I design, implement, support and maintain internal web apps (mostly in python) for small and medium companies.Generally, these companies have existing manual processes using in house Mac or Windows servers and workstations. Migrating to the cloud, adds flexibility and allows companies to partially or fully automate processes. This often includes putting in place backup and recovery procedures, and implementing strict security protocols. I also occasionally use machine learning to optimize clients' tasks, mostly simple classification problems.

Achieved state of the art stereo vision accuracy by implementing and training MLmodels.Implemented a custom algorithm for merging very large outputs.Implemented a benchmark for inhouse stereo vision algorithms and state of the art models with industry-standard datasets.

Performed a series of 25 observational experiments to evaluate low cost PM2.5 sensor precision and accuracy. Compared data from a network citizen run air monitoring stations against data from thegovernment run air monitoring stations. Evaluated multi-sensor data from five types of air quality sensors.Created a dataset and framework to store and analyze air quality data points from multiple sources. Evaluated the air quality around the geography of the city with the help of ML. Examined the PM2.5 pollution measurements of Kamloops during extreme pollution events caused by wildfires.