Led a team to develop a dynamic and interactive TA Management website using HTML, PHP, and JavaScript for the McGill School of Computer Science competition, winning first place.

• View Project

In this Project we tested several machine learning models to detect deep fake videos

• View Project

For a class project, created a well-designed, well documented software for Event Brite, the event management and ticketing website.

• View Project

• Built a real world database application on managing the Covid Vaccination.
• Designed an Entity Relationship (ER) diagram forming relations between multiple entity which include: Nurses, Vaccine type, Vaccine, Slots, Hospital, patient based on priority, location etc.
• Built a SQL database schema and DDLs and wrote SQL code on DB2 to successfully store the entire database entries and perform suitable actions.
• Finally, built a mini frontend on Java, for the hospital to instantiate the vaccination process.

• View Project

• Created a basic shell memory which takes multiple commands including “exec” and built a shell memory that stores values which are used later by multiple other commands
• Created a fully working kernel and process execution which allowed up to three files to run simultaneously using the “exec” command assigning a specific quanta to each program.
• Built PCBs, single core CPU and Ram for the execution of these files, as well as OS Boot sequence, backing store and the memory manager for the operating system

• View Project

• In a project-based course leading two fellow developers, verified the authenticity of the 2020 US elections by utilizing the reddit API to collect posts from the subreddits: r/politics and r/conservative using Python's Request library and compiled the analysis in professional data science report.
• Demonstrated knowledge of dynamic programming using Java to develop a script that utilized min profit max weight Knapsack to calculate the minimum number of people Biden had to convince in order to win the US elections.

• Data Structure Project
• Data Science Project

Built a custom 13 layered CNN model to classify a noisy MNIST dataset comprised of letters and digits achieved an accuracy of 94.85% using Keras.

• View Project

• View Project

Developed a program that automated a playlist creation based on user's selected/favorite artists, using Python's Request library to access Spotify's API and a Spotify Library

• View Project