I delivered high quality software in team and individual projects. I was involved in the full cycle of software development: idea exploration; project design, planning and deployment scheduling; building software; maintenance and continuous improvement.

I utilized Ruby on Rails, React and PostgreSQL to build:

Smart thermostat development (similar to NEST). I proposed and developed an occupancy model based on humidity and temperature sensor signals. A provisional patent was filed based on my invention.

I used Python (including Pandas, Scikit-learn, Statsmodels, Matplotlib) to run experiments, develop and validate the occupancy model.

I brought automated water quality analysis to the customers by extending an open source IoT platform used by the company.

I used Python (including Pandas, Scikit-learn) to train ML models. I deployed inference services on AWS and on company owned servers with Flask.

I used JavaScript (including D3) to build customer facing dashboards for real time water quality analysis.

My work resulted in full automation of the water scanning and analysis process. Now the scans are available in real time with an interactive UI instead of having a technician to run the analysis and provide customers with the results and insights.

I developed assignments and automated graders for Self Driving Cars courses offered by the University of Toronto. More specifically, I contributed to the following topics: visual odometry, PID controllers, stereo vision, simulation.

I used Jupyter Notebook (Python, OpenCV, CARLA) for developing assignments and Python for building scalable graders with Docker containers.

These courses were taken by 60K+ happy students.