Behavioral Data Scientist · Applied AI · Decision Systems

Psychology-trained researcher building reproducible data workflows, behavioral models, and practical AI applications.

LinkedIn • GitHub • Publication

I'm a behavioral scientist with a background in psychology, quantitative research, and applied AI.

My work sits at the intersection of human behavior, data science, and decision systems.
I'm especially interested in learning, experimentation, model evaluation, and building tools that make analytical thinking practical.

What you'll find here:

• behavioral data science projects
• applied AI and LLM explorations
• reproducible analysis workflows
• research-driven technical work

Designing experiments, structuring data, and translating behavioral questions into quantitative workflows.

Building Python-based AI workflows and exploring practical use cases for model evaluation, automation, and intelligent systems.

Working on problems around learning, sequential decisions, and the overlap between human cognition and computational models.

Built a Python-based workflow to collect, structure, and analyze video-level engagement data for behavioral research.

Worked on research comparing recurrent neural networks and human learners in restless bandit tasks.

Applying computational modeling in Python and Stan to learning and decision-making data.

• M.Sc. in Psychology
• MIT Applied AI & Data Science Program
• Published research in behavioral science
• Research experience in experimental psychology, behavioral modeling, and decision-making

• LLM applications with real practical value
• behavioral modeling and evaluation
• reproducible AI / data science workflows
• human-centered decision support systems

This GitHub is where I document projects around behavioral data science, applied AI, experimentation, and decision systems as well as some fun leisure projects.