After earning degrees in computer science and biochemistry, I spent several years teaching, driven by a desire to make a meaningful impact. During the pandemic, I realized the importance of contributing beyond the classroom to create a future for my two children and expand our very-fragile human consciousness, aiming to deepen our understanding of what it means to be conscious.

During my first two years in the lab, I focused on model and task design, data collection, and analysis of human behavioral data within the context of reinforcement learning. My work also included studying behavioral data in populations with alcohol use disorder and depression. Additionally, I designed and maintained this website, enhancing my proficiency in coding and web design, and further populating the idea that we're all living in a simulation.

As a second-year PhD student, my research aims to develop a novel computational model that clarifies how feature-level uncertainty influences various learning phenomena. Using real-time, sub-second measurements of dopamine and serotonin via fast-scan cyclic voltammetry in patients undergoing deep brain stimulation placement, I seek to detail the relationship between dopamine as a reward prediction error and model a measure of state uncertainty.

My career goal is to integrate these models into tools that can enhance therapies for psychiatric disorders linked to altered decision making — such as addiction, PTSD, and depression. Ultimately, I hope to provide a guide to navigating the complex algorithms of the human mind, much like finding the ultimate question to the answer of life, the universe, and everything.

>> Interests

• Reinforcement Learning
• Behavioral Neuroscience
• FSCV

>> Education

	Ph.D. Neuroscience, Student Wake Forest University School of Medicine
	B.S. Biochemistry, 2022 University of North Carolina - Greensboro
	B.A. Computer Science, 2014 Wake Forest University