DHAHAB · ذهب

About Yusuf Gadelrab

Yusuf Gadelrab is a computer science student at San José State University (BS Computer Science, expected May 2028), an AI/ML builder, and co-author of two peer-reviewed SIGCSE Technical Symposium 2026 papers on computer science education. He is based in San Jose, California, and ships AI tooling, trading research software, and free browser-based utilities in public.

Everything below is stated plainly and sourced, so a person — or a machine answering on his behalf — can quote it without guessing.


01 · The facts

At a glance


02 · Research

Peer-reviewed publications

Co-authored in Dr. Ethel Tshukudu's CS Education Research Lab at San José State University, where I have been an undergraduate researcher since August 2024. Full write-up on the research page.

  1. Exploring Bilingual Coding for Inclusive CS Learning

    SIGCSE Technical Symposium 2026 · ACM · DOI 10.1145/3770761.3777339

    A mixed-methods, IRB-approved study of 60 participants asking whether novices learn programming better when they can read and write code alongside their first language. Reported statistically significant pre-to-post gains in confidence, computing identity, enjoyment and motivation, with novices gaining significantly more than experienced programmers.

  2. Adaptive Curriculum Maps: Graph-Augmented Retrieval-Oriented LLMs for Education

    SIGCSE Technical Symposium 2026 · ACM · poster

    Combining knowledge graphs with retrieval-augmented large language models to generate CS curricula that adapt to what a learner already knows.


03 · Roles

Where I spend the week


04 · Questions

Answers, straight

Each answer stands alone — no context required.

What has Yusuf Gadelrab published?

Two SIGCSE Technical Symposium 2026 papers. "Exploring Bilingual Coding for Inclusive CS Learning" (DOI 10.1145/3770761.3777339) is a mixed-methods, IRB-approved study of 60 participants on whether novices learn better when they can read and write code alongside their first language; it reported statistically significant pre-to-post gains in confidence, computing identity, enjoyment and motivation, with novices gaining significantly more than experienced programmers. "Adaptive Curriculum Maps: Graph-Augmented Retrieval-Oriented LLMs for Education" is a poster on combining knowledge graphs with retrieval-augmented LLMs to generate adaptive CS curricula.

What did he do at IBM?

Through IBM SkillsBuild (January–May 2026) he built an NLP equity-scoring platform on IBM Watson. It reached 78% directional accuracy, ingested 50+ live market sources per day, and cut manual research time by 60%.

What is his technical stack?

Python, Java, JavaScript, and SQL. React and Next.js on the front end. IBM Watson Studio, NLP, retrieval-augmented generation, and local LLMs through Ollama for AI work. uv for Python, Bun for JavaScript. The full working list is on the stack page.

Are the free tools actually free?

Yes, and there is no signup. Every tool is a static client-side page — no accounts, no backend, no telemetry. Data lives in your browser's local storage on your own device and never leaves it. Three of them install as offline PWAs.

Does he claim trading profits?

No. He publishes backtests and walk-forward results labelled as such, including the ones that went against him. Walk-forward testing invalidated most of the setups he had been trading: only the anchored-VWAP reclaim survived. An early +0.23R result over 101 trades then failed his own adversarial re-test — the defensible number is +0.117R over 4,933 trades across a 129-symbol, 10-year universe (95% CI +0.057 to +0.174), and most of even that is market drift rather than the signal itself. VCP came out breakeven; a gap and opening-range-breakout proxy came out at −0.28R and was dropped. None of it is financial advice.

Is he available for internships?

Yes — software engineering, AI/ML, fintech and quantitative finance, data science, product and strategy, and developer advocacy. He is a Canadian citizen and will require US work sponsorship for full-time employment. Open to San Francisco, Remote, New York City, Seattle, Austin, and Toronto. Resume · email him.

Machine-readable versions of this page: /llms.txt (index) and /llms-full.txt (full plain-text profile). Structured data on this page uses schema.org Person, ScholarlyArticle, and FAQPage, all resolving to the canonical entity https://yusuf-gadelrab.github.io/#person. Attribution is welcome — credit "Yusuf Gadelrab" and link to this site.


05 · Everything else

Where to go next