Chetan Solanke

I am an accomplished professional with 9 years of experience in machine learning and renewable energy forecasting. My expertise lies in developing and deploying advanced ML models specifically for wind power prediction, data engineering, and automated MLOps pipelines. I have a proven track record of improving forecast accuracy and implementing scalable solutions for complex energy systems.

Currently, as a Senior Machine Learning Engineer at Vestas Wind Systems, I architected an advanced renewable energy forecasting system that achieved a 25% reduction in Mean Absolute Error (MAE). I developed a hybrid ML approach utilizing XGBoost and LSTM for power forecasting, and engineered an automated MLOps pipeline that significantly reduced model deployment time. My commitment to mentoring junior engineers has also boosted team productivity by 150%.

In addition to my professional experience, I have undertaken personal projects such as developing a personalized book recommendation system and a chatbot for nutrition data. These projects showcase my ability to leverage machine learning and natural language processing to create innovative solutions.