Applied research at the intersection of human behavior and AI systems

Built AI systems and agentic workflows to automate UX research, BI analytics, and enterprise LLM applications for product and decision support

• Architected a natural language analytics interface by integrating a full-stack Umami event pipeline with a Python semantic layer and agentic orchestration framework
• Designed and implemented a synthetic research engine to automate frontend usability testing, simulate focus groups, and generate enhanced evaluation datasets for agentic product development
• Increased research throughput 12× by engineering MCP-based agentic frameworks to automate thematic analysis, project management workflows, and product communications
• Contributed to the development and deployment of LLM-based virtual assistant systems for Fortune 500 enterprise applications

Applied AI methods to accelerate mixed-methods research and hierarchical statistical analysis in support of data-driven product strategy

• Led experimental design, survey methodology, and cross-functional project management for a foundational mixed-methods research initiative supporting development of an experimental AI product
• Applied multivariate regression modeling to survey data to characterize user attitudes toward agentic AI capabilities and deliver strategic recommendations to product and engineering teams
• Moderated and synthesized 20+ remote user interviews to contextualize quantitative findings and inform product strategy through insight-driven narratives
• Developed applied AI systems to automate conversational design workflows for research and experimentation

Led applied AI and behavioral analytics initiatives to inform product strategy and enterprise decision-making in consumer goods and retail

• Created a behavioral analytics framework and evaluation criteria to quantify the impact of UI/UX redesigns, enabling data-driven decision-making for product development
• Led a cross-functional initiative with executive leadership and external stakeholders to design an agentic chatbot for Enterra’s consumer insights platform, aligning product capabilities with client and business requirements
• Engineered NLP pipelines to extract and analyze unstructured text data, supporting predictive modeling for dynamic pricing strategies in Consumer Packaged Goods

Co-led a mixed-methods UX research initiative to inform B2B product strategy and guide a platform redesign

• Synthesized enterprise user personas from 12 stakeholder interviews to shape product direction by aligning cross-functional teams around key use cases
• Simplified stakeholder decision-making in Power BI by standardizing dashboard visualizations to reduce visual complexity by 2/3

Led research program investigating how negative emotions influence what people remember and how accurately individuals can judge the reliability of emotional memories and experiences

• Graduate Prize Fellow
• Led end-to-end research operations, including IRB approval, recruitment, protocol design, multi-session data collection, and collaboration with interdisciplinary teams
• Trained machine learning models on multimodal data and evaluated their ability to accurately predict emotional intensity using theory–driven emotional features
• Reanalyzed a large 9/11 dataset along with a new Covid-era longitudinal panel using dimensionality reduction techniques to evaluate how current mood biases memories of past negative experiences
• Implemented computational models to quantify how well confidence tracks performance under negative emotional experiences

Conducted neuroimaging research at the National Institute on Drug Abuse to identify the brain mechanisms underlying nicotine addiction

• Intramural Research Training Award
• Led independent research integrating multimodal datasets to evaluate Psilocybin's effectiveness as a smoking cessation aid
• Applied advanced regression models to 100,000+ observations to estimate treatment effects, control for confounders, and reveal complex patterns