Akanksha Negi is a Lecturer (Assistant Professor) in the Department of Econometrics and Business Statistics at Monash University, Australia. Her academic journey includes a PhD in Economics (2020) from Michigan State University, preceded by a BS and MS in Statistics from the University of Delhi, India. Education: PhD in Economics, Michigan State University (2020) BS and MS in Statistics, University of Delhi (India) Research Interests focus on Econometrics, particularly Causal Inference and Experimental Design. Her work addresses methodological challenges in treatment effect estimation, including misclassification, heterogeneity, and missing data, with applications to agricultural economics and network transaction costs. Trends in Publications highlight contributions to Difference-in-Differences, Doubly Robust Estimation, and M-Estimation frameworks. She also explores dynamics in agricultural markets, aligning with UN Sustainable Development Goals (SDGs) related to poverty reduction and economic prosperity.
Javier Gomez-Lavin is an Associate Professor in the Department of Philosophy at Purdue University, specializing in cognitive science, moral psychology, and philosophy of mind. He directs the Purdue Normativity and Cognitions (PuNCs) lab, integrating experimental social psychology and analytical philosophy of science to explore how cognition interacts with social, aesthetic, and moral domains. Education: Ph.D. from the City University of New York (2018) Prior Roles: Sessional Assistant Professor at York University (Toronto), Provost Postdoctoral Fellow at the University of Pennsylvania (2018–2021), Guest Researcher at the Berlin School of Mind and Brain (2016–2021) Research Themes include interdisciplinary investigations of working memory, collective action, moral responsibility, and the aesthetic self. His work bridges empirical methods with philosophical analysis, particularly through collaborations with neuroscience and AI ethics frameworks. Article Trends reflect a focus on cognitive mechanisms (working memory, neural networks), moral psychology (collective action, identity), and interdisciplinary critiques (fMRI epistemology, AI ethics). Keywords cluster around Cognitive Science , Neuroscience , and Philosophy , with subfields like Normative Systems and Moral Selfhood . Scientific Awards & Grants : Templeton Foundation Grant (Co-PI, 2016–2018) Provost Postdoctoral Fellowship, University of Pennsylvania (2018–2021) Labs & Collaborations : Leads the PuNCs Lab at Purdue, previously collaborated with the MIRA Lab at UPenn and the Berlin School of Mind and Brain.
Prof. Dr. Richard Traunmüller is a Professor of Political Science and Empirical Democracy Research at the University of Mannheim. He serves as Scientific Director of the German Internet Panel (GIP) and is affiliated with the Research Institute Social Cohesion (RISC) at Goethe University Frankfurt. His research spans multidimensional social change, immigration policy, wartime sexual violence, and quantitative methodology. School of Social Sciences, University of Mannheim Goethe University Frankfurt University of Essex University of Bern University of Konstanz His research focuses on: Democratic challenges from social structural reconfiguration Religious diversity and social cohesion Free speech regulation in digital democracies Long-term effects of wartime sexual violence Recent work analyzes: Causal impacts of immigration policies Contextual speech norms Gendered consequences of conflict trauma Bayesian approaches to sensitive topics Scientific awards include: BEST PAPER AWARD (CES Immigration Research Network, 2017) BEST ARTICLE AWARD (APSA Migration & Citizenship, 2017) He teaches courses on: Bayesian Statistics Data Visualization Free Speech & Censorship Political Methodology Conflict Studies
Raul U. Hernandez-Ramirez is a Research Scientist in Biostatistics at the Center for Methods in Implementation and Prevention Science (CMIPS) at the Yale School of Public Health. He serves as Director of the Dissemination and Implementation Science Methods (DISM) Core at the Center for Interdisciplinary Research on AIDS (CIRA) and is an Affiliated Faculty member at the Yale Institute for Global Health. His work bridges biostatistics, implementation science, and global health research with a focus on practical applications for public health improvement. Dr. Hernandez-Ramirez earned his PhD in Public Health (Chronic Disease Epidemiology) from Yale University in 2018, following an MPhil in the same field in 2016. During his doctoral studies, he conducted research as a predoctoral visiting fellow at the National Cancer Institute (NCI). He further enhanced his expertise through specialized training programs including the Training Institute for Dissemination and Implementation Research in Cancer (TIDIRC) and the Multilevel Intervention Training Institute (MLTI) from NCI, as well as training in optimization of multicomponent interventions using the Multiphase Optimization Strategy (MOST). His research primarily focuses on HIV/AIDS, cancer, and implementation science. He develops and applies causal inference methods for evaluating HIV prevention interventions and methods to account for exposure uncertainty in environmental health studies. His work spans multiple settings including New Haven, other locations in the United States, and low- and middle-income countries, particularly Mexico. He is particularly interested in adapting and developing interventions to increase the uptake of evidence-based practices for HIV and cancer prevention and care, including follow-up care for abnormal cervical cancer screens. He is a member of the Yale Cancer Center (YCC) and the Yale Institute for Global Health (YIGH). Analysis of Dr. Hernandez-Ramirez's recent publications reveals a strong focus on gastric cancer epidemiology through the Stomach cancer Pooling (StoP) Project, examining dietary factors and their relationship to cancer risk. His work prominently features implementation science methodologies applied to HIV prevention and cancer screening programs, particularly in Mexican and other international settings. His research combines rigorous biostatistical methods with practical applications in global health contexts, with significant contributions to causal inference methods and network-randomized trial analysis. Provides expertise, consultations, and technical assistance on implementation science through CIRA's DISM core Contributes to projects in Ending the HIV Epidemic (EHE) priority areas through the CIRA-affiliated IS hub R3EDI Collaborates on research projects in New Haven, other US settings, and low- and middle-income countries including Mexico Offers seminars and trainings on research methods, design, and analysis to CIRA affiliates Dr. Hernandez-Ramirez previously gained substantial research experience in nutrition, environmental health, and cancer at the National Institute of Public Health of Mexico, where he worked as a researcher and instructor and served as project coordinator, data manager, and main statistician for a multistate study. He holds an MSc in Epidemiology and a BSc in Nutrition, establishing a strong foundation for his current work at the intersection of nutritional epidemiology and implementation science.
Lorenzo Farina is a Full Professor at Sapienza University of Rome's Faculty of Information Engineering, Computer Science and Statistics, specializing in Electronic and Computer Bioengineering (ING-INF/06). With over 25 years of academic leadership, he co-founded Italy's first Bioinformatics degree program and established key oncology precision medicine initiatives, maintaining active collaborations with Harvard Medical School's network medicine division. His educational background includes a cum laude Electronic Engineering degree and PhD in Systems Engineering, both from Sapienza University. These foundational studies evolved into pioneering work in positive linear systems theory, evidenced by his highly-cited Wiley textbook Positive Linear Systems: Theory and Applications (2000). Farina's research centers on network medicine – applying complex network science to molecular medicine since his 2004 breakthrough. His work spans cancer mechanisms (breast, glioblastoma, lung), drug repositioning (including COVID-19 applications), and liquid biopsy biomarker development. Current projects focus on miRNA-based network biomarkers for cancer diagnostics and immunotherapy response prediction, integrating multi-omics data through advanced computational frameworks. Analysis of his 15 most recent publications (2024-2025) reveals dominant themes: sexual dimorphism in cancer networks (MIRROR platform), immunotherapy response signatures, and critical examinations of AI's role in precision medicine. His work consistently bridges computational innovation with clinical applications, particularly in oncology diagnostics and therapeutic optimization. His scientific recognition includes: 2001 Guillemin-Cauer Award for best IEEE Transactions on Circuits and Systems article 2014 SysBio Award for annual best publication Farina actively mentors through interdisciplinary programs he established, including the Network Oncology doctoral program. His laboratory collaborations span Sapienza's Oncogenomics and Immunology Laboratories, Harvard's Channing Division of Network Medicine, and clinical departments in oncology and radiology, driving translational research from computational models to patient applications. He leads multiple research teams focused on network-based diagnostics, including the MIRROR platform for cancer disparity analysis and liquid biopsy development teams investigating circulating miRNA networks for early cancer detection across multiple malignancies.
Johanna Rickne is a Professor of Economics at the Institute for Social Research (SOFI), Stockholm University, where she conducts research at the intersection of labor economics, political economics, and gender studies. Her work examines gender disparities in labor markets and political representation, utilizing large-scale register data and natural experiments to analyze causal relationships in social phenomena. She actively contributes to SOFI's research environment through the Labor Market Economics (AME) and GAINS (Gender Analysis and Interdisciplinary research Network) groups. Rickne's research program centers on understanding systemic inequalities through interdisciplinary lenses. Her investigations span gender dynamics in career advancement, political selection mechanisms, and the socioeconomic impacts of family structures. Key methodological approaches include quasi-experimental designs leveraging Swedish administrative data, with particular attention to how gender-traditional norms affect professional trajectories and relationship stability. Current projects address labor market equity for marginalized groups—including women, immigrants, and transgender individuals—and the historical evolution of gender-balanced political representation. Analysis of her recent publications reveals consistent thematic focus on gendered career patterns, political elite formation, and workplace inequality. Her work demonstrates how structural barriers like the 'class ceiling' in politics and gender gaps in meaningful work persist despite formal equality measures. Methodologically, she pioneers the use of municipal-level political data and occupational survey evidence to isolate causal mechanisms, with growing emphasis on sexual harassment dynamics and intergenerational political transmission. Scientific recognition includes: CEPR Fellow Wallenberg Academy Fellow Rickne leads multiple significant research initiatives including 'En jämlik arbetsmarknad i teori och praktik' examining labor market outcomes for vulnerable demographics, 'Hundra års färd mot en jämställd politisk representation' analyzing historical political representation trends, and the Laborocto network fostering interdisciplinary working-life research. Her grant portfolio reflects sustained funding for projects investigating political recruitment barriers, gendered career divergence, and policy interventions for workplace equality. She actively mentors junior researchers through SOFI's collaborative environment while contributing to national policy debates on gender equity. Within SOFI's organizational structure, Rickne operates through the Labor Market Economics group studying education, health, taxation, and crime alongside core labor issues, and the GAINS network facilitating cross-disciplinary gender research. Her workspace in University Road 10 F serves as a hub for analyzing Swedish registry data and coordinating international collaborations with institutions like IZA and the Stockholm China Economic Research Center, where she maintains affiliate status.
Shalmali Joshi serves as Assistant Professor of Biomedical Informatics at Columbia University's Vagelos College of Physicians and Surgeons, where she leads the reAIM lab. She holds verified membership in Columbia's Data Science Institute (DSI) and maintains affiliated memberships with the Foundations of Data Science Center, Health Analytics Center, and Education Center. Her educational trajectory includes a PhD in Electrical and Computer Engineering from the University of Texas at Austin, followed by postdoctoral training at Harvard University and the Vector Institute. Dr. Joshi's research program focuses on developing AI/ML systems that enhance scientific inference and predictive capabilities in biomedical contexts, specifically targeting challenges of generalizability, reliability, and robustness. Her methodological toolkit spans deep learning, reinforcement learning, observational causal inference, and probabilistic modeling to address critical gaps in biomedical data science. She maintains significant cross-disciplinary affiliations with Columbia's SNF Center for Precision Psychiatry and Mental Health and Computer Science department, facilitating collaborative approaches to complex biomedical problems through her reAIM lab.
Steven Wu is an Associate Professor in the School of Computer Science at Carnegie Mellon University, with primary appointments in the Software and Societal Systems Department (S3D) and affiliated roles in the Machine Learning Department, Human-Computer Interaction Institute, CyLab, and Theory Group. Previously, he held positions at the University of Minnesota (Assistant Professor) and Microsoft Research-New York City (post-doctoral researcher). Ph.D. in Computer Science, University of Pennsylvania (co-advised by Michael Kearns and Aaron Roth) His research spans Machine Learning , Algorithms , Privacy , and Fairness , focusing on responsible AI foundations, interactive learning, causal inference, and economic applications. Recent work explores uncertainty quantification and privacy risks in synthetic data. He has received prestigious awards including the NSF CAREER Award and Penn's Rubinoff Award for his dissertation. His group mentors students across Ph.D. , postdoc, and visiting programs, with alumni now at institutions like UC Berkeley, Stanford, and Amazon. Key grants: NSF, Okawa Foundation, Open Philanthropy, Amazon, Google, J.P. Morgan, Meta, Mozilla, Apple, Cisco
Jacob Goldin is a Professor at Stanford Law School, where he conducts research at the intersection of tax law, behavioral economics, and public policy. His work addresses critical questions in tax policy design, judicial behavior, and the economic impacts of government programs. Goldin's research interests center on tax policy, behavioral economics, and law and economics. He examines how individuals respond to tax incentives, the optimal design of tax systems, and the behavioral aspects of tax compliance. His work often combines rigorous empirical analysis with theoretical insights to inform tax policy debates. He has made significant contributions to understanding the Earned Income Tax Credit, child tax benefits, and the behavioral effects of tax salience. His recent publications demonstrate a strong focus on empirical analysis of tax policy impacts, particularly regarding child benefits, tax filing behavior, and the economic consequences of tax design choices. Goldin frequently employs experimental and quasi-experimental methods to provide causal evidence on policy questions, bridging the gap between theoretical tax design and real-world outcomes. Goldin has been actively involved in legal proceedings as an expert, contributing to amicus briefs in significant tax cases including South Dakota v. Wayfair. His scholarly work has appeared in leading law and economics journals including the Yale Law Journal, American Law and Economics Review, and Journal of Public Economics. As an advisor and collaborator, Goldin works with economists and legal scholars across institutions, including the U.S. Department of the Treasury's Office of Tax Analysis. His research often addresses practical policy challenges while maintaining rigorous academic standards, making his work highly relevant to both academic and policy communities.
Professor Robert Elliott is a Professor of Economics and Director of Research in the Department of Economics at the University of Birmingham's Birmingham Business School. His work spans international economics, development economics, environmental and energy economics, and international business, with particular expertise in the Chinese economy, firm behavior, natural disasters, and globalization's environmental impacts. Professor Elliott holds a BA in Economics from the University of Leicester, an MA in Economics from the University of Essex, and completed his PhD at the University of Nottingham under the supervision of Professor David Greenaway, Dr Peter Wright, and Robert Hine. His research focuses on empirical environmental, international trade, development, energy, and labor economics. Key areas include the economics of China and East Asia, empirical environmental economics, economic geography, globalization and environment, natural disasters (floods, typhoons, earthquakes), biodiversity and deforestation, trade and environment, FDI and industrial restructuring, and energy economics. His interdisciplinary approach often combines large dataset manipulation with advanced econometric techniques. Analysis of his recent publications reveals a strong focus on environmental economics, particularly examining the intersection of climate change, natural disasters, and economic outcomes. His work spans historical environmental events in China, contemporary energy and transportation economics, air quality policy evaluation, and the economic impacts of natural disasters across different regions and time periods. A significant portion of his research applies advanced statistical and machine learning methods to environmental policy questions. Professor Elliott serves as an editor for the Sustainable Future Policy Lab and Director of the Trade, Environment, Development and Energy (TEDE) research group. He is also a Co-Investigator on ReLIB as part of the Faraday Institute, a member of Water Challenges in a Changing World IGI, and an Affiliate of the Lloyds Bank Centre for Responsible Business. He actively supervises PhD students across international and development economics and environmental and energy economics. His current projects include the "Brexit Uncertainty Index" and Leverhulme Trust research projects in "Globalisation and the Environment" with Matthew Cole. He has received significant funding including an ESRC grant for "China-UK energy issues" worth approximately £1 million. Professor Elliott is a key member of the Birmingham Plastics Network, an interdisciplinary team of over 40 academics addressing the global plastics problem. This network brings together experts from diverse fields including chemistry, environmental science, engineering, philosophy, linguistics, economics, and law to develop holistic solutions for plastics sustainability.
Professor Ingo Rohlfing is a Professor for Methods of Empirical Social Research at the University of Passau, specializing in advanced methodological approaches in social science research. His work focuses on bridging qualitative and quantitative methodologies to enhance causal inference and research transparency. Current position: Professor for Methods of Empirical Social Research, University of Passau Contact: ingo.rohlfing@uni-passau.de, +498515092720 Professional website: https://ingorohlfing.wordpress.com/ Rohlfing's primary research interests center on causal inference, qualitative and multimethod research, and research transparency and credibility. He has made significant contributions to Qualitative Comparative Analysis (QCA), process tracing, and Bayesian approaches to qualitative research. His work emphasizes methodological rigor and the integration of diverse methodological traditions to address complex social phenomena. His recent publications demonstrate a consistent focus on methodological innovation, particularly in integrating Bayesian statistics with qualitative methods. Rohlfing's 2025 article with Lion Behrens on integrating Bayesian regression analysis with Bayesian process tracing represents a cutting-edge contribution to mixed-methods design. His blog content shows ongoing engagement with critical issues in research transparency, open science, and the practical application of advanced methodological approaches. Rohlfing is actively involved in methodological training, offering courses such as the 5-day remote course 'Introduction to Qualitative Comparative Analysis' through the ICPSR Summer Program and an on-demand seminar on process tracing. His teaching reflects his commitment to making sophisticated methodological approaches accessible to social science researchers. Regular instructor at the ICPSR Summer Program Creator of self-paced methodological training materials Active participant in the DORA (Declaration on Research Assessment) movement
Orla Doyle is a Professor in the School of Economics at University College Dublin and a Research Fellow at the UCD Geary Institute for Public Policy. She serves as Director of the UCD Childhood and Human Development Research Centre and has held various academic positions at UCD since 2004, progressing from Postdoctoral Researcher to full Professor in 2023. Her academic journey includes appointments as Assistant Professor (2011-2017), Associate Professor (2017-2023), and multiple leadership roles including Deputy Head of School and Director of Teaching & Learning. BA (Mod) from Trinity College Dublin PhD from Trinity College Dublin Professor Doyle's research focuses on the economics of human development, particularly examining how early life conditions shape later life outcomes through rigorous experimental methods. Her work spans health economics, labor economics, political behavior, early child development, and policy evaluation methodologies. She emphasizes interdisciplinary collaboration across economics, psychology, medicine, and public health to advance understanding of human capital formation. Her publication record demonstrates consistent research productivity across multiple disciplines, with recent articles examining gender norms, cardiovascular disease prevention, rare disease economics, and early childhood interventions. The research shows a strong emphasis on experimental designs and causal inference methods to evaluate policy effectiveness, particularly in early childhood contexts. A significant portion of her work examines the long-term impacts of interventions through longitudinal studies. Professor Doyle leads major research initiatives including the Preparing for Life study, the longest-running early childhood field experiment in Europe. She has secured substantial research funding from diverse sources including the Irish Research Council, Medical Research Council, and international collaborations. Her professional activities include committee memberships, conference organization, and public engagement initiatives focused on policy relevance and gender equity in economics. She directs the UCD Childhood and Human Development Research Centre, leading a team of researchers focused on early intervention programs. Her work bridges academic research with practical policy applications, particularly through collaborations with Irish government agencies and health services to translate research findings into actionable programs for disadvantaged communities.
Fred Morstatter is a Research Assistant Professor at the Thomas Lord Department of Computer Science, University of Southern California. He serves as Principal Scientist at the USC Information Sciences Institute and Associate Director for USC Data Science, bridging academia and applied research in AI ethics and social media analysis. Research Interests include: Mitigating algorithmic bias in NLP systems Developing robust social media content analysis frameworks Creating hybrid human-machine forecasting models for geopolitical events Studying causal relationships in online-offline event dynamics Advancing crowdsourcing methodologies with ethical AI Recent Article Trends examine: Temporal knowledge graph forecasting without explicit training data Gender bias quantification in named entity recognition Characterizing misinformation through network analysis Developing fair decision-making attribution mechanisms Mapping moral valence in crisis-related social media discourse Student Supervision includes advising PhD candidates exploring: Implicit biases in LLMs Computational social science Hate speech detection Persuasion modeling in forecasting systems Contact: fred@isi.edu | Google Scholar | USC ISI
B. Douglas Bernheim is the Edward Ames Edmonds Professor of Economics at Stanford University's Department of Economics. He serves as the Academic Council Faculty Director of Undergraduate Studies, overseeing academic programs and policies for undergraduate economics students. His research spans behavioral economics, public economics, game theory, and financial economics, with notable contributions to rationalizability in game theory, coalition-proofness, and behavioral welfare economics frameworks. Professor Bernheim has received prestigious recognitions including an honorary doctorate from the University of Zurich and the 2022 Exeter Prize for groundbreaking work in experimental economics. His work often bridges theoretical economics with practical policy implications, particularly in areas like financial education and addictive behaviors. Research Interests: - Behavioral Welfare Economics - Social Motives for Economic Choices - Financial Education Policies - Theories of Collusion and Market Structures His recent publications explore interventionist policies in welfare states, peer influence in financial decisions, and the empirical foundations of decision theories like cumulative prospect theory. Bernheim's work emphasizes rigorous experimental methods and real-world policy applications, reflecting his dual focus on academic theory and societal impact.
Nicolás Ajzenman is an Assistant Professor of Economics at McGill University , with affiliations at J-PAL and IZA. He previously held positions at the Sao Paulo School of Economics-FGV and the Inter-American Development Bank. PhD in Economics (Sciences Po) Master in Public Administration-International Development (Harvard University) Master's in Economics (Universidad de San Andres) BA in Economics (Universidad de Buenos Aires) His research focuses on applied microeconomics at the intersection of development economics , political economy , and behavioral economics , utilizing randomized control trials and quasi-experimental methods to study education, immigration, and corruption in Latin America. Recent publications highlight trends in democracy's impact on social preferences , behavioral interventions in education , and migration's socioeconomic effects . His work spans experimental designs, policy evaluation, and novel data sources for development contexts. Research Affiliate at J-PAL, IZA, EGAP, CSDC, ISID Associate Editor, Journal of Economic Behavior and Organization Ajzenman collaborates with Latin American governments through advisory roles (e.g., Inter-American Development Bank, Argentina’s Nudge Unit) and has conducted large-scale workshops in Uruguay, Dominican Republic, and Peru. His teaching includes advanced econometrics, behavioral economics, and development economics courses.
