Solving problems in the mining, renewable energy, and water resource management sectors using data science coupled with a background in water resource engineering. Applying machine learning to support analyses typically approached using traditional methods and building interactive applications to better communicate results and uncertainties.
Over 11 years of consulting experience including management of hydrology data collection programs, data analysis, probabilistic water balance and energy modelling, development of in-house data analysis and visualization applications, and open channel numerical modelling. Experience in conceptual design and project viability assessments to environmental permitting and operational modelling.
Master of Data Science, 2021
University of British Columbia (Okanagan)
Bachelor of Applied Science, 2008
University of British Columbia (Vancouver)
Approach for open-source near real-time anomaly detection with InfluxDB time series database using a LSTM neural network
HDFS log anomaly detector with a CNN on feature matrices generated using TF-IDF on log events
R Package API Wrapper for the Government of Canada Vehicle Recalls Database published on CRAN
Shiny R application hosted on AWS to explore Water Survey of Canada hydrometric data and conduct data summarization and flood frequency analysis
Shiny R application hosted on both AWS and shinyapps.io to bulk download Environment Canada climate data and view summaries of available/missing data
Data Collection and Analysis:
Development of In-House Applications:
Probabilistic Balance Modelling: