Omar Ashraf Mohammed — home

AI / ML Engineer

Omar Ashraf Mohammed

AI/ML engineer working across research and production.

I build and evaluate machine-learning systems, then follow them into the software, data and infrastructure that determine whether they actually work.

BSc Computer Science · University of London / European Universities in Egypt
First Class Honours · Top 5% of cohort · Expected March 2027

Selected work

PERSONALML SYSTEMS2025

SysMon AI

A local-first monitoring pipeline that turns system telemetry into calibrated anomaly signals, threshold forecasts, and actionable terminal alerts.

A terminal system monitor that collects local telemetry, scores it for anomalies with a calibrated Isolation Forest, forecasts threshold crossings, and raises alerts — without sending a single host metric anywhere.

Python · Scikit-learn · SQLite · Rich

96.2% accuracy on the synthetic benchmark

Measured on generated data — 100,000 training and 20,000 test observations with 5% injected anomalies. Not measured on real workstation traces.

CODE-VERIFIED

3.8% false-positive rate

Same synthetic benchmark, against a calibration target of 5% or below. Precision was 84.1% and recall 78.5% on the same run.

CODE-VERIFIED

Read case study

INTERNSHIP CASE STUDY2025

AI Facies Classification

A collaborative seismic segmentation system that compares U-Net variants and packages inference behind a web and API deployment.

PyTorch · Flask · FastAPI · Docker

97.2% average accuracy — InceptionV3

The strongest of the three backbones. ResNet-50 reached 96.7% and ResNet-34 93.5% on the same task; the three-model mean is 95.8%, which is what the résumé's 95.7% figure refers to.

AUTHOR-CLARIFIED

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INTERNSHIP CASE STUDY2025

SpotAI

A multimodal misinformation platform that verifies claims from video through speech, text and retrieval — and marks generated media at source so provenance survives re-upload.

Python · Faster-Whisper · RoBERTa-MNLI · C2PA

90%+ claim verification accuracy

Measured by the team during the sprint, checking extracted claims against scraped Wikipedia articles after a polarity score narrowed which statements were worth verifying.

AUTHOR-CLARIFIED

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All projects

Selected research


Experience across

  • European Universities in Egypt
  • University of London
  • Orange Egypt
  • Qestit Group
  • Dell Technologies
  • Emirates NBD
  • Deepkapha AI Lab
  • SAP
  • Deloitte
  • GDG On Campus

Experience

Professional

  • European Universities in Egypt

    Undergraduate Research Assistant

    Supervised research on exercise-form assessment from video, comparing template matching, classical ML and deep learning.

    Show details for Undergraduate Research Assistant at European Universities in Egypt
    • Recorded and annotated a boxing-gesture corpus covering five actions at three execution-quality levels, tracking eight body landmarks per frame with MediaPipe.
    • Built a reproducible evaluation protocol — one fixed unseen test video, timestamp-aligned scoring, and the same test set applied to every approach.
    • Compared a $1 Recognizer, a nine-model classical sweep, and a CNN-LSTM, and reported the negative results as carefully as the positive ones.

    Python · MediaPipe · PyCaret · TensorFlow · scikit-learn

    Read the research dossier

  • Orange Egypt

    Backend Engineer Intern

    Built a promotional fulfilment engine designed to grant a gift exactly once under concurrent requests.

    Show details for Backend Engineer Intern at Orange Egypt
    • Designed four REST APIs — eligibility preview, transactional fulfilment, segment creation, and segment assignment — over PostgreSQL with JdbcTemplate.
    • Enforced exactly-once delivery using request-key idempotency, per-user advisory transaction locks, and a re-check after lock acquisition.
    • Made cap rules data-driven, so new gift segments and frequency caps ship as configuration rather than redeploys.

    Java 21 · Spring Boot · PostgreSQL

    Read the case study

  • Qestit Group

    QA Engineer Intern

    Full-cycle functional and non-functional testing on an enterprise Test Management System.

    Show details for QA Engineer Intern at Qestit Group
    • Wrote and executed UI, API and database test suites with Playwright, Postman and JMeter against a system serving a six-figure user base.
    • Surfaced more than twenty critical pre-release defects across the UI, API and database layers.
    • Identified performance bottlenecks that drove a 61% improvement in page load times, unblocking enterprise client release readiness.

    Playwright · Postman · JMeter · SQL

  • Dell Technologies

    Summer Intern — AI/ML

    Owned the verification pipeline and the watermarking layer of a multimodal misinformation platform, presented to Dell executive leadership.

    Show details for Summer Intern — AI/ML at Dell Technologies
    • Selected from a field of more than twelve thousand applicants.
    • Built the claim-verification pipeline: speech recognition, OCR, web retrieval, and RoBERTa-MNLI entailment over retrieved evidence.
    • Designed the prevention side as well — C2PA-signed provenance manifests, visible badge and QR overlays, and perceptual-hash fingerprinting for near-duplicate detection.
    • Presented the system and its business case to Dell executive leadership.

    Python · Faster-Whisper · Transformers · FastAPI · PostgreSQL

    Read the case study

  • Emirates NBD

    IT Summer Intern

    Infrastructure automation and security assessment across enterprise banking systems.

    Show details for IT Summer Intern at Emirates NBD
    • Automated health-check scripts in Python and Bash, cutting manual audit cycles by a reported 20%.
    • Supported the CISO and Security Architect on a Nessus vulnerability sweep of on-premise core-banking infrastructure.
    • Documented more than fifty critical findings and drafted the accompanying mitigation playbooks.

    Python · Bash · Linux · Nessus

  • Deepkapha AI Lab

    AI Engineer Intern

    Built and deployed a seismic facies segmentation service end to end, from training to container.

    Show details for AI Engineer Intern at Deepkapha AI Lab
    • Trained U-Net segmentation models with ResNet-34, ResNet-50 and InceptionV3 encoders on the Dutch F3 seismic dataset.
    • Owned the preprocessing and augmentation pipelines and the hyperparameter search.
    • Packaged inference behind a Flask interface mounted through FastAPI, containerised with Git LFS-managed weights.

    PyTorch · Flask · FastAPI · Docker

    Read the case study

Extracurricular

  • SAP

    Dual Study Programme Trainee

    Structured enterprise-software training programme.

    Extracurricular

  • Deloitte

    Innovation Hub Mentee

    Mentored programme at the Deloitte Innovation Hub.

    Extracurricular

  • GDG On Campus EUE

    Logistics & Organisation Lead

    Led logistics for campus workshops, hackathons and meetups across the academic year.

    Extracurricular

Academic foundation

BSc Computer Science

University of London · European Universities in Egypt

First Class Honours · Top 5% of cohort · Expected March 2027

AI/ML core

  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Natural Language Processing

Computer science foundations

  • Data Structures & Algorithms
  • Object-Oriented Programming
  • Computer Systems & Architecture
  • Networks

Skills

Machine learning
PyTorch, TensorFlow, Keras, Scikit-learn, Hugging Face, OpenCV
Backend
Python, Java, Spring, FastAPI, Flask, Node.js, Express
Data
PostgreSQL, SQLite, MySQL, Pandas, NumPy
Infrastructure & quality
Docker, GitHub Actions, AWS, Linux, Playwright, Postman, JMeter

Contact

Interested in careful ML work, production-minded engineering, or graduate research? Email me.

On Medium


Evidence