AI & Bioinformatics Expert | Academic Lecturer | Aim's Founder

Dr.Moshira is a PhD-driven researcher specializing in biomarker discovery, multi-omics integration, and radiogenomics. My primary focus is on the intersection of AI and cancer research, where I design and deploy explainable Machine Learning pipelines that enable earlier diagnosis and personalized therapeutic strategies directly within clinical pathways.

Beyond research, I am dedicated to translating complex science into tangible impact. As an Academic Lecturer and Founder, I educate the next generation in AI and computer science while building practical tools. My work has been internationally recognized, including an award from DAAD for Entrepreneurship and Innovation (TU Berlin, 2023) and 2nd place at Falling Walls Lab Cairo (2024).

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10+

Publications

2nd Place

Falling Walls Lab Cairo ’24

DAAD

TU Berlin Innovation ’23

    Recent Highlights
    
        Published Work: Two journal papers under review on advanced multi-omics feature selection and AI diagnostics.
      
        Founded: OmicsFusionNet & Seq2Image — AI-oncology tools for clinical decision support.
      
        Instructed: IBM-certified instructor in Data Science, AI, Cloud, Big Data, and Mobile.

Core Expertise

Multi‑Omics (RNA‑seq, Proteomics, etc.)
Feature Selection (sDCFE, XGBoost)
Cancer Diagnosis & Staging
Explainable AI
Radiomics / Radiogenomics
Programming Languages (Python, R, SQL, etc.)

Teaching & Instruction

IBM Certified Instructor

Recognized by IBM for instructional excellence in:

Artificial Intelligence
Data Science
Big Data
Cloud Computing
Mobile App Development

Successfully delivered industry-aligned curriculums for both academic and corporate learners, blending theory with hands-on projects.

Curriculum Developer & Course Leader

Designed and led advanced CS & AI courses including:

Machine Learning for Biologists
Deep Learning
Python

Courses emphasize critical thinking, real-world applications, and cross-disciplinary integration.

Certificates

IBM Big Data Specialist (2015)
IBM Mobile Application Development — MobileFirst (2015, 2017)

AI Projects

OmicsFusionNet

OmicsFusionNet is a multi-omics integration platform designed for early cancer detection, staging, and treatment response. It combines statistical feature selection with Machine Learning and Deep Learning models. The platform also supports MSI/MSS-aware precision oncology.

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Lung Cancer Project

A research-driven project using AI and multi-omics to improve lung cancer detection and treatment prediction, combining imaging and genetic data for earlier, more accurate, and personalized care.

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Seq2Image

Seq2Image is a radiogenomic pipeline that correlates pathology images with genomic signatures. Its purpose is to predict therapy choices (specifically, immunotherapy versus chemotherapy) while providing interpretability.

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Selected Publications

A Novel Statistical Feature Selection Framework for Biomarker Discovery and Cancer Classification via Multiomics Integration.
BMC Medical Research Methodology — Under review

AI‑Based Multiomics Integration for Cancer Diagnosis and Prognosis.
Journal of Genetic Engineering and Biotechnology — Under review

Ovarian Cancer Proteome Analysis and Biomarker Discovery Using ML.
AISI 2024

Lung Cancer Stages Classification via Differential Gene Expression & DL.
AISI 2024, Springer.

Full publication

Let’s Collaborate

Whether you're interested in research collaborations, guest speaking, mentorship, or supervision opportunities — feel free to reach out.

Reach me at: moshira.ghalib79@gmail.com

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