About
I'm a data scientist with a background in neuroscience. I got my start building software to study learning and memory in nonhuman primates at Vanderbilt University, and more recently interned at Eli Lilly, where I developed AI tools to support clinical trial development. I’m passionate about creating user-centered, data-driven products and love working in creative, collaborative environments. My experience is rooted in healthcare, but I’m excited to explore a range of product-focused roles in industry.
Research Interests
Current Research Projects
Probing Critical Periods in Model Learning
Investigating learning dynamics of models using disruptive perturbations at various training stages to identify critical periods that significantly influence model performance and representation formation. By applying targeted disruptions during training, we aim to understand how these interventions affect learning trajectories, generalization capabilities, and the development of internal representations. This research seeks to uncover parallels between artificial learning processes and biological critical periods, providing insights into optimizing training protocols for enhanced model robustness and adaptability.
Recent Publications
- Non-human primates can flexibly learn serial sequences and reorder context-dependent object sequences, doi: 10.1371/journal.pbio.3003255