Machine Learning Research
Single object tracking, one-stream trackers, deformable masked representations, domain generalization, and federated generalization.
PhD student in Computer Science at the University of British Columbia, focused on single object tracking, domain generalization, LLM/NLP systems, and secondary use of medical data. I combine research publication, software engineering, and academic teaching with a computer systems background.
$ whoami Omar Abdelaziz - ML researcher, software engineer, PhD candidate $ focus --current single object tracking | domain generalization | clinical text correction | medical data ethics $ links --primary github.com/omar-ashinawy | scholar.google.com/citations?user=pY9RyXMAAAAJ
My work spans machine learning research, clinical NLP/LLM tooling, visual tracking, domain generalization, middleware automation, teaching, and systems projects.
I am strongest where research ideas need to become reliable software: models, data pipelines, reproducible experiments, readable technical writing, and interfaces that help people use the work.
Single object tracking, one-stream trackers, deformable masked representations, domain generalization, and federated generalization.
Clinical text correction, deterministic rule layers, multi-agent LLM pipelines, spotting/proposal workflows, and medical-report reliability.
API middleware automation, Swagger generation, Java/C++/Python systems projects, agile software engineering, and academic instruction.
Public repositories from @omar-ashinawy, plus resume projects that show the range from research code to systems coursework.
Python research code connected to federated/domain-generalization mixture-of-experts work.
Implementation of the MIT 2019 paper Learning the Face Behind a Voice using an audio encoder and face decoder.
C++ assembler that converts MIPS assembly into binary machine code.
Content-based multimedia retrieval with relational database design and a Java GUI.
Dataset/support repository tied to a deep-learning framework built from scratch with CNN support.
Decision tree project showing applied machine-learning fundamentals.
These are the project entries from the resume, grouped as practical evidence.
Automatic grading system for Java code questions using Google Gemini API.
Implementation of the MIT 2019 paper Learning the Face Behind a Voice.
Deep-learning framework implemented from scratch in Python with CNN support.
Relational database design and GUI implementation for multimedia retrieval.
C++ program that solves up to 100 simultaneous equations.
Simulation of process-allocation algorithms with a reactive Qt GUI.
Converter from MIPS assembly to binary code.
Research, industry ML, integration engineering, and teaching roles.
Publications listed from the resume and current portfolio page.
Computer science and computer systems foundation across graduate research and engineering training.
University of British Columbia, Canada
University of British Columbia, Canada
Ain Shams University, Egypt
The practical stack behind the research and software work.
Currently pursuing the PhD at UBC, researching domain generalization in visual trackers, and writing up the next paper.
Email is best for research collaboration, engineering roles, and teaching/research inquiries.