جست‌وجوی استاد و پژوهشگر

• Epidemiology
• Biostatistics
• Infectious Diseases
• +۴ مورد دیگر

Forrest W. Crawford is an Associate Professor Adjunct in Biostatistics at the Yale School of Public Health (YSPH). He holds affiliations with the Computational Biology and Bioinformatics Program, the Center for Biomedical Data Science, and the Public Health Modeling initiative. His research focuses on mathematical and statistical methods for discrete structures and stochastic processes, with applications in epidemiology, public health, biomedicine, and evolutionary science. Dr. Crawford earned his PhD and MS in Biostatistics from the University of California, Los Angeles (2012 and 2009). His work bridges statistical theory and applied public health challenges, emphasizing network analysis, infectious disease modeling, and computational methods. He leads the Crawford Lab, which develops tools for understanding complex systems like opioid epidemics, HIV transmission dynamics, and pandemic response strategies. Key research interests include: - Network-based epidemiological modeling - Causal inference under contagion - Public health data science - Statistical methods for hidden populations - Stochastic processes in biological systems Recent work includes studies on fentanyl-related mortality trends in Connecticut, SARS-CoV-2 transmission dynamics, and vaccine efficacy analyses. His interdisciplinary collaborations span public health, computer science, and mathematics. Dr. Crawford has advised numerous research initiatives and contributed to pandemic response efforts through real-time modeling. His lab's projects include software development for public health surveillance (e.g., the covidestim tool) and methodological advancements in respondent-driven sampling for hidden populations. Professional affiliations include the American Statistical Association, Society for Mathematical Biology, and editorial roles in statistical and epidemiological journals.

Eric D. Kolaczykمشاهده پروفایل

استاد

• Statistics
• Network Analysis
• Machine Learning
• +۶ مورد دیگر

Eric D. Kolaczyk is a Professor of Statistics in the Department of Mathematics and Statistics at McGill University, where he also serves as the inaugural director of the Computational and Data Systems Initiative (CDSI). Additionally, he is an associate academic member at Mila, The Quebec AI Institute, positioning him at the forefront of statistics, data science, and artificial intelligence research. Dr. Kolaczyk's research focuses on statistical and machine learning theory and methods that support human endeavors enabled by computing and engineered systems, frequently from a network-based perspective of systems science. His work spans multiple domains including: Network analysis and modeling Computational biology and neuroscience AI-assisted chemistry and materials science Data privacy and security Statistical methodology for complex systems His recent publications demonstrate a strong emphasis on network science, with particular attention to dynamic networks, privacy-preserving methods, and applications across diverse fields from epidemiology to materials science. His work bridges theoretical statistics with practical applications, often developing novel methodologies to address challenges in complex data environments. Dr. Kolaczyk has received significant recognition for his contributions to the field: Elected Fellow of the American Association for the Advancement of Science (AAAS) Elected Fellow of the American Statistical Association (ASA) Elected Fellow of the Institute of Mathematical Statistics (IMS) Elected Senior Member of the IEEE Elected Member of the International Statistical Institute (ISI) Throughout his career, Dr. Kolaczyk has been actively involved in academic leadership and service. He has served as an associate editor for prestigious journals including the Journal of the American Statistical Association (JASA) and the Journal of the Royal Statistical Society, Series B (JRSSB). He previously served as co-chair of the U.S. National Academies of Sciences, Medicine, and Engineering Roundtable on Data Science Education and as president of the New England Statistical Society. His research has been supported by numerous grants that enable collaborations across disciplines. As the inaugural director of McGill's Computational and Data Systems Initiative (CDSI), Dr. Kolaczyk leads interdisciplinary efforts to advance computational and data-intensive research across the university. His leadership at CDSI fosters collaboration between statisticians, computer scientists, domain experts, and industry partners to tackle complex data challenges.

Casey Breenمشاهده پروفایل

استادیار

• Formal Demography
• Health and Mortality Disparities
• Social Networks
• +۱ مورد دیگر

Casey Breen is an Assistant Professor in the Department of Sociology and Population Research Center at the University of Texas at Austin . He earned a Ph.D. in Demography and M.A. in Biostatistics from UC Berkeley, followed by a postdoctoral fellowship at the University of Oxford . His research combines computational demography and network-based methods to address critical questions in population health and mortality disparities , particularly in the United States. Key research areas: Formal Demography , Health and Mortality Disparities , Social Networks , Computational Methods Recent work explores digital inequality , death rate estimation in humanitarian crises , and historical mortality patterns . His publications appear in top journals like Demography , American Journal of Epidemiology , and Population and Development Review . He actively collaborates with institutions including the Max Planck Institute for Demographic Research , Berkeley Population Sciences , and Leverhulme Centre for Demographic Science , and participates in events such as the Population Association of America (PAA) 2025 conference.

• Marketing
• Retail Analytics
• Bayesian Applications
• +۱۰ مورد دیگر

Sandeep R. CHANDUKALA is a Full-time Associate Professor of Marketing and Lee Kong Chian Fellow at the Lee Kong Chian School of Business, Singapore Management University. His research focuses on new technologies in marketing, retail analytics, Bayesian applications, and quantitative models for advertising and new product development. He holds a Ph.D. in Marketing from The Ohio State University (2008), an MBA from the University of Texas, Dallas (2002), and engineering degrees from the University of Minnesota and Osmania University. Education: Ph.D. Marketing (Ohio State), MBA (UT Dallas), M.S. Computer Engineering (Minnesota), B.E. Instrumentation (Osmania) His research explores immersive retailing, AR applications in retail, and data-driven marketing strategies. He has published in top journals like Journal of Marketing and Journal of Retailing , receiving the 2022 AMA/MSI/H. Paul Root Award for impactful marketing practice contributions. His work bridges academic insights with real-world retail challenges, emphasizing consumer behavior in digital and physical spaces. Teaching excellence awards include the 2020 MiM Excellent Teaching Award and multiple Dean's Honours recognitions. His research funding includes the 3M Junior Faculty Grant and Lee Kong Chian Fellowship. He has contributed case studies on generative AI in advertising, omni-channel strategies, and influencer analytics. His interdisciplinary expertise spans digital transformation, AI-driven decision-making, and competitive brand strategies.

Sabine Zinnمشاهده پروفایل

استاد

• Computational Social Science
• Survey Methodology
• Data Science
• +۶ مورد دیگر

Sabine Zinn serves as Director of the Socio-Economic Panel (SOEP) at DIW Berlin since 2022 and holds a W3 Professorship in Social Science Methods at Humboldt University of Berlin since 2020. She leads one of Germany's most significant longitudinal social surveys while advancing computational methodologies at the university. Her dual roles bridge academic research with policy-relevant social analysis through DIW Berlin's institutional framework. Zinn's academic journey includes: Doctorate in Modeling and Simulation (2011) from University of Rostock's Faculty of Electrical Engineering and Computer Science Habilitation in Survey Statistics and Demography (2019) from University of Bamberg Studies in Business Mathematics at University of Jena Her research centers on computational social science with emphases on survey methodology, data science, and demographic analysis. She investigates migration flows, educational trajectories, and health outcomes using advanced statistical techniques including Bayesian modeling and microsimulation. Her work on nonresponse mechanisms in longitudinal surveys has established new methodological standards for population studies. Recent publications (2022-2025) demonstrate her focus on refugee survey methodology, nonprobability sampling validation, and microsimulation applications. She has pioneered innovative approaches for studying Ukrainian refugees in Germany through the IAB-BAMF-SOEP project, developing specialized sampling frameworks and weighting techniques that address hard-to-reach populations. Her article trends reveal consistent integration of machine learning with traditional survey methods. Zinn directs substantial research funding through DIW Berlin projects including ENTAILab and the German Social Cohesion Panel. She serves on multiple national and international advisory boards influencing survey methodology standards, though no formal student advisement is documented. Her leadership in projects like the IAB-BAMF-SOEP Survey of Refugees demonstrates significant grant management capacity. As SOEP Director, Zinn oversees Germany's premier household panel study infrastructure. She leads the ENTAILab research innovation lab and contributes to the RKI Panel's methodological development. Her teams specialize in cutting-edge data collection techniques including video-interviewing integration and respondent-driven sampling to enhance population diversity in surveys, particularly for migration research contexts.

Elena A. Eroshevaمشاهده پروفایل

استاد

• Statistical Methodology
• Discrete Data Analysis
• Latent Variable Models
• +۷ مورد دیگر

Elena A. Erosheva is a Professor of Statistics at the University of Washington with a joint appointment in the School of Social Work. She serves as Associate Director of the Center for Statistics and the Social Sciences (CSSS) and is an Associate Editor for the Journal of the American Statistical Association and the Annals of Applied Statistics. Education PhD in Statistics from Carnegie Mellon University (2002) Elena Erosheva is a statistician whose research focuses on the development and application of modern statistical methods for addressing complex substantive questions in the social, medical and health sciences. Her ongoing methodological research focuses on latent variable and mixed membership models, multivariate and longitudinal data analysis, and text and network analysis. Her work has important applications in understanding disability in elderly populations, criminal desistance patterns, and scientific collaboration networks. Dr. Erosheva's research bridges statistical theory with practical applications, making significant contributions to both methodology and substantive fields. Analysis of Dr. Erosheva's recent publications reveals a strong focus on mixed membership models and their applications across diverse domains. Her work spans from theoretical developments in statistical methodology (such as variational inference techniques and bootstrap methods) to applied research in health sciences (particularly aging and disability) and social sciences (including criminology and scientific collaboration patterns). A notable trend in her recent work is the application of advanced statistical techniques to understand gender dynamics in scholarly publishing and to improve peer review processes. Scientific Awards 2013 Mitchell Prize from the International Society of Bayesian Analysis First Prize from the National Institutes of Health's Peer Review Challenge Dr. Erosheva has successfully advised numerous graduate students across multiple departments including Statistics, Sociology, Health Services, and Educational Psychology. Her research has been supported by grants from the National Institute on Aging (funding her work on operational definition of disability in the National Long Term Care Survey) and NIH (funding the COAP - Cognitive Outcomes with Advanced Psychometrics project). She has collaborated extensively with researchers across disciplines, demonstrating the interdisciplinary nature of her work. Dr. Erosheva is actively involved in the Center for Statistics and the Social Sciences (CSSS) at the University of Washington, where she serves as Associate Director. She leads research projects focused on measuring gender-based homophily in scientific collaborations, modeling life course transitions, developing partial mastery cognitive diagnosis models, and identifying commensuration bias in grant review.

Rana B. Khouryمشاهده پروفایل

استادیار

• Middle Eastern Politics
• Civil Society and Social Movements
• Refugee and Migration Studies
• +۲ مورد دیگر

Rana B. Khoury serves as Assistant Professor in the Department of Political Science within the College of Liberal Arts & Sciences at the University of Illinois Urbana-Champaign, holding a concurrent appointment at the Center for South Asian and Middle Eastern Studies. Her scholarly work examines political dynamics in conflict zones with particular emphasis on Syria and Jordan, investigating intersections of civil society, humanitarian intervention, and displacement. Her research program spans Middle Eastern Politics, Civil Society and Social Movements, Refugee and Migration Studies, Humanitarian Aid in Conflict Zones, and Political Methodology. She analyzes how civil society organizations operate during wartime, the political consequences of humanitarian aid frameworks, and methodological innovations for studying hard-to-reach populations including refugees and conflict-affected communities. This work bridges qualitative field research with quantitative analysis to document political behavior under extreme conditions. Analysis of her 15 most recent publications reveals escalating focus on Syrian civil society's role in democratic transitions (2024-2025), with recurring themes of digital activism through social media platforms, power asymmetries in humanitarian localization efforts, and civil society's resilience during war. These contributions advance broader fields including conflict studies, international relations, and refugee studies by centering local agency within global intervention frameworks while exposing tensions between international aid architectures and grassroots political mobilization.

Sebastien Rochمشاهده پروفایل

استاد

• Applied Probability
• Mathematical Phylogenetics
• Population Genetics
• +۳ مورد دیگر

Sebastien Roch is a Vilas Distinguished Achievement Professor in the Department of Mathematics at the University of Wisconsin-Madison, with affiliate appointments in the Department of Statistics and the Theory of Computing Group in the Department of Computer Sciences. He is a member of the Probability Group and Applied Mathematics Group within the Mathematics Department and can often be found at the Wisconsin Institute for Discovery. Roch serves on the executive committee of the Institute for Foundations of Data Science (IFDS), a collaboration with several major universities funded through the NSF TRIPODS Phase II program. Roch's research spans the intersection of applied probability, statistics, and theoretical computer science, with a strong emphasis on biological applications, particularly in mathematical phylogenetics and population genetics. His work focuses on developing rigorous mathematical frameworks for analyzing probabilistic and combinatorial structures arising from evolutionary biology. His research has produced significant contributions to understanding species tree estimation, sequence alignment, and phylogenetic methods under various evolutionary models. His recent publications demonstrate a consistent focus on advancing computational methods in phylogenetics, with particular attention to statistical consistency, sample complexity, and polynomial-time algorithms. Roch has developed innovative approaches to species tree estimation under gene duplication and loss, addressed challenges in respondent-driven sampling, and contributed to understanding phase transitions in phylogenetic inference. Scientific Awards and Recognition: Vilas Distinguished Achievement Professor (2024) Fellow of the Institute of Mathematical Statistics (2022) Van Vleck Research Professor Award (2023) Best Paper Award at RECOMB 2018 Honorable Mention for Marcus W. Feldman Prize in Theoretical Population Biology Roch has successfully mentored multiple PhD students to completion, including Max Hill (2023), Yu Sun (2023), and Shuqi Yu (2023). His research is currently supported by NSF grants DMS-2023239 (TRIPODS Phase II) and DMS-2308495, as well as institutional awards. He is actively involved in developing new courses, including "Linear Algebra and Optimization" (MATH 345) and "Graphs and Networks in Data Science" (MATH 444), which bridge traditional mathematics with modern data science applications.

Chantal Visمشاهده پروفایل

استاد مدعو

• Aquatic Ecosystems
• Marine Conservation
• Biogeochemistry
• +۳ مورد دیگر

Chantal Vis is an Adjunct Professor in the Department of Biology at Carleton University, part of the Faculty of Science. She holds a B.Sc. from Dalhousie University and both an M.Sc. and Ph.D. from Université de Montréal. Her primary affiliation is with Parks Canada, where she serves as a marine/aquatic ecosystem specialist in the Marine Conservation Division. Her research focuses on understanding how aquatic primary producers respond to natural and human-driven changes, with a particular emphasis on biogeochemical processes in large river systems, nutrient impacts on plant communities, and cyanobacteria proliferation. She also develops models to guide wetland restoration in the Great Lakes region. Her work spans diverse topics including dissolved oxygen dynamics in agricultural streams, hydrological controls on algal growth, and policy evaluations for marine protected areas. Recent publications highlight interdisciplinary approaches to conservation challenges. Chantal’s contributions bridge scientific research and practical management strategies within Canada’s national parks and marine conservation areas. Education: B.Sc. (Dalhousie University), M.Sc., Ph.D. (Université de Montréal) Affiliations: Parks Canada (Marine Conservation Division), Department of Biology (Carleton University) Contact: chantal.vis@pc.gc.ca | Phone: 819-420-9198

• Mixed Methods Survey Research
• Respondent-Driven Sampling
• Research with Vulnerable Populations
• +۴ مورد دیگر

Dr. Mariel McKone Leonard serves as Interim Head of SOEP Innovation Sample at the German Socio-Economic Panel study Research Infrastructure. With over ten years of experience in mixed methods survey research, she specializes in working with small, rare, and vulnerable populations within sensitive research contexts. She maintains active research collaborations with the Universities of Maryland (UMD) and Munich (LMU), while being primarily affiliated with the German Institute for Economic Research (DIW). Her research expertise centers on innovative sampling methodologies, particularly respondent-driven sampling (RDS) techniques to improve representation of marginalized populations in survey research. Dr. Leonard has made significant contributions to developing data collection structures designed to measure and evaluate structural and individual racism. Her methodological work addresses critical challenges in creating more inclusive and representative social science data. Recent research outputs demonstrate her focus on advancing virtual and hybrid sampling approaches, with publications and conference presentations examining how to implement respondent-driven sampling to increase diversity in general population samples and integrate egocentric network data collection with traditional survey methods. Her work has important implications for improving survey methodology across social science disciplines. Dr. Leonard has presented her research at major international venues including the European Survey Research Association (ESRA 2025), the American Association for Public Opinion Research (AAPOR), and the General Online Research Conference (GOR 2024), establishing herself as a contributor to methodological innovation in survey research.

Brittany Moreyمشاهده پروفایل

دانشیار

• Structural Racism
• Health Inequities
• AAPI Communities
• +۵ مورد دیگر

Brittany Morey is an Associate Professor at the University of California, Irvine in the Joe C. Wen School of Population & Public Health, Department of Health, Society, & Behavior . She holds a PhD and MPH in Community Health Sciences from the UCLA Fielding School of Public Health (2017, 2011). Her research examines how structural racism , neighborhood environments , and immigration policies shape racial/ethnic health inequities , particularly for AAPI communities . Morey's recent work focuses on social determinants of cardiovascular health in Asian Americans, validation of neighborhood-level sociocultural measures , and environmental justice in Boyle Heights. She serves as a co-investigator on NIH grants related to breast cancer disparities and respiratory health in AAPI populations. Her CAPIWAVES project, conducted with the NHPI Data Policy Lab , revealed severe mental health and economic impacts of the pandemic on Native Hawaiians and Pacific Islanders. Key findings from her 15 most recent publications include: Methodological advancements in measuring sociocultural institutions and their role in health equity Links between sleep disturbances , cardiometabolic risks , and acculturative stress in Chinese/Korean Americans Community health workers' critical role in equitable pandemic responses and challenges in sustainable funding Exposure disparities to air pollution among AAPI subgroups Structural barriers in data equity and healthcare access for NHPI communities She advises PhD candidates and collaborates with institutions like Kaiser Permanente , UCLA Center for Health Policy Research , and Roswell Park Cancer Institute . Morey also serves on the Center for the Pacific Asian Family board, addressing gender violence in AAPI communities.

Pratsinakis Manolisمشاهده پروفایل

استادیار

• Geographies of migration
• Diasporas and transnationalism
• Geographies of diversity
• +۶ مورد دیگر

Pratsinakis Manolis is an Assistant Professor in Social Geography at the Department of Geography, Harokopio University, Athens. His academic work focuses on migration geographies, diasporas, transnationalism, urban ethnography, and social integration. Department of Geography, Harokopio University Research interests: migration, diversity, ethnic relations, RDS methodology Educational Background BA in Geography (2002), University of the Aegean MA in Migration and Ethnic Studies (2004), University of Amsterdam PhD in Urban Ethnography and Ethnic Studies (2013), University of Amsterdam Teaching Activities Undergraduate: International Migration, Social Geography, Qualitative Methods Postgraduate: Scientific Research Methods, Migration Policy Studies

Miguel Arriagaمشاهده پروفایل

پژوهشگر

• Health Literacy
• Public Health
• Psychology
• +۸ مورد دیگر

Miguel Arriaga is a Researcher at the Católica Research Centre for Psychological, Family and Social Wellbeing (CRC-W), Universidade Católica Portuguesa. He holds a PhD in Psychology from the University of Beira Interior, awarded in 2018, and has been actively engaged in research related to public health, health literacy, and social wellbeing. His work spans multiple interdisciplinary projects, including national and international collaborations focused on crisis response, digital health, and population health assessment. PhD in Psychology, University of Beira Interior (2018) His primary research interests include health literacy, public health, psychology, social sensing, healthy aging, quality of life, and crisis communication. Miguel’s work often integrates behavioral insights with data intelligence to understand public responses during health emergencies such as the COVID-19 pandemic. He has contributed significantly to the development and validation of health literacy instruments, including the HLS19-DIGI tool used across 13 countries. Recent publications reflect a strong focus on the behavioral aspects of pandemic compliance, digital health interventions for older adults, and the role of trust and fairness in public health messaging. His research employs diverse methodologies, from large-scale surveys to quasi-experimental studies and social sensing technologies. Prémio nacional de Saúde Publica Francisco George (2018) Miguel Arriaga has been involved in significant research grants and collaborative projects, including HLS-19, ResiliScence 4 COVID-19, and studies on vaccination intentions and social prescribing. He frequently presents at academic and policy forums, contributing expert insights on health literacy and crisis management. He is also engaged in supervising research and mentoring early-career researchers within the CRC-W framework. His affiliations with the WHO Action Network M-POHL and participation in multi-country studies underscore his role in shaping evidence-based public health strategies. He collaborates closely with national health authorities and research teams across disciplines to advance social and psychological wellbeing.

Pedro Simões Coelhoمشاهده پروفایل

استاد

• Statistics
• Sampling Techniques
• Structural Equation Modeling
• +۱۲ مورد دیگر

Pedro Simões Coelho is a Full Professor and President of the Scientific Board at NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, where he also serves as an Integrated Researcher in the Information Management Research Center (MagIC). He is a senior expert for the European Commission in statistical methods and sampling techniques, and holds leadership roles in several national and European bodies, including the European Master of Official Statistics (EMOS) board and the Portuguese Health Technologies Commission. His research interests lie at the intersection of statistics, data analysis, and public policy. He specializes in sampling techniques, structural equation modeling, survey methodology, and data quality, with applications in health economics, business intelligence, and official statistics. His work bridges theoretical statistical innovation with real-world policy impact, particularly in health and administrative systems. His recent publications demonstrate a strong trend toward integrating artificial intelligence and advanced modeling techniques into public administration and health policy. Topics include AI-based detection of legislative burdens, economic burden assessments in dermatology, consumer segmentation via social media, and cardiovascular health optimization. These works reflect a multidisciplinary approach combining statistics, machine learning, and domain-specific knowledge to solve complex societal challenges. Senior Expert, European Commission (Statistical Methods & Sampling) Member, EMOS Board Member, Ischools Accreditation Committee Head of Information and Statistics, NOVA Clinical Research Unit (NOVA CRU) Former President, Portuguese Association for Classification and Data Analysis (CLAD) Former Member, Portuguese High Council for Statistics (CSE) Former President, Fiscal Board, CESD-Lisboa He has supervised numerous graduate and undergraduate courses and has been a consultant and trainer for major institutions including Eurostat, the Portuguese Statistical Office, and the Portuguese Central Bank. His work includes over 100 peer-reviewed publications and around 200 research projects resulting in more than 500 reports. He has delivered nearly 100 invited talks and conference presentations worldwide. He is actively involved in research labs and teams such as MagIC and NOVA CRU, where he leads initiatives in data-driven public health and statistical innovation. His ongoing projects focus on AI for policy assessment, sustainable health systems, and advanced statistical modeling for small area estimation and data integration.

Julien Labonneمشاهده پروفایل

دانشیار

• Political Economy
• Electoral Politics
• Clientelism
• +۷ مورد دیگر

Julien Labonne is an Associate Professor in Economics and Public Policy at the Blavatnik School of Government, University of Oxford. His research focuses on political economy in developing countries, particularly the Philippines, with an emphasis on clientelism, electoral politics, and social networks. He employs field experiments, household surveys, and large-scale data to analyze voter and politician behavior. Julien also serves as the DPhil Coordinator at the Blavatnik School, overseeing doctoral studies. University: University of Oxford School: Blavatnik School of Government Academic Rank: Associate Professor Email: julien.labonne@bsg.ox.ac.uk Julien Labonne completed his PhD in Economics at the University of Oxford and holds master’s degrees from Oxford, University College London, and ENSAE Paris Tech. Prior to Oxford, he was an Assistant Professor at Yale-NUS College in Singapore. He has also worked at the World Bank and consulted for the Asia Foundation, Millennium Challenge Corporation, and the OECD. His research interests include political economy, clientelism, electoral behavior, social networks, and governance in developing countries. He conducts field experiments to understand how information affects voting behavior and how political dynasties influence representation, particularly in the Philippines. His work explores how voters respond to policy platforms versus personal connections, and how NGOs and governments can shift electoral incentives toward better governance. The trend in Julien Labonne’s recent publications shows a strong focus on empirical political economy, particularly in Southeast Asia. His work combines rigorous experimental methods with deep contextual understanding of local politics. Key themes include political dynasties, clientelism, voter information campaigns, and public service delivery. His research often involves collaboration with international institutions and uses randomized field experiments to assess causal impacts of policy interventions. Julien Labonne has not been publicly recognized with scientific awards in the provided texts. However, his work has been published in top-tier journals such as the American Political Science Review , Economic Journal , and Journal of Development Economics , indicating high scholarly impact. Julien Labonne has advised or collaborated with several researchers and students, though no formal list of advisees is provided. His research has been supported through collaborations with institutions like the Inter-American Development Bank and the Evidence in Governance & Politics (EGAP) network. He has organized policy panels and engaged with policymakers in Washington, highlighting the policy relevance of his work. He also contributes to academic discourse through publications and public engagement. Julien Labonne is part of a collaborative research team involving scholars from the University of British Columbia and the Inter-American Development Bank. He works closely with a local NGO in the Philippines to implement voter information campaigns during elections. His research is conducted under the auspices of the Blavatnik School of Government and is connected to broader networks such as the Centre for the Study of African Economies at Oxford, reflecting interdisciplinary and international collaboration.