Abdullah Adil

Ambitious AI engineer building intelligent systems that solve real problems. Experienced in deploying production-grade machine learning solutions across computer vision, NLP, and full-stack development.

Full Stack AI Developer at Shannon Biologics (2025-08 – 2026-02)

• Implemented ProteinMPNN with ESM2 embeddings to run protein sequence simulations. The system accepts protein data in FASTA format and generates structural predictions.
• Built REST APIs to serve model inference requests and handle large-scale data processing. Optimized GPU performance for running protein structure predictions efficiently.
• Developed a React frontend for visualizing predicted protein structures and collaborating with the research team to validate results and improve prediction accuracy.

Full Stack AI Developer at VisionPass.ai (2024-12 – 2025-02)

• Developed a vehicle number plate detection system using YOLO with Flask backend. The system processes video streams at 30+ FPS with latency under 50 milliseconds.
• Created a character extraction pipeline that combines Tesseract OCR with custom preprocessing. Used ensemble voting across multiple OCR models to improve accuracy beyond any single model.
• Built the React frontend to display detected plates and extracted characters in real time with clean, intuitive UI.

BS in Artificial Intelligence – FAST National University of Computer and Emerging Sciences (2022 – Present)