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 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 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.
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. 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. 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.
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. 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.
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 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 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.
Yuan Pei is an Associate Professor in the Department of Mathematics at Western Washington University (WWU), WA. He previously held roles including Assistant Professor at WWU (2018–2024), Postdoctoral Associate at University of Nebraska-Lincoln (2015–2018), and Visiting Assistant Professor at Ursinus College (2014–2015). His academic journey includes a PhD in Applied Mathematics (2014) and MS in Statistics (2013) from the University of Southern California, and a BS in Mathematics from Peking University (2008). His research focuses on qualitative properties and numerical simulations of partial differential equations (PDEs) arising in fluid dynamics and geophysics. Recent work includes studies on data assimilation techniques, Boussinesq equations, Navier-Stokes equations, and geophysical fluid dynamics models. His publications emphasize rigorous mathematical analysis alongside computational methods for fluid systems. Outside academia, Pei enjoys reading across diverse genres, sports (hiking, running, swimming), and exploring art and culture through museums and travel.
Sancho Salcedo Sanz is a Full Professor at the Universidad de Alcalá, affiliated with the Signal Theory and Communications Department and the GHEODE Research Group. His work focuses on applying machine learning and optimization techniques to energy systems, climate science, and environmental modeling. He holds PhDs from Universidad Complutense de Madrid (2019) and Universidad Carlos III de Madrid (2002). Key research interests include deep learning for energy price prediction, spatio-temporal climate analysis, and hybrid models for renewable energy forecasting. His GHEODE group develops optimization algorithms for network design and distributed systems. Recent publications highlight advancements in extreme weather prediction, smart grid optimization, and explainable AI for environmental monitoring. He has pioneered methodologies like Autoencoder-based flow analogues for heatwave reconstruction and multi-method ensembles for energy demand modeling. Labs/Teams: Leader of the GHEODE Group, specializing in modern heuristics and network design. Collaborates extensively on interdisciplinary projects combining AI with environmental and engineering applications.
Dr. Quinn Webber is an Assistant Professor at the University of Guelph's Department of Integrative Biology, College of Biological Science. His research focuses on the causes and consequences of animal behavior, particularly in bats and caribou. He examines how individual behavioral variation and environmental factors influence fitness and disease outcomes, leveraging contemporary statistical methods to analyze ecological scales. His work contributes to One Health initiatives and species conservation. Research Interests: Behavioral ecology of bats and caribou Disease ecology and pathogen transmission Spatial ecology and habitat selection Conservation biology and species management Integration of social and spatial behavior Lab Environment: The lab emphasizes collaborative learning, with weekly meetings, writing groups, and interdisciplinary collaborations. Recent achievements include student publications, scholarship awards (e.g., NSERC, Vanier), and ongoing projects on behavioral aging, migration, and microbial transmission. Follow lab activities via Instagram (@uog_web_lab) or Bluesky (@qwebber.bsky.social). Grants & Advising: Mentors graduate students in PhD/Master's programs, focusing on behavioral ecology and conservation. Lab members have secured notable scholarships, reflecting strong mentorship and research impact. Labs/Teams: Active in the Department of Integrative Biology, collaborating on multi-layer social network analyses and telemetry data applications. The lab prioritizes EDI initiatives to foster inclusive research environments.
Dr. Louise Hassan is an Associate Professor in Marketing at the Department of Marketing, Birmingham Business School, University of Birmingham. She holds a PhD in Statistical Modelling and a BSc (Hons) in Applied Statistics, both from Glasgow Caledonian University. With over 15 years of academic experience, she has held faculty positions at several UK universities, including Bangor University (where she was a Professor and Director of Research), University of Strathclyde, Stirling, St Andrews, Heriot-Watt, and Lancaster. Education: PhD in Statistical Modelling, Glasgow Caledonian University (2004) BSc (Hons) in Applied Statistics, Glasgow Caledonian University (2001) Louise's research lies at the intersection of consumer psychology, marketing, and public health, with a focus on responsible and sustainable consumption, risky behaviors (e.g., smoking, alcohol), and consumer decision-making. Her work is grounded in theories of attitudes and social cognition and often employs quantitative methodologies across cross-national samples. She investigates how information processing, persuasion, and identity influence consumer choices, particularly in ethical and health-related contexts. Her recent publications span topics such as the effectiveness of alcohol warning labels, identity marketing, digital service recovery, and sustainable behavior during crises. These works reflect a strong trend toward interdisciplinary research combining marketing theory with public policy and behavioral science, often contributing to social marketing and consumer protection initiatives. Scientific Awards: Best Paper Award, American Marketing Association Winter Marketing Educators’ Conference (2009) Louise has served on editorial boards of the Journal of Business Research and International Journal of Consumer Studies , and co-edits the Consumer Ethics section of the Journal of Business Ethics . She has received research funding from the Arts and Humanities Research Council, Academy of Marketing, British Academy, and Welsh Government. Her work has been cited over 3,500 times on Google Scholar. She teaches courses in marketing principles, responsible marketing, and contemporary issues in marketing. She leads a funded interdisciplinary project (£450k+) on sustainability in consumer mask-wearing choices. She previously held leadership roles at Bangor Business School, including Deputy Head of School and Director of Research, and contributed to the REF2021 submission. She is actively involved in interdisciplinary research, supervising and collaborating with scholars in public health, psychology, and social policy. Her research has practical implications for policymakers, regulators, and marketing practitioners aiming to promote ethical and sustainable consumer behavior.
