Hi, I'm Charbel 👋
I'm a medical student with a deep passion for technology, data, and the ways they can transform healthcare. With a background in bioinformatics and hands-on clinical experience, I love finding creative ways to merge medicine and computation to improve patient care and make a real difference in people’s lives.
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About

I’m in my final year of med school, and I’ve always been drawn to the way technology can shape the future of healthcare. My background in bioinformatics gave me a strong foundation in data science, and over time, I’ve used that knowledge to tackle real-world medical problems. I’ve worked on everything from analyzing genomic data to applying machine learning for disease detection. I’ve also built systems that help streamline medical processes, especially in humanitarian settings. I’m always learning, always adapting, and always looking for ways to bridge the gap between medicine and technology. The future of healthcare is changing fast, and I want to be part of that transformation.

Projects

Acute Leukemia Prediction with Machine Learning

Acute Leukemia Prediction with Machine Learning

Led a bioinformatics capstone project that applied machine learning techniques to classify and predict Acute Lymphoblastic Leukemia (ALL) and Acute Myeloid Leukemia (AML) using RNA-seq data.

R
Python
Machine Learning
Data Normalization
Principal Component Analysis (PCA)
RNA-seq Analysis
Data Visualization (GraphPad Prism)
Bioinformatics Tools
MyTutor.io

MyTutor.io

Co-founded and designed a Generative AI SaaS for efficient studying and exam preparation, implementing AI ChatBot, AI-Generated Study Guides, and Quizzes using OpenAI, Next.js, React, and Node.js.

Next.js
React
Node.js
OpenAI
Shopping Mall Management Database

Shopping Mall Management Database

Developed a comprehensive database system to manage a multi-level shopping mall, optimizing client management, space rentals, employee records, and event planning.

SQL
Oracle
Data Modeling
PostgreSQL
Query Optimization

Certificates

  • A

    AI in Healthcare specialization

    Stanford Healthcare

    Completed the AI in Healthcare course by Stanford University, enhancing a background in medicine and computational sciences with knowledge in AI applications such as medical imaging, predictive analytics, and personalized medicine, along with an understanding of ethical and regulatory considerations in healthcare AI.
  • B

    Biomedical Researcher

    CITI Program

    Credential ID 49983024
  • B

    Basic Life Support

    Beirut Lebanon

    Credential ID 235609355437
  • A

    Advanced Cardiac Life Support

    Beirut Lebanon

    Credential ID 255626476526
  • E

    Excel Fundamentals

    Datacamp

    Completed the Excel Fundamentals track on DataCamp, developing skills in data preparation, visualization, and analysis using Excel. Learned advanced techniques such as pivot tables, conditional formatting, and efficient use of Excel formulas and shortcuts to streamline workflows.
  • A

    Analyzing Genomic Data in R

    Datacamp

    Credential ID 526834 /nCompleted the Analyzing Genomic Data in R course on DataCamp, strengthening expertise in bioinformatics by learning key techniques such as differential gene expression analysis, RNA-seq, ChIP-seq, and advanced data visualization using Bioconductor in R.
  • S

    SQL Associate Certification

    Datacamp

    Earned the SQL Associate Certification from DataCamp, enhancing expertise in database management systems (DBMS) with skills in PostgreSQL, NoSQL, data modeling, and efficient database querying and design.
  • P

    Python data Associate Certification

    Datacamp

    Earned the Python Data Associate Certification from DataCamp! This certification reflects my skills in data analysis, Python programming, and data manipulation. Along the way, I honed my abilities in Pandas, NumPy, and data visualization, making data-driven decisions more efficient and insightful.
  • A

    AI fundamentals

    Datacamp

    Completed the AI Fundamentals track on DataCamp, building expertise in foundational AI concepts such as large language models (LLMs), neural networks, generative AI tools, and natural language processing (NLP). Gained practical skills in prompt engineering, data preparation, and understanding AI ethics to apply AI-driven solutions effectively.