About
I am a Data Science graduate student at Vanderbilt University. My research focuses on human-aligned AI, personalization, and adaptive models for understanding individual variation. I am also interested in applied ML areas such as recommender systems and user modeling. I aim to contribute to AI that is more personalized and impactful in real-world settings.
Research Interests
Current Research Projects
Personalized Representational Connectivity with fMRI-Guided CLIP
Human visual perception emerges from coordinated activity across many interconnected brain regions. To develop AI models that better reflect this biological organization, we fine-tuned CLIP to predict both the representational structure within individual visual cortical areas and the functional connectivity patterns linking them. Using lightweight model adaptations—such as layer-specific feature reweighting and low-rank personalization—the model successfully captured individual differences in neural processing across 14 visual regions. Additionally, the fMRI-aligned models achieved zero-shot generalization to MEG dynamics, demonstrating a pathway toward personalized and biologically grounded multimodal AI systems.