Junior Machine Learning Engineer specializing in NLP, Computer Vision, Explainable AI, and MLOps. I design transparent, production-grade AI systems that ship.
I'm a Junior Machine Learning Engineer and Applied Artificial Intelligence graduate with hands-on experience in Machine Learning, Deep Learning, NLP, Explainable AI, Computer Vision, Data Engineering, and MLOps.
My Bachelor's thesis focused on Explainable Mental Health Detection using emotion analysis, topic modeling, and machine learning models — combining rigorous evaluation with interpretability.
I'm passionate about building practical, transparent, and impactful AI systems that solve real-world problems.
From research notebooks to monitored deployments — across the full ML lifecycle.
Shipped systems, research thesis work, and production-grade MLOps pipelines.
Comparative study on early detection of mental health disorders using Reddit posts. Models: SVM, Bi-LSTM, BERT.
Real-time age, gender, and facial expression recognition optimized for on-device mobile deployment.
Production-ready fraud detection system with monitoring and retraining capabilities.
Political topic extraction and comparison from 2024 U.S. election tweets.
Data engineering pipeline for environmental sensor data processing.
AI-powered health recommendation platform built with machine learning.
Generated climate stories using real-time environmental data.
I'm open to Junior ML Engineer roles, research collaborations, and impactful AI projects. The fastest way to reach me is email.