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Developed a transfer learning foundation model for time series forecasting in vaccine manufacturing, leveraging data from similar processes to address data scarcity. Benchmarked LSTM deep learning models against Gaussian Process Regression (GPR), selecting GPR for its superior forecasting performance on new processes. Engineered and deployed a production-ready API for the GPR model and published it on Azure Machine Learning.
Led two projects to predict stock market values and client insurance claims. Engineered a complete MLOps pipeline, migrating data from on-premises databases to Azure SQL and building an API endpoint for insurance application.
Improved energy price prediction accuracy by 20% through implementing a denoising strategy for data fed into an LSTM model.
Built and deployed a computer vision model for plant anomaly detection with 90% accuracy, and automated the model retraining pipeline on GCP using MLOps techniques.
Data Science, Statistics Orientation, with a thesis on Gaussian Process Regression.
B.S. in Agricultural Engineering with coursework in informatics and programming.