I am a Cognitive Science student at Rutgers University, with a minor in Data Science and Psychology. I build reproducible Python workflows to study how people make decisions, analyze behavioral data, and communicate research findings clearly.

I currently work as a Research Assistant in Rutgers' Glass Lab, where I develop and evaluate behavioral models using Prospect Theory, delay discounting, and participant-level data.

• Behavioral decision-making, cognition, and judgment under uncertainty
• Research data pipelines, model fitting, and quantitative evaluation
• Reproducible analysis with Python, pandas, NumPy, and SciPy
• Clear technical communication for research teams and broader audiences

One example of my research work: an editable, reproducible codebase for modeling prosumer energy-sales decisions in a repeated market. It includes PT-TW and PT-TW-DD implementations, fitted parameters, canonical predictions, and final model-comparison findings.

A privacy-conscious, reproducible audit of DeepFace output patterns across demographic labels. The project focuses on aggregate age-estimation, agreement, and disparity analysis while keeping face-level source data out of the public repository.

• Rutgers University - B.S. Cognitive Science, minor in Data Science and Psychology, expected May 2027
• Middlesex College - A.A. Liberal Arts, Dean's List and Phi Theta Kappa

Python pandas NumPy SciPy R SQL Data Cleaning Exploratory Data Analysis Model Fitting Git GitHub SPSS PsychoPy

Explore my energy-market modeling and responsible-AI audit projects, or browse this profile for future research and data work.