Delivering AI across IoT, healthcare, and agriculture — from award-winning research to real-world pilots and €1–2M pipeline growth.
I'm a passionate Data Scientist pursuing a Master of Science in Data Analytics at Rochester Institute of Technology (starting in 3 months), building upon my BSc in Computing and Information Technologies from RIT with a 3.55 GPA and six Dean's List recognitions.
My expertise spans from building genetic algorithms that revolutionize scheduling systems to developing computer vision models for medical applications. I've published award-winning research and delivered workshops to 80+ participants, consistently bridging the gap between complex data science concepts and practical business solutions.
Expected Graduation: May 2027
Graduated: 2025
Processed 980K+ protein/peptide records to build predictive models for early-stage Parkinson's progression, achieving 65-70% classification accuracy through advanced feature engineering and signal processing.
Developed AI models and datasets for crop analysis using drone imagery in partnership with Dubai Future Labs. Assisted in creating the complete data pipeline, machine learning models, and web interface for resource-efficient farming. Project was published in the 21st International Conference on Distributed Computing and Artificial Intelligence (DCAI 2024) with Springer Nature, achieving 86.5% accuracy using YOLOv8 and multispectral sensors. View Publication
Built a 3D Avatar-based sign language translator for English–German translation using computer vision and NLP. Implemented sign-to-text model with Euler angle calculations.
Developed a genetic algorithm-based scheduling system that reduced class scheduling time from days to 2-3 hours while maintaining 90% accuracy. Optimized resource allocation and conflict resolution for large-scale academic institutions.
I'm always interested in discussing data science opportunities, collaborating on innovative projects, or sharing insights about AI and machine learning.