Developed a comprehensive ISO 15118 certificate fetcher system for electric vehicle charging infrastructure during my internship at Shell. This project handles the complex certificate provisioning workflow required for secure EV charging communications, implementing the full certificate installation and management process according to ISO 15118 standards.

I used Logistic Regression on KDD Cup 99 data set to develop a model that can accurately detect and classify network attacks into DoS, Probe, R2L or U2R categories. This cybersecurity project demonstrates machine learning applications in network security.

Using NVIDIA's research paper on self driving car trained an end-to-end deep learning model that would let a car drive by itself around the track in Udacity driving simulator. It is a supervised regression problem between the car steering angles and the road images in real-time from the cameras of a car.

Leveraged prompt engineering extensively in developing sophisticated software using Ruby on Rails and ChatGPT for efficient data extraction from diverse documents. Automated PDF extraction, processing 200,000 reports. Enhanced accuracy via user-driven prompt and data point refinement. Streamlined data extraction, conversion, and analysis.

Developed distinctive time tracking software with advanced features, such as QR code employee clock-in and optimized staff scheduling algorithms. Resulted in heightened productivity and reduced costs, receiving positive client feedback as an alternative to established solutions like TSheets.