
Worker Posture Analysis
Benchmarking state-of-the-art pose estimation algorithms across camera configurations for real-world 3D human pose analysis.
Ph.D. Candidate in Data Science at the University of Virginia, building deep learning systems for computer vision and 3D human understanding.
Deep learning and computer vision research applied to real-world 3D understanding

Benchmarking state-of-the-art pose estimation algorithms across camera configurations for real-world 3D human pose analysis.

We benchmark three state-of-the-art 3D pose estimation models on biomechanical joint angle accuracy and discover that models with lower MPJPE produce higher joint angle error — challenging a core assumption in the field.
A large-scale 3D pose estimation dataset of 5,966 professional tennis serves from broadcast video, enabling motion classification, player identification, and performance prediction using deep learning at unprecedented scale.

A deep learning approach for predicting pediatric Crohn's disease from histopathological whole slide images, with investigation of inter-site generalizability and site-specific artifact mitigation.
Building and benchmarking state-of-the-art pose estimation and 3D reconstruction models
Designing transformer and CNN architectures for 3D pose lifting, generative modeling, and domain adaptation
Deploying ML pipelines for large-scale video analysis, medical imaging, and human motion understanding