Bridging data science and social impact through data-driven research. I specialize in cutting-edge AI and data science techniques to automate and streamline academic research and build, curate, and analyze critical social science datasets, with expertise in Natural Language Processing (NLP) and research methodology.
Build and maintain high-integrity social science datasets from diverse, multi-lingual, and often unstructured sources. Designing rigorous data collection strategies, implementing comprehensive quality control frameworks, and managing research teams for large-scale data products.
Develop custom, Python-based AI and computational tools to automate and streamline multi-step academic research workflows. This process includes leveraging Large Language Models (LLM) and APIs to efficiently extract, categorize, and structure complex variables, significantly reducing manual effort in coding and data preparation.
Apply and develop robust Machine Learning (ML) and Deep Learning models to solve critical social and public policy questions. This specialization encompasses building advanced classification systems for phenomena such as predictive analysis in social conflict, conducting sentiment analysis, and performing rigorous accuracy testing to ensure model reliability for research application.
