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Amr Abujabal

Computer Science | Cloud & Backend | Computer Vision

I build computer-vision pipelines that turn match footage into player analytics, and I ship full-stack apps to production.

A little background

I'm a fourth-year Computer Science student at UBC Okanagan, graduating in May 2027. Backend and cloud work is home base, but I'll go wherever the project needs me in the stack.

Most of my projects mix ML with sports. I built a system that tracks every soccer player on the pitch from a single camera, and a World Cup predictor, trained on 49,000 historical matches, that ran live through the 2026 tournament.

PitchVision exists because pro-level player tracking costs more than most amateur clubs can spend. One camera and the right models close most of that gap. That is the kind of problem I want to keep working on.

School
UBC Okanagan
Graduating
May 2027
Focus
Backend · Cloud · Computer Vision

Selected work

PitchVision

Computer Vision / ML + Cloud

In Progress

Single-camera player identification and performance analytics for amateur soccer clubs. Detects and tracks every player frame-by-frame, computes per-player physical and tactical metrics (distance, speed zones, heatmaps, pressing), and serves them through a REST API to a coach-facing dashboard. 126 tests passing.

YOLOv10 SAM 2 TransReID OSNet FastAPI Next.js PostgreSQL Docker GitHub Actions

Tactical diagram of a soccer pitch with player bounding boxes, trajectory lines, and a heatmap contour

World Cup 2026 Predictor

Full-Stack ML App

Live match outcome predictor for the 2026 FIFA World Cup. XGBoost classifier trained on 49,000+ historical matches with ELO-based features predicts every knockout match. Includes a live bracket, user predictions, leaderboard, and auto-polling from football-data.org during the tournament.

XGBoost scikit-learn FastAPI React SQLAlchemy Tailwind Vercel Railway

Screenshot of the live AI Bracket Challenge: model stats and the knockout bracket picker

ByteBites

COSC 310 Software Engineering

RESTful food-delivery backend using a 3-layer architecture (API -> Service -> Repository) spanning 8 features: auth, menu management, ordering, delivery tracking, pricing, payment, and notifications. JWT authentication with role-based access control (User / Manager / Admin).

FastAPI Python PostgreSQL Docker GitHub Actions Pytest

What I work with

Languages

Python Java C C++ SQL JavaScript

Backend & Web

FastAPI React PostgreSQL MySQL REST APIs JWT

Cloud & DevOps

Google Cloud Platform Docker Git GitHub Actions CI/CD Linux

ML & Data

NumPy pandas scikit-learn XGBoost YOLOv10 SAM 2 TransReID/OSNet Vision-Language Models Multi-Object Tracking

Let's get in touch

I'm looking for internships. If you're hiring, or you want to talk about tracking soccer players with one camera, email me.

Email Me