CSCI 576: Multimedia Systems Design

• Collaboratively implemented a global search feature that enabled users to search content across the app using partial keywords, increasing search efficiency.• Integrated filters allowing users to filter meetings by date, teams, organizations, and combinations of these, providing greater flexibility in consuming meeting data.• Developed a call dashboard that displays all recorded calls, complete with filtering options, improving user access to call data.• Implemented Single Sign-On (SSO) using SAML and OIDC, streamlining the authentication process and enhancing security across the application.• Introduced a "Continue Watching" feature, allowing users to continue watching meetings where they left off by integrating Room database and pagination.• Deployed a price gating functionality, enabling users to access content based on their subscription plan, effectively monetizing the application.

• Assisted in developing an attendance and entry system application for gyms, integrating advanced features for seamless user experience.• Integrated ML Kit for face detection, streamlining the attendance process and enhancing accuracy.• Configured Firebase database for secure storage of user information and gym branch data, ensuring real-time data synchronization.• Engineered an entry mechanism utilizing ESP32 microcontroller and relays, writing logic to automate gym access control.• Designed and implemented a comprehensive Bluetooth service to facilitate communication between the mobile application and entry device.

• Performed performance testing for several company portals, by creating scripts in LoadRunner to examine various user flows on websites.• Implemented various load, stress, endurance, and spike tests with JMeter and performed API testing using POSTMAN.• Supervised Datadog and Grafana for real-time monitoring, addressing performance variations and breakpoints, reducing the downtime of portals and easy resolution of bugs on development side.

• Worked on computer vision components of an autonomous vehicle, dataset generation, and conducted feasibility studies for deployment on various terrains. • Devised modules for object detection, lane detection, image segmentation, and odometry applying concepts from machine learning, deep learning, and computer vision.• Integrated all modules in collaboration with team leads and deployed system on real-time dash camera footage.• Optimised codes for GPU implementation, improving performance on real-time data by up to 60% and mentored and on-boarded 2 new interns on the project.