Using data science and a background in water resource engineering to solve problems and continuously learn. Data management, cleaning, statistical analysis, modelling, and project management experience gained while working in water resource consulting and further pursued through a Master of Data Science.
I started my career collecting remote data in the Coast Mountains, managing hydrometric data collection programs, and providing data analysis/modelling. I then began using machine learning to support water resource studies and develop in-house analysis and visualization applications for the growing volume of data collected on projects. I’m now excited to be part of the TerraSense team working on computer vision with deep learning projects, learning, and making an impact in the mission intelligence space.
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: