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Abdelrahman Karim
AI Engineer · Full-Stack Architect · Researcher

I build production software and applied AI systems that companies actually run.

Architecting and shipping production product software, internal tools, marketplaces, and AI workflows for companies across the US, UK, EU, KSA, UAE, Kuwait, and Egypt. Peer-reviewed work in Scientific Reports (Springer Nature) and IEEE.

Work with meSelected workDownload CV↗
Production Platforms35+
Peer-Reviewed PapersSpringer + IEEE
Undergraduate GPA3.647 · 4th
Global Reach8 Countries

Next.js · TypeScript · FastAPI · Supabase · LangChain · Hugging Face · OpenCV · PyTorch · Distributed Systems

Selected Work

Systems with hard constraints.

Explore all case studies →
01 / 07
Capabilities

What I do.

01 · Architecture

Product & Full-Stack Software

Next.js, TypeScript, FastAPI, PostgreSQL, Supabase

End-to-end web applications, reactive dashboards, real-time catalogs, and robust APIs designed for continuous uptime and smooth operator workflows.

FULL-STACKACTIVE
02 · Machine Learning

Applied AI & Intelligent Agents

LangChain, Hugging Face, Computer Vision, NLP, Digital Twins

Production AI systems that move beyond toy prompts: localized RAG knowledge bases, symbolic guardrails, autonomous IoT robots, and predictive models.

APPLIED AIGUARDED
03 · Defensive Systems

Systems That Survive Production

Auth, Payments, RBAC, Ingestion Contracts, Security

Architecting invariants upfront: least-privilege permissions, payment reconciliation, state-machine transitions, and hardened defense-in-depth.

RELIABILITYHARDENED
Peer-Reviewed Publications

Scientific research.

From deep learning theory to physical autonomous systems. Published in Springer Nature and IEEE conferences.

View all papers & code →
Springer Nature2025 – 2026

IoT-Integrated Robotic System for Automated Plant Disease Detection and Environmental Monitoring

Scientific Reports (Springer Nature) · Co-author & Embedded AI Architect

Precision agriculture demands real-time, in-situ pathological screening without human fatigue. We developed a solar-powered, autonomous mobile robot capable of navigating agricultural rows, capturing high-resolution plant imagery, running localized deep-learning disease classification models on the edge, and streaming continuous environmental telemetry (soil moisture, temperature, ambient humidity) to a synchronized cloud dashboard with automated alert triggers.

Peer-ReviewedRead paper details→
IEEE2024

Arabic Abstractive Text Summarization Using Multilingual T5

2024 6th International Conference on Computing and Informatics (ICCI) · Lead Author & AI Researcher

Abstractive summarization in Arabic is historically hindered by morphological complexity, rich root-pattern systems, and dialetical variations. In this study, we fine-tuned Multilingual Text-to-Text Transfer Transformer (mT5) architectures on diverse Arabic textual corpora, implementing customized sub-word tokenization and length penalty schedules. Systematic evaluation demonstrated substantial improvements in ROUGE-1, ROUGE-2, and ROUGE-L metrics over traditional sequence-to-sequence recurrent and transformer baselines.

Peer-ReviewedRead paper details→
IEEE2024

A Comparative Study: Word Frequency, K-Means, and PageRank for Arabic Extractive Text Summarization

2024 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC) · Co-author & Data Scientist

Extractive summarization approaches provide interpretable, low-latency document condensation for resource-constrained systems. This paper conducts a rigorous comparative analysis between three foundational paradigms: statistical word frequency weighting, centroid-based K-Means sentence clustering, and graph-centrality PageRank (LexRank/TextRank adaptations) on Arabic news corpora. We report trade-offs in computational latency, sentence diversity, redundancy elimination, and semantic coverage.

Peer-ReviewedRead paper details→
Recognitions

Honors & competitions.

1st PlaceFeb 2025

1st Place Winner · Benha National Hackathon for Smart Cities & AI

Benha University & Ministry of Higher Education

Engineered an automated intelligent urban monitoring platform utilizing edge vision and distributed sensor networks, securing 1st place among top national engineering universities.

Best TeamMar 2025

Best Team Award · Finology Fintech Competition

New Mansoura University & Banking Sector Partners

Designed and deployed an intelligent financial risk assessment system featuring explainable AI (SHAP) and algorithmic fraud detection for digital banking portfolios.

National Finalist (Top 4)Mar 2024

Top 4 Nationally · Huawei ICT Competition — Innovation Track

Huawei Egypt & Ministry of Communications (MCIT)

Architected an end-to-end cloud and AI pipeline combining deep learning with low-latency IoT hardware, ranked among the top 4 teams across Egypt.

5th PlaceFeb 2024

5th Place Nationwide (Two Consecutive Rounds) · Benha Hackathon for Artificial Intelligence & IoT

Benha University

Selected as 5th nationwide across two judging rounds for an integrated autonomous computer vision and sensor telemetry system.

15th / 355Jul 2023

15th Place out of 355 Teams · International Military Technical College (ICMTC) AI Competition

Military Technical College (MTC)

Competed against 355 collegiate engineering teams in machine learning algorithms, deep neural network optimization, and computer vision challenges.

Finalist2023 – 2024

ECPC Participant & DEBI Robotics Finalist · Egyptian Collegiate Programming Contest (ECPC) & DEBI Robotics

AASTMT & Digital Egypt Builders Initiative

Competed in rigorous algorithmic problem solving and built autonomous robotic systems for competitive field tasks under constrained hardware specifications.

Available for Selective Engagements & Research

If the problem is real, write to me. Response within two business days.

Tell me the constraint. A paragraph beats a deck. If you only have a deck, send it anyway.

Start a projectEmail directly

Email: abdalrhmanayoub414@gmail.com · Phone / WhatsApp: +201024484974