Curriculum Vitae
Jeffrey Clark
Builder of tools & data for modern policy research
Builder of tools & data for modern policy research
Currently completing first-year coursework in mathematics, microeconomics, macroeconomics, and econometrics.
Specialized in data-intensive economic research with a focus on development, resource, and policy analysis. Built strong competence in econometrics, data science, and modern empirical methods through coursework and thesis work.
Co-authored with Tamina Matti
Investigating the effects of rural road upgrades on agricultural output in northern Mozambique using remote sensing and machine learning methods. Findings contributed to research conducted at the World Bank.
Completed advanced training in causal inference, randomized evaluations, and data analysis for policy design. Developed skills in evaluating the effectiveness of social programs using modern empirical methods.
Built a foundation in economics, management, and empirical methods, with a strong interest in behavioral and environmental economics. Discovered a passion for experimental design and data-driven analysis through thesis work and large-scale game-theoretic experiments.
Co-authored with Marcus Lindeberg-Goni
Investigating how climate change characteristics affect resource management through a dynamic common pool resource experiment with university students. Used large-scale game-theoretic experiments (100 sessions, 416 participants) and secured a $6,700 research grant.
Engaged with the Aerial History Project, an international research initiative digitizing and processing 1.8 million historical aerial photographs across 60+ countries. The project enables research on urbanization, land use, and development history using high-resolution geospatial data.
Contributed to the development of large-scale raster mosaics through stitching pipeline engineering and georeferencing (GCP) quality control. Developed orchestration tools to automate stitching workflows across supercomputer (Savio) and cloud environments. Coordinated labeling workflows and performed quality assurance for training data used in machine learning models.
Contributed to multiple research projects led by Associate Professor Marieke Bos, including studies on the effects of mergers on employee mental health and the long-run impact of mental illness diagnoses on life outcomes.
Worked extensively with large-scale Swedish register data from SCB, performing data preparation, advanced cleaning, variable construction, and regression analysis using Stata. Responsible for end-to-end empirical workflows, from raw data processing to final estimation and robustness checks.
Engaged in research with Professor Anna Dreber Almenberg. Currently co-authoring a study on gender discrimination in Swedish academia's grant allocation, pioneering techniques to parse publication titles from thousands of heterogeneously formatted documents.
Supported the research of Assistant Professor Anne Karing, evaluating the impact of social incentives on the completion of child immunization programs in Sierra Leone. Oversaw survey data collection and developed an online monitoring tool.
Founded and developed RegiStream, an open-source tool that automates the labeling, translation, and processing of Swedish register data. The tool is used by researchers and public agencies to streamline register-based research workflows.
Presented RegiStream at Statistics Sweden (SCB), the Swedish National Audit Office (Riksrevisionen), and a workshop at the Stockholm School of Economics.
RegiStream supports reproducible research and metadata-driven analysis across Stata, Python, and R, and is designed to serve the broader academic and microdata research community.
Co-founded the student-run investment fund at the Stockholm School of Economics and helped grow it from concept to a fully operational organization with 120+ members and over $110,000 in assets under management. Prioritized broader student engagement across programs and backgrounds.
Today, the fund manages over $180,000 USD, maintains a membership of ~80 active students, and continues to thrive as a hands-on educational platform for students interested in financial markets.
Open-source package for automating the labeling, translation, and processing of Swedish register data (SCB and other sources). Enables seamless integration of register metadata into analysis workflows across Stata, Python, and R. Supports reproducible research and modern data pipelines for register-based studies.
Open-source tooling for automating and scaling the aerial photo stitching pipeline for the Aerial History Project. Includes orchestration of cluster-based workflows (Savio supercomputer + cloud VMs), integration with Docker/Apptainer containers, automated job management, and logging. Developed to support creation of large-scale raster mosaics for machine learning and geospatial analysis.
Project developing a program to detect rural road upgrades using publicly available satellite imagery (Sentinel-2, MODIS), primarily using the Google Earth Engine Python API. The road upgrade-detection is done through a random forest model trained on image-differencing data.