Swing Optimizer Pro

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Swing Optimizer Pro is a Python-based diagnostic tool that processes 3D motion capture data from OpenCap to extract kinetic metrics from swing kinematics, delivering athlete-specific feedback to improve mechanical efficiency and performance. The system runs an automated pipeline that uses raw motion capture files, applies a weighted composite scoring model across key biomechanical variables, and outputs prioritized recommendations benchmarked against evidence-based standards. Designed as a translational framework to bridge the gap between data-heavy motion analysis and actionable coaching insights — making advanced biomechanical screening accessible to athletes.

 Pitching Injury Risk Model

A kinematic injury risk model for baseball pitchers using Driveline's publicly available motion capture dataset of 99 pitchers ranging from high school to Minor League Baseball. A six-factor composite scoring system was developed, weighted by literature,  with elbow extension velocity (30%) and shoulder external rotation (25%) as the dominant predictors, since these correspond most directly to UCL and rotator cuff injury mechanisms. The central finding was that throwing velocity and injury risk are essentially independent (r = 0.079), meaning mechanical efficiency is highly indicative of arm health, which is validated by the fact that MiLB pitchers showed the lowest risk scores despite throwing the hardest. The tool outputs individual reports with percentile rankings and tailored recommendations. The most actionable takeaway being that 83% of 90+ mph throwers achieve elite velocity with acceptable risk, demonstrating that the path to high velocity through efficient mechanics is not only possible but actually the norm among successful pitchers.

Applying tissue engineering concepts for electrospinning-based scaffold fabrication to be used in neurovascular Blood Vessel Mimics (BVMs) for clinical in vitro device testing applications. I'm the lead in SEM imaging and SIMPoly, to measure and characterize fiber morphology while quantitatively  analyzing  fiber structures. Optimized scaffold fiber morphology and density with an environmentally safer solvent solutions to enhance lab safety, reliability, and reduce environmental hazard. Additionally, pioneered the fabrication of nanofibers, yiedling optimal cell adhesion to the scaffolds— improving physiologic relevance and model capabilities.