Charbel Younis, MD
An enthousiast with a background in bioinformatics and AI, passionate about the field of healthcare & AI
CY

About

I’m a recent graduate from the Lebanese American University (LAU), where I earned my MD and a B.S. in Bioinformatics. I care deeply about clinical medicine and the patient experience, and I’m equally passionate about exploring how digital health, genomics, and AI can make healthcare smarter and more effective. My goal is to grow as a compassionate physician while continuing to create and contribute to innovations that improve the way we care for patients.

Projects

RNA-seq and iPSC Models to Study Heart Disease in Turner Syndrome

RNA-seq and iPSC Models to Study Heart Disease in Turner Syndrome

Conducting a translational bioinformatics project at UTHealth Houston that integrates RNA-seq pipelines, pathway enrichment, and network analyses to study how X-chromosome dosage impacts endothelial cells in Turner Syndrome (TS)

R
Machine Learning
Pathway Analysis
RNA-seq Analysis
Data Visualization
Linux
High Computing Power (TACC)
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.