AI & Data Science engineer focused on predictive analytics, time-series forecasting, and scalable machine learning systems. I build end-to-end AI solutions with real-world impact.
Aspiring AI & Machine Learning Engineer with hands-on experience in building real-world AI systems. I specialize in predictive modeling, anomaly detection, and full-stack AI integration. My work focuses on environmental intelligence and industrial-scale data systems.
Environmental intelligence, industrial CO2 monitoring, air quality prediction, and building AI systems that make a tangible impact on sustainability.
AI identity
I treat machine learning as a complete engineering system rather than just model training. My approach begins with identifying the real business problem and building clean, scalable data pipelines that ensure reliable data flow and preprocessing. I focus on developing and validating models with attention to performance, stability, and real-world reliability, not just accuracy metrics. Beyond model development, I design production-ready APIs and backend systems that integrate AI seamlessly into applications. I also create dashboards and analytics interfaces that transform complex predictions into actionable insights, making decision-making faster and more effective. Overall, I combine data engineering, machine learning, deployment, and user experience to build intelligent systems that are practical, scalable, and impactful.
Open to AI/ML internships, research opportunities, and real-world problem solving. Let's build something impactful.