Zein Shehabeddine

Beirut, Lebanon ยท zein@zeinshehab.com

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I am interested in computational methods for exploring complex systems in biology and physics, particularly bioinformatics and astrophysics. I also have an interest in systems-level computing, including cybersecurity, operating systems, and low-level programming.

Skills

Applied Machine Learning
  • Clinical Machine Learning
  • Computational Genomics
  • Deep Learning
  • Computer Vision
  • Computational Linguistics
  • Natural Language Processing
  • Feature Engineering
  • Statistical Analysis
  • Data Analysis
Programming & Tools
Cloud & Infrastructure

Experience

Graduate Research Assistant

American University of Beirut

Worked on multiple research projects. Instructed multiple computer science labs.

January 2025 - Present

Competitive Programmer

American University of Beirut

Solved over 150 project Euler problems and participated in programming tournaments. Won the Late Henri Qais Naccache Competitive Programming Award

October 2021 - January 2023

ABLE Hackathon Finalist

American University of Beirut

Led team to develop real-time sign language translation model using TensorFlow and OpenCV.

January 2020 - August 2020

Education

American University of Beirut

Master of Science - MS
Computer Science

Activities and societies: Graduate Assistant, Research Assistant, Research groups

2024 - Present

American University of Beirut

Bachelor of Science - BS
Computer Science

Activities and societies: Competitive Programming, Hackathons, Education Above All. Dean’s Honor List

2021 - 2024

Labeeb

Labeeb is the first Lebanese Sign Language Translator app designed to address communication challenges faced by the deaf and hard-of-hearing community. The app offers fast real-time offline translation services for both the Arabic alphabet and common Lebanese words, facilitating seamless communication between sign language users and those seeking to engage with this community.

Read more..

Article - Screening autism spectrum disorder in children using machine learning on speech transcripts

A study presenting a machine learning approach for screening autism spectrum disorder in children using only speech transcripts, offering a privacy-conscious alternative to audio or video analysis.

October 2025