Julia Penfield, Ph. D.
Principal Machine Learning Developer
VelocityEHS
Dr. Julia Penfield, Principal Machine Learning Scientist, is part of the Research & Development department at VelocityEHS where she has worked on a range of machine learning and data science projects. She has expertise in risk assessments, failure prediction, anomaly detection, long-term and short-term forecasting with proper uncertainty estimations, root cause diagnostics, and optimization.
In her previous role, Julia led the machine learning and data sciences team of BC Hydro, one of Canada’s largest energy suppliers in British Columbia, Canada. There, she founded several programs, including the electrical demand forecasting using advanced recurrent neural networks architecture, the generation of plant asset failure prediction using unsupervised machine learning, and wind farm generation forecasting using fully connected neural networks architecture.
In addition, Julia has utilized Natural Language Processing (NLP) and Computer Vision (CV) in several machine learning projects.
Julia received her Ph.D. in the application of machine learning in electrical engineering from the University of British Columbia (UBC) in Canada.
In her previous role, Julia led the machine learning and data sciences team of BC Hydro, one of Canada’s largest energy suppliers in British Columbia, Canada. There, she founded several programs, including the electrical demand forecasting using advanced recurrent neural networks architecture, the generation of plant asset failure prediction using unsupervised machine learning, and wind farm generation forecasting using fully connected neural networks architecture.
In addition, Julia has utilized Natural Language Processing (NLP) and Computer Vision (CV) in several machine learning projects.
Julia received her Ph.D. in the application of machine learning in electrical engineering from the University of British Columbia (UBC) in Canada.