I’m a research fellow at the Learning and Decision-Making Unit at the National Institute on Drug Abuse (NIDA), which is part of the National Institutes of Health (NIH) — the largest biomedical research agency in the world. I earned my Ph.D. in Psychology from The Ohio State University, where I specialized in cognitive and computational neuroscience in the Model-based Cognitive Neuroscience Lab.

My work bridges psychology, cognitive neuroscience, and computational modeling to understand how people learn, make decisions, and — more broadly — how intelligence emerges in the human brain.

I’m now exploring data science and AI opportunities in industry, where I aim to apply my analytical rigor to real-world challenges.

• Programming & Tools: Python, R, MATLAB, Git, Bash, PySpark, Jupyter
• Machine Learning: Scikit-learn, PyTorch, TensorFlow, XGBoost, deep generative models
• Statistics: Bayesian inference, generalized linear models (GLMs), mixed-effects models, model simulation
• Data Science: Data wrangling, data visualization, experimental design, A/B testing
• Cognitive & Computational Modeling: Drift diffusion models (DDM), reinforcement learning models, model-based analysis of behavior and neuroimaging data
• Neuroimaging & Neuromodulation: fMRI preprocessing and analysis, model-based fMRI, SPM, transcranial magnetic stimulation (TMS), data quality control
• Soft Skills: Strategic thinking, fast learner, scientific writing, mentoring, cross-disciplinary collaboration

Visit my Research page for cognitive science + neuroscience projects, or see my Data Science page for applied ML and AI work.

• ResearchGate
• LinkedIn
• Google Scholar