Molecular & Cell Biology undergrad at UC San Diego working at the intersection of the wet lab and code — I build imaging pipelines, computer-vision tools, and analysis software for biological R&D.
I'm drawn to problems where careful bench work meets quantitative software: turning microscopy stacks into measurements, and turning measurements into things that help people.
3D imaging & microscopy — volumetric tissue clearing, whole-mount immunofluorescence, and confocal z-stack pipelines (currently mapping nerve–cancer crosstalk in the pancreatic-cancer microenvironment).
Computational image analysis — segmentation, morphometrics, and validation on multi-channel confocal data.
Applied computer vision — real-time, privacy-first pose estimation in the browser.
Device & assay engineering — 3D-printed lab tooling and patented liquid-handling components.
Rehabibi — a real-time, in-browser computer-vision physical-rehabilitation coach. Uses webcam pose estimation and 3D goniometric vector math to track joint angles, isometric holds, and rep cadence, giving live form feedback. Fully client-side with zero video retention.
React · TypeScript · MediaPipe Pose · WebAssembly
PanIN-segment — a machine-learning pipeline to automatically segment PanIN lesions from normal ducts and debris in 3D confocal microscopy stacks. Multi-channel segmentation and morphometric feature extraction across 70k+ candidate objects, benchmarked against manual annotation with Dice, IoU, Cohen's κ, and Hausdorff distance.
Python · scikit-image · image analysis
Wet lab: immunofluorescence · tissue clearing (RapiClear) · vibratome sectioning · 3D cell co-culture · confocal & super-resolution imaging
Code & analysis: Python · TypeScript / React · image segmentation · data analysis · computer vision