I’m a passionate AI researcher focusing on time-series modeling, multimodal AI with large language model integration, and applied AI in wearables. My expertise lies in developing deep learning architectures to process diverse data types efficiently, enhancing machine learning models for various medical tasks, and applying traditional statistical approaches to validate model performance.
I am committed to integrating AI techniques to improve medical equitability and accessibility, and I strive to contribute to advancing healthcare technologies. Additionally, I have experience collaborating on research projects and a strong foundation in computer science, mathematics, pharmacology, and basic sciences.

Research Interests

Large Multimodal Models in Medical Imaging

Designing deep learning architectures to efficiently process diverse data types (from chest x-rays, echocardiograms, ECG, and text) at scale.

AI Techniques in Wearable Technologies

Developing PPG noise reduction models and collaborating with Apple on use of Apple Watch in cardiopulmonary fitness prediction.

Time-Series Models for Healthcare Monitoring

Focusing on deep learning for analyzing health monitoring data, including irregularly sampled, multivariable time series.