Orazio Giancola is Associate Professor at the Department of Social and Economic Sciences, Sapienza University of Rome. His research focuses on social research methodologies, educational inequality analysis, and policy evaluation in Italian and comparative contexts. He teaches courses such as Applied Social Research Methodology , Research Methods for Social Policies , and data analysis techniques. Research Interests : Sociology of education, social stratification, big data analytics, educational equity, tertiary education access, and policy evaluation. Key Projects : School experiences and educational choices in the post-pandemic landscape (Rome high school survey). His recent publications examine educational poverty , digital technology disparities , and policy impacts in Italy and Europe. Articles employ multivariate analysis and logistic modeling to explore structural inequalities. No scientific awards are currently documented.
David H Laidlaw is a Professor of Computer Science at Brown University, specializing in virtual reality, scientific visualization, and medical imaging. His work spans interdisciplinary applications in neuroscience, biomedical research, and educational tools. Brown University Affiliation Department of Computer Science His research focuses on: Immersive visualization for complex data analysis Diffusion MRI and neuroimaging techniques Human-computer interaction in virtual environments 3D interaction methods for scientific exploration Collaborative visualization tools for multidisciplinary teams Recent trends in his publications highlight advancements in: Graph neural networks for biomedical data Memory-efficient segmentation algorithms Perceptual studies in VR environments Annotation and analysis of placental vasculature Technological innovations in foot dynamics research He teaches courses in virtual reality design and scientific visualization, including: CSCI 1370 - Virtual Reality Design for Science CSCI 1951S - Virtual Reality Software Review CSCI 1951T - Surveying VR Data Visualization Software CSCI 2370 - Interdisciplinary Scientific Visualization
Juan Alcacer is the James J. Hill Professor of Business Administration at Harvard Business School. He holds a PhD in International Business and Strategy from the University of Michigan, an M.A. in Economics, an MBA in Finance, and a Computer Engineering degree. His research focuses on international strategies, location decisions, and agglomeration economies. PhD - University of Michigan (Ross School of Business) MA - Economics, University of Michigan MBA - IESA Computer Engineering - Universidad Simon Bolivar Alcacer’s work examines how firms build competitive advantage through geographic choices, supply chain dynamics, and knowledge transfer. Recent projects analyze Brexit’s impact on investment and the role of internal/external agglomeration economies. His publications span top journals like Strategic Management Journal , Management Science , and Journal of International Business . Awards include the 2024 HBS Student Association Faculty Teaching Award and the 2016 Michigan Ross Distinguished PhD Alumni Award. 2024 HBS Student Association Faculty Teaching Award 2019 Greenhill Award for Field Global Immersion program 2016 Michigan Ross Distinguished PhD Alumni Award 2013 Meritorious Service Award from Management Science At HBS, he teaches required MBA strategy courses, Executive Education programs, and PhD seminars. His consulting spans global corporations on competitive advantage and location strategy.
Jiayi (Jessie) Tong, PhD is an Assistant Professor in the Department of Biostatistics at Johns Hopkins University, with joint appointments in the Bloomberg School of Public Health and School of Medicine. She received her PhD from the University of Pennsylvania in 2024 and has rapidly established herself as a leading researcher in biostatistical methods for real-world data analysis. Dr. Tong's research program focuses on clinical evidence generation and evidence synthesis with real-world data (RWD). Her work spans three main areas: clinical evidence generation using data from distributed research networks, surrogate-assisted semi-supervised learning methods, and systematic reviews and meta-analyses. She has developed innovative statistical methodologies for analyzing electronic health records across multiple institutions while preserving patient privacy through distributed computing approaches. Her research has significant implications for improving evidence generation in healthcare, particularly for rare conditions and emerging health threats where traditional clinical trials may be impractical. Analysis of Dr. Tong's publication record reveals a strong emphasis on methodological innovation in biostatistics, particularly in the areas of federated learning, meta-analysis, and electronic health record analysis. Her work frequently addresses challenges in multi-site collaborative studies, developing one-shot algorithms that enable analysis without sharing patient-level data. Much of her recent research has focused on applications to SARS-CoV-2 infection and its sequelae, demonstrating the practical utility of her methodological contributions to pressing public health challenges. Dr. Tong has demonstrated exceptional productivity since completing her PhD in 2024, with numerous high-impact publications in top biostatistics and medical journals. Her work has been recognized through mentions on various platforms including Mendeley readership and blog coverage. As a new faculty member, Dr. Tong is actively building her research program and mentoring the next generation of biostatisticians. Her expertise in distributed analysis of healthcare data positions her at the forefront of methodological developments needed to address contemporary challenges in evidence generation.
Tomas Karlsson is a Professor and Deputy Head of Department at the Royal Institute of Technology , specializing in Space and Plasma Physics . He teaches courses such as EF2240 Space Physics , EF2245 Space Physics II , and EI1240 Electromagnetic Theory , while serving as examiner or coordinator for advanced projects and thesis work in space-related fields. His research focuses on the interaction between the solar wind and planetary magnetospheres , with specific interests in bow shock physics , magnetosheath jets , solar wind magnetic holes , auroral physics , and comparative studies of magnetospheres across planets and comets. He employs spacecraft data (e.g., MMS , Cluster , BepiColombo ) and simulations to analyze plasma dynamics and space weather phenomena. The 15 most recent publications highlight trends in solar wind turbulence , magnetospheric boundary processes , and planetary plasma interactions , with recurring themes in SLAMS (Short Large-Amplitude Magnetic Structures) , magnetosheath jet formation , and magnetic hole propagation . These works span statistical surveys, hybrid simulations, and multi-mission data analysis.
Roger Flage is a Professor of Risk Management at the University of Stavanger, affiliated with the Faculty of Science and Technology and the Department of Security, Economics and Planning. His research focuses on foundational and applied aspects of risk analysis, uncertainty quantification, and decision-making under uncertainty, with applications in critical infrastructure, environmental systems, and offshore energy. Roger Flage's research interests lie at the intersection of risk science, safety engineering, and decision theory. He investigates how uncertainty—especially epistemic uncertainty and assumptions—affects risk assessments, and advocates for more transparent and robust frameworks. His work spans theoretical advances, such as the treatment of 'black swan' events and the concept of 'real risk', as well as practical applications in offshore safety, power systems, and geohazards. He emphasizes the integration of data-driven methods, AI, and digital twins while critically assessing their limitations and associated security risks. His recent publications show a strong trend toward integrating dynamic, data-rich, and interdisciplinary approaches to risk analysis. Themes include the role of time in risk, AI applications, infrastructure interdependencies, and environmental risk in the oil and gas sector. He frequently publishes in top-tier journals like Risk Analysis , Reliability Engineering & System Safety , and Safety Science , often in collaboration with leading scholars such as Terje Aven and Seth Guikema. No scientific awards are mentioned in the provided text. Roger Flage has supervised or collaborated with several researchers, though no formal list of advisees is provided. His work is supported through academic collaborations and institutional affiliations rather than explicit grant mentions. He is actively involved in advancing risk science methodology, particularly in the treatment of assumptions and uncertainty, and contributes to both theoretical foundations and real-world applications in safety-critical domains. He is associated with research groups and collaborative networks at the University of Stavanger, particularly within the Department of Security, Economics and Planning. His work often involves interdisciplinary teams focusing on risk in complex engineered systems, including energy, transportation, and environmental systems.
James O'Malley is a Professor at The Dartmouth Institute for Health Policy and Clinical Practice and Professor of Biomedical Data Science at the Geisel School of Medicine, Dartmouth College. He holds the prestigious Peggy Y. Thomson Professorship in the Evaluative Clinical Sciences and serves as an Adjunct Professor of Computer Science, demonstrating his interdisciplinary expertise spanning statistics, healthcare policy, and computer science. Dr. O'Malley earned his B.Sc. (Hons) in Statistics from the University of Canterbury, New Zealand (1994), M.S. in Applied Statistics from Purdue University (1999), and Ph.D. in Statistics from the University of Canterbury (1999), followed by a Postdoctoral Fellowship in Biostatistics at Harvard Medical School (2001). His research spans statistical methodology and healthcare applications, with methodological contributions in statistical inference for social networks , multivariate hierarchical models , comparative effectiveness research , and Bayesian analysis . These methods address critical healthcare problems including health-social network relationships , healthcare quality measurement , medical technology diffusion , and comparative effectiveness in vascular surgery, cardiology, and mental health . His work bridges theoretical statistics with practical healthcare challenges through collaborations with physicians, epidemiologists, and health services researchers. Dr. O'Malley's recent publications reveal a strong emphasis on healthcare network analysis, comparative effectiveness research, and methodological innovations. His work examines physician networks and patient outcomes, evaluates surgical interventions, identifies healthcare disparities, and develops novel statistical approaches for complex healthcare data, with significant contributions appearing in high-impact journals across multiple disciplines. Mid-career Excellence award from the Health Policy Section of the ASA Elected fellow of the ASA (2012) ISPOR Award for Excellence in Methodology (2019) Peggy Y. Thomson Professorship (2021) 2025 Research Excellence Award for Senior Faculty in the Foundational Sciences As a dedicated mentor, Dr. O'Malley has supervised numerous post-doctoral fellows and PhD students across multiple programs. He currently leads major research initiatives including NIH/NLM R01LM014233 on Geographic Variations in Health Care, serves as PI for cores in NIH/NIA projects on healthcare inequity in Alzheimer's Disease and Rural Health Care Delivery Science, and contributes to multiple substantial grants totaling millions of dollars. He previously chaired the Health Policy Statistics Section of the ASA and co-chaired the 2011 International Conference on Health Policy Statistics. Dr. O'Malley co-organized the Dartmouth Interdisciplinary Network Research (DINR) seminar series (2014-2020) and serves as an Associate Editor for Statistics in Medicine and Observational Studies, demonstrating his commitment to advancing methodological research and fostering interdisciplinary collaboration in health services research.
Krishnan Bhaskaran is a Professor of Statistical Epidemiology at the London School of Hygiene & Tropical Medicine (LSHTM) , affiliated with the Faculty of Epidemiology and Population Health and the Department of Non-communicable Disease Epidemiology . He leads the Beyond Cancer research group , supported by a Wellcome Senior Research Fellowship . He co-founded the OpenSAFELY platform for real-time pandemic data analysis. Education: Background in Mathematics and Medical Statistics Research Interests: Cancer survivorship, cardiovascular and mental health outcomes in cancer survivors, pharmacoepidemiology of drug interactions, and methodological advancements in electronic health records analysis Publication Trends: His recent work focuses on long-term health consequences of cancer and its treatments, drug interactions in cardiovascular therapies, and the impact of chronic conditions on cancer risk. Many studies utilize large UK datasets and the OpenSAFELY platform. Scientific Awards: Wellcome Senior Research Fellowship Grants & Leadership: He has secured major funding from Cancer Research UK , British Heart Foundation , and Wellcome Trust to investigate cardiovascular risks post-cancer, health inequalities in endocrine therapy adherence, and drug safety in anticoagulant use.
Ian Quinn is the Allen Forte Professor of Music Theory and Director of Graduate Studies (DGS) at Yale University, within the Department of Music in the College of Arts and Science. He holds a B.A. from Columbia University (1993), M.A. and Ph.D. from the Eastman School of Music (1998, 2004). Prior to Yale, he taught at the University of Chicago and University of Oregon, and was a CASBS Residential Fellow at Stanford (2008-09). His research focuses on tonal harmony, corpus studies, music cognition, and the intersections of mathematics and computation in music theory. He edited the Journal of Music Theory (2004–2011) and co-organized the 2009 Society for Mathematics and Computation in Music conference. He leads the Yale-New Haven Regular Singing (YNHRS) shape-note singing group and serves on editorial boards for Journal of Mathematics and Music and the Northeast Music Cognition Group (NEMCOG). Quinn’s work has earned awards from the Society for Music Theory, including the Emerging Scholar Award (2004) and Outstanding Publication Award (2006/2007). His research spans analytical frameworks for harmonic function, corpus-based studies of tonal systems, and empirical investigations of music perception. He has advised over 15 doctoral students, many now in academic and industry roles. Key collaborations include co-authoring the Oxford Handbook of Corpus Studies in Music (2023) and developing the Yale-Classical Archives Corpus. His work bridges theoretical, computational, and historical approaches to music analysis, with contributions to Science , Music Theory Spectrum , and Perspectives of New Music .
Mark Hebblewhite is a Professor in Ungulate Ecology at the Wildlife Biology Program, University of Montana. His research integrates ecological theory with applied wildlife management, focusing on species like elk, wolves, and grizzly bears. Institution: University of Montana Academic Rank: Professor Research Interests span: Wildlife-habitat interactions Predator-prey dynamics Conservation of endangered species Remote sensing for forest and wildlife monitoring Climate change impacts on ecosystems Recent Publications emphasize: Multi-scale movement ecology Remote sensing integration for forest inventory Anthropogenic effects on wildlife behavior Fire ecology and post-disturbance recovery LiDAR and satellite-based vegetation mapping Collaborations include researchers from the University of Alberta, University of British Columbia, Colorado State University, and the Wildlife Conservation Society.
Dr. Henry Streby is an Associate Professor of Ecology in the Department of Environmental Sciences at the University of Toledo, where he leads the Streby Lab. He also holds an appointment as Adjunct Assistant Professor and is recognized as a Fellow of the American Ornithological Society. Education: Ph.D. in Ecology from University of Minnesota Research Focus: Dr. Streby's research spans avian ecology , wildlife ecology , evolutionary biology , and quantitative science . His work particularly emphasizes organismal ecology with applications to conservation and management of migratory songbirds. Key research areas include: Migratory connectivity and seasonal interactions Conservation biology of declining songbird populations Behavioral ecology of breeding and migratory birds Quantitative methods in wildlife research Effects of environmental change on bird populations Research Impact: Dr. Streby's work has significantly advanced understanding of songbird migration, particularly in Vermivora warblers and golden-winged warblers. His 2015 Current Biology paper on tornado avoidance behavior in songbirds received extensive international media coverage and reached the 99th percentile of all articles tracked by Altmetric. His recent research continues to explore migratory connectivity, hybridization patterns, and conservation strategies for North American migratory birds. Awards and Recognition: 2021 President's Award for Excellence in Scholarly Activity (University of Toledo) Elected Fellow of the American Ornithological Society (2021) 2013 Cooper Ornithological Society Young Professional Award Multiple best presentation awards at professional conferences Student Mentorship and Lab: Dr. Streby has successfully mentored numerous graduate students who have gone on to prestigious positions. Notable former students include: Gunnar Kramer (PhD 2021) - now Assistant Professor at Iowa State University Silas Fischer - recipient of multiple awards and fellowships Sean Peterson - pursued PhD at UC Berkeley Kyle Pagel - Environmental Scientist with California Department of Fish and Wildlife Annie Lindsay - active in migration research The Streby Lab continues to be highly productive, with ongoing research on Gray Vireos, migration ecology, and conservation applications. The lab maintains active field sites and collaborates extensively with other institutions and agencies.
Celia Byrne is an Associate Professor in the Department of Preventive Medicine and Biostatistics at the Uniformed Services University of the Health Sciences (USUHS). She holds a dual appointment in the Department of Epidemiology and Biostatistics. Her academic background includes a Bachelor's in Biology from Earlham College and a PhD/Master's in Epidemiology from UCLA. Her research focuses on environmental exposures, breast cancer epidemiology, and public health disparities. Key projects include investigating polycyclic aromatic hydrocarbons (PAHs) and breast cancer risk, environmental metal impacts on breast density, and the effects of SARS-CoV-2 on long-term health outcomes in military populations. She has led federally funded studies, such as the US Army-funded PAHs and Breast Cancer Risk project and a National Institute of Environmental Health Sciences study on metal/metalloid exposures. Byrne’s work bridges epidemiology and biostatistics, emphasizing methodological rigor in analyzing population-level health data. Her recent studies address post-COVID-19 sequelae, vaccination impacts, and racial disparities in endocrine-disrupting chemical exposure. Collaborations include multidisciplinary teams across military and civilian institutions. Her publications span environmental health, infectious disease epidemiology, and breast cancer research. Notable contributions include analyses of long-COVID symptoms, hybrid immunity mechanisms, and the role of acculturation in breast density among immigrant populations.
Philipp Otto is a Professor of Statistics and Data Science at the University of Glasgow. Previously, he was a Reader in Statistics and Data Analytics (2023–2024) and held a Junior Professorship in Big Geospatial Data at Leibniz University Hannover (2018–2023). He earned his PhD in Statistics (summa cum laude) from European University Viadrina in 2016 and a B.Sc. in International Economics, with study visits to Saint Petersburg State University. His research focuses on spatial and spatiotemporal statistics, environmetrics, network modeling, and machine learning applications. Education: PhD in Statistics (2016), European University Viadrina, Frankfurt (Oder) B.Sc. in International Economics (with study visits to Saint Petersburg) Research Interests: Philipp’s work centers on spatial statistics, spatiotemporal volatility modeling, environmental data analysis, and network processes. He develops statistical methods for geo-referenced and network data, with applications in climatology, finance, and environmental risk assessment. His contributions include advancements in GARCH models, spatiotemporal clustering detection, and statistical process monitoring for AI systems. Grants & Projects: He has secured €1,038,847 in research grants, leading projects on historical map time series analysis, agricultural air quality impacts, and high-dimensional spatial dependence structures. Industry collaborations include survival analysis for building information models. Awards: 2017 Fellowship to attend the Lindau Nobel Laureate Meeting (Economic Sciences) 2017 Best Presentation Award (Data Science, Statistics, and Visualisation) Teaching: He teaches statistics and data science across disciplines, including economics, engineering, and mathematics, at both undergraduate and postgraduate levels. Professional Activities: Editorial Boards: Environmetrics (2021), AStA Advances in Statistical Analysis (2020) Member of German Statistical Society (Treasurer, 2013)
Kenneth BENOIT is the Dean and Full-time Professor of Computational Social Science at the School of Social Sciences, Singapore Management University (SMU). Previously, he served as Director of the Data Science Institute at the London School of Economics (LSE) from 2020 to 2024. He holds a PhD in Government from Harvard University, specializing in statistical methodology. His research focuses on computational methods for analyzing textual data, particularly political texts and social media. Key areas include text-as-data techniques, natural language processing, and the application of large language models in social sciences. He has pioneered methods combining machine learning with crowd-sourced coding to improve the accuracy of political text analysis. Ken’s work emphasizes the analysis of big data, electoral systems, and comparative party competition, with notable contributions to the European Parliament and policy positioning studies. His expertise extends to software development, including R packages like quanteda and spacyr , which are widely used in text analysis. His articles and publications span methodological innovations, policy analysis, and interdisciplinary applications. Notable projects include scaling political party positions and examining the role of AI in public policy. He is actively involved in academic leadership, having served on editorial boards and organized collaborative research initiatives like the CIVICA research hackathon. Beyond SMU, he maintains professional profiles on LinkedIn and GitHub , reflecting his commitment to open-source tools and scholarly collaboration.
Marius Gilbert is a Full Professor at Université libre de Bruxelles (ULB) since 2023, with dual administrative roles as Vice-rector of Research and Valorization (since 2020) and Vice-rector of Culture and Scientific Mediation (current mandate). He obtained his PhD in spatial epidemiology from ULB in 2001 after studying Agricultural Sciences (1995) and conducting visiting research at Oxford's Department of Zoology. Key Research Areas: Spatial epidemiology of animal diseases and invasive species Impact of agricultural and ecosystem changes on pathogen emergence Specialization in avian influenza and emerging infectious diseases Development of livestock distribution models and antimicrobial resistance tracking Scientific Contributions: His 15 most recent publications (2025-2021) focus on viral phylogeography , livestock-environment interactions , antimicrobial use forecasting , and pandemic response modeling . Notable work includes COVID-19 spatio-temporal analysis and global antibiotic resistance trends in food animals. Public Engagement: Played a central role in French-speaking media during the pandemic , authored the book "Juste un Passage au JT" , and maintains a Le Soir column on science-society intersections. Co-founded the Spatial Epidemiology Lab (SpELL) in 2016, now led by Simon Dellicour.
