prize for outstanding PhD research work EPSRC Doctoral Training Award (2008) He supervises several PhD students in areas such as derivatives pricing, machine learning in actuarial science, and pension optimization. He has received research support through editorial leadership, consultancy (e.g., with Lloyd’s Treasury), and academic collaboration. He is actively involved in organizing conferences and workshops, including the Finance and Business Analytics Conference. He is affiliated with research groups focusing on financial modeling , actuarial computation , and machine learning in insurance , contributing to both academic and industry-facing initiatives. His co-authored book Machine Learning in Insurance (MDPI, 2020) highlights his leadership in bridging data science with actuarial applications.

Xuebin ZhangView profile

Assistant Professor

• Climate Change Detection and Attribution
• Climate Extremes
• Weather and Climate Extremes
• +7 more

Xuebin Zhang is an Assistant Professor in the Department of Geography at the University of Victoria and serves as the Director, President, and CEO of the Pacific Climate Impacts Consortium (PCIC). His role combines academic research with leadership in applied climate science, focusing on regional climate impacts in Canada and globally. Institution: University of Victoria School: Faculty of Social Sciences Department: Department of Geography Leadership: Director, President & CEO, PCIC Dr. Zhang holds a PhD from Lisbon, an M.Eng, and a B.Eng from Hohai University. His research centers on the detection and attribution of climate change, particularly focusing on weather and climate extremes at regional and global scales. He has made significant contributions to understanding how human activities influence extreme precipitation and temperature events. His recent publications demonstrate a strong trend in analyzing extreme climate events using advanced statistical methods such as optimal fingerprinting and Bayesian analysis. These studies often involve large international collaborations and utilize climate model simulations (e.g., CMIP6) to attribute observed changes to anthropogenic forcing. Key areas include extreme precipitation, temperature variability, drought, and flood events across North America and China. Dr. Zhang has been deeply involved in major scientific assessments: Coordinating Lead Author, IPCC 6th Assessment Report (Working Group I, Chapter on Extremes) Co-chair, Expert Team on Climate Change Detection and Indices (WCRP) Co-chair, Grand Challenge on Weather and Climate Extremes (WCRP) Fellow of the Royal Society of Canada He leads and mentors a broad team of scientists at PCIC, overseeing projects related to climate analysis, hydrologic impacts, and computational support. While specific student names are not listed, his leadership role implies extensive supervision of postdoctoral researchers and graduate students. He has secured significant research funding through PCIC and federal programs to support climate modeling, monitoring, and impact assessments. His work directly informs policy and adaptation planning in British Columbia and across Canada.

Bin PengView profile

Professor

• Econometrics
• Panel Data Analysis
• Time Series Analysis
• +3 more

Bin Peng is a Professor in the Department of Econometrics and Business Statistics at Monash University. His research focuses on developing novel econometric models and methods, particularly in panel data analysis, time series econometrics, and climate data modeling. He holds a PhD in Econometrics from Monash University (2013) under Professors Giovanni Forchini and Don Poskitt, preceded by a BSc in Mathematics from Nanjing University (2007). His work addresses structural changes in factor models, time-varying parameters in vector error-correction frameworks, and productivity convergence in manufacturing sectors. Key contributions include nonparametric panel models for climate data and methodologies for handling interactive effects in panel data with general factors. Peng has received multiple Dean’s Awards, including the 2021 Early Career Research Excellence Award, 2023 Commendation for Excellence, and 2024 Researcher of the Year. He leads a 2021–2025 project on modeling time trends in panel data, funded by Monash University. His recent articles (2021–2025) emphasize methodological advancements in econometric theory, applied to climate science, economic growth, and macroeconomic policy.