Shreyas Kori

I am a machine learning expert who applies deep learning, probabilistic modeling, and Python-driven automation to solve industrial engineering challenges. My work focuses on time-series forecasting, predictive maintenance, and risk-based inspection for real-world assets.

At BP (Aberdeen) I developed probabilistic degradation and corrosion models, integrated condition-monitoring data into predictive pipelines, and helped reduce unplanned downtime by 30%. I have built deep learning architectures (BiLSTM, CNN-LSTM) for RUL forecasting of turbofan engines and applied reinforcement learning to optimize maintenance scheduling.

In industry roles I created Python automation for design validation, built preprocessing and visualization pipelines with SQL and Tableau, and integrated sensor/IoT streams into condition-monitoring frameworks. I consistently delivered improvements in efficiency, documentation accuracy, and project delivery timelines.

I combine a mechanical systems background with advanced AI/ML skills and practical tools (TensorFlow, PyTorch, SQL, Tableau) to bridge assets with intelligent automation, driving better decision-making, reliability, and operational efficiency.