Curriculum Vitae

Ph.D. in Mechanical Engineering

• Dissertation: "Autonomous Methods of Measuring Native and Implanted Joint Kinematics from Single-Plane Fluoroscopic Images"

B.S. in Mechanical Engineering, Magna Cum Laude

• GPA 3.7/4.0
• Honors thesis: "The Effect of Gaussian Blurring on Femoral Implant Segmentation by a Convolutional Neural Network"

Senior AI Architect

• Engineered a 3D reconstruction pipeline for cone-beam CT, enabling clinical imaging on refurbished hardware at a fraction of new-equipment cost.
• Developing ML models for orthopaedic surgical planning and ligament modeling, progressing toward FDA clearance; architected the company's quality management system and FDA regulatory submission pipeline.

Machine Learning Research Intern

• Built predictive models for clinical outcomes in total shoulder arthroplasty patients via statistical shape models, radiomics, and contrastive learning.
• Identified preoperative risk factors for postoperative complications using statistical shape models and vision transformers on a proprietary TSA patient database.

Graduate Research Assistant

• Led development of Joint Track Machine Learning (JTML), the first software to autonomously measure joint kinematics with clinical accuracy from single-plane fluoroscopy — now used by ~10 laboratories across the US, Japan, Canada, and Belgium.
• Mentored 25 undergraduate research assistants on machine learning and computer vision projects.

Product Research and Development Intern

• Quantified the effect of surgical variability on implant coverage for unicompartmental knee arthroplasty, informing implant design decisions.
• Built ML and PCA models linking surgical kinematics to clinically relevant patient outcomes.

Undergraduate Researcher

• Calibrated and validated a CNN for segmentation of knee implants from fluoroscopic images; characterized network robustness to image degradation (published as honors thesis).