About me
I currently work as an AI Engineer at TrAIngle AI, where my work spans machine-learning research and engineering, full-stack development, and platform work, taking AI-driven software from idea to a secure, working product. Day to day that means moving between research and production: prototyping models, building the interfaces and backend systems around them, hardening security, and writing the documentation that keeps a growing codebase understandable. I like sitting close to both ends of that pipeline: the research questions that shape what a system should do, and the engineering discipline that makes it reliable enough to ship.
Alongside that, I'm a driven student passionate about artificial intelligence and machine learning, with a growing portfolio that spans competitive data science and published research. I'm the winner of the WiDS Global Datathon 2026 (High School Track), the first high school student in Jordan to receive this international recognition, and co-author of an accepted research paper applying SciBERT and Graph Neural Networks to detect AI-generated scientific content. I've also completed a wide range of specialized courses in deep learning, computer vision, generative AI, and reinforcement learning from institutions including Stanford University, DeepLearning.AI, IBM, Meta, and the University of Michigan.
TrAIngle AI is where I get to turn that research energy into real systems, working alongside the amazing founder, Maen Hourani.
Research
My research sits at the intersection of NLP and graph learning, and I care about making it possible to tell trustworthy scientific writing apart from AI-generated content.
- ResearchNet: a novel framework combining SciBERT embeddings with Graph Neural Networks to detect AI-generated scientific text, accepted for presentation at AEECT 2026 and to be published in IEEE Xplore, indexed in Scopus.
- IEEE Jordan Student Paper Contest: selected as one of 33 accepted papers out of 110 submissions (top 30% acceptance rate).
Competitive data science
Five global Kaggle competitions, each placing in the top fifth of entrants or better.
Awards
Princess Sumaya University for Technology. Won first place for AirQualityAI, a project focused on predicting air quality.
Amman Arab University, with the IEEE Jordan Section. Presented ResearchNet against university-level competitors from across the Arab world.
Top ranking on the competition's Kaggle leaderboard (385th of 1,754 globally), confirmed by WiDS Worldwide and Kaggle. First high school student in Jordan to receive this award at the global level.
Experience
- Fixed critical security vulnerabilities in production software, including an access-control issue.
- Built automated PII detection with a human-in-the-loop review step.
- Designed a subscription and billing system end-to-end, integrating a third-party payment provider.
- Built user-facing interfaces in React.
- Authored the product's Privacy Policy and Terms of Service.
- Contributed to machine-learning research, model development, and evaluation.
- Supported platform and DevOps engineering, including testing, QA, and release preparation.
- Maintained technical documentation across the codebase.
- Worked on data- and policy-related engineering tasks.
- Collaborated on integrating machine-learning models into user-facing features.
CV
My full resume is online: resume.pdf