* Developed backend infrastructure using Python and Javascript for automating data collection for industrial BACnet networks, enhancing data assimilation and channeling to a client-facing application• Worked on prototyping the front-end on a data streaming SaaS platform using React, Redux, and Material UI, and integrating the user login, authentication, and session cookies using React, Redux, MongoDB, and NodeJS.• Built multiple programs to migrate, store, and filter data for a client: Wrote a C program to pull data from a Rockwell programmable logic controller (PLC) and send to HarperDb, a geo-distributed database, via a REST API; then, using Python, worked with another team member to build a custom plugin for Fledge, an open source platform for industrial Internet of Things (IOT) to receive the data polled from HarperDb and then filter the data within Fledge before sending it out to OSIsoft's Cloud Service.• Used regression in machine learning to predict a building’s power usage with 82% accuracy on the first attempt, increasing to 93% accuracy with further refinement.

Using random forest algorithms and XGBoost to predict power consumption at building sites