At the National Institutes of Health (NIH) – National Institute of Mental Health (NIMH), I investigate human decision-making, reward valuation, and temporal learning through behavioral experiments grounded in reinforcement learning and computational cognitive neuroscience.
I analyze behavioral pilot data and support the development and refinement of online experiments using jsPsych, Python, and R. My work evaluates reward-based learning, temporal prediction accuracy, and how reward magnitude, delay, and attentional demands affect decisions.
At Wells Fargo Wealth Management (WIM), I analyzed client–advisor interactions and identified 10+ behavioral and systemic risks. I also supported an AI automation initiative that saved 500+ hours monthly across departments, and presented findings to leadership to inform process changes.
