Engineering AI for
I build end-to-end AI systems that transform complex scientific data into scalable, production-ready solutions. Combining artificial intelligence, machine learning, software engineering, and computational biology, I develop intelligent technologies for healthcare, agriculture, and environmental science—turning scientific challenges into practical tools that drive discovery and real-world impact.
About Me .
I build intelligent systems where artificial intelligence, software engineering, and computational biology converge to solve meaningful scientific challenges.
My work focuses on designing end-to-end AI systems that transform complex scientific data into practical tools for research and real-world decision-making. By combining artificial intelligence, computational biology, and software engineering, I develop scalable solutions across healthcare, agriculture, and environmental science.
Rather than building isolated machine learning models, I enjoy engineering complete AI systems—from data acquisition and engineering to model development, backend infrastructure, deployment, and user-facing applications. I believe impactful AI requires both scientific understanding and strong software engineering.
My long-term goal is to contribute to research and industry by developing intelligent technologies that accelerate scientific discovery while making advanced AI more accessible to researchers, organizations, and communities.
Core Expertise
Research Interests
Technologies
Professional Experience
Artificial Intelligence Committee Member
IEEE SSCS Alexandria University Student Chapter
- Develop AI systems using Machine Learning, Deep Learning, and Generative AI for real-world engineering applications.
- Build production-oriented software through collaborative engineering projects and structured technical training.
- Apply modern software engineering practices across the complete AI development lifecycle, from experimentation to deployment.
- Collaborate with multidisciplinary teams to transform research concepts into scalable AI solutions.
Research Cohort Member
Misr El Kheir Foundation
- Selected through a competitive national research program focused on developing future interdisciplinary researchers.
- Built practical expertise in research methodology, academic writing, literature review, and evidence-based analysis.
- Designed research questions, evaluated scientific literature, and translated ideas into structured study designs.
- Prepared for future peer-reviewed publications through mentorship and collaborative research training.
Research & Community Engagement Facilitator
Save the Children International
- Conducted participatory community research to investigate digital safety challenges affecting young people.
- Contributed to developing an evidence-based policy paper by transforming research findings into actionable recommendations.
- Designed and independently delivered a critical-thinking workshop for 25 school teachers to strengthen digital resilience.
- Collaborated with multidisciplinary teams to convert research outcomes into practical community interventions.
Google Gemini Student Ambassador
BasharSoft
- Promoted practical adoption of Generative AI across Egyptian universities through structured outreach and technical guidance.
- Evaluated AI-generated content and designed Arabic prompting strategies for educational use cases.
- Supported more than 800 university students in effectively using Google Gemini Advanced.
- Recognized among the program’s top-performing ambassadors for outreach impact and community engagement.
Certifications
NVIDIA DLI : Generative AI (Beginner Level)
Information Technology Institute (ITI)
Statistics for Genomic Data Science
Johns Hopkins University (Coursera)
Introduction to Genomic Technologies
Johns Hopkins University (Coursera)
Python for Genomic Data Science
Johns Hopkins University (Coursera)
Data Science: R Basics
HarvardX & edX
Python Basics for Data Science
IBM & edX
Data Analytics Basics
IBM & edX
Google Gemini Student Ambassador
BasharSoft
Galactic Problem Solver
NASA Space Apps
Future M.Ds+ in STEM Scholar
MedSTEMPowered
GreenAura Ambassadors
GreenAura
Featured Projects .
A curated collection of my research applications, tools, and open-source contributions in computational biology, machine learning, and full-stack development.
Flood Intelligence AI
A geospatial intelligence platform detecting flood extent from Sentinel-1/2 satellite imagery using a U-Net deep learning model. Features a 3D tactical HUD for wide-area damage assessment and smart SAR fallback for cloud obscuration.
BioPhys Refinement Lab
A production-grade bioinformatics platform that transforms raw AI-predicted protein structures into docking-ready conformations using GPU-accelerated molecular dynamics.
NeuroScan AI: Explainable Tumor Classification
A full-stack medical AI system for real-time breast tumor classification. Built with TensorFlow, FastAPI, and React, integrating SHAP to provide feature-level clinical interpretability and resolve the AI black-box problem.
Research Preprints .
A selection of my ongoing research in computational biology and neuroscience. These preprints highlight my focus on applying machine learning and network science to understand complex biological systems.
Chemical Analysis of Water Pollution and Its Impact on Public Health
Explores chemical contaminants in water resources and their long-term risks on community health.
An Integrated Framework for Asteroid Impact Risk Assessment
Proposes a structured risk assessment framework combining data, scenario modeling, and decision-support.
Integrated Consciousness: AI Impact on Human Cognitive Autonomy
Examines how advanced AI systems interact with human cognition and autonomy, highlighting risks and safeguards.