Pratyaksh Mundra

• Designed and developed real-time location-tracking Android app using Kotlin and Android Studio, seamlessly integrated with AWS for processing, demonstrating proficiency in full-stack app development, cloud computing, and problem-solving.
• Engineered AWS solution to deploy large-scale IoT networks, focusing on scalability, resilience, and security, demonstrating expertise in AWS services like EC2, S3, Lambda, IAM, CloudTrail, CloudWatch and DynamoDB.
• Deployed end-to-end pipeline for research and end-user applications involving collecting data to processing and storage in DynamoDB. Achieved latency of around 300 milliseconds.
• Reduced end-to-end transfer latency by factor of 10 through codebase optimization, improving system efficiency and performance.
• Developed comprehensive analytics by visualizing of pipeline using Python and Matplotlib, ensuring smooth operations and facilitating decision-making.

Comparative Analysis of Different Reinforcement Learning for Drone Control

• Implemented reinforcement learning algorithms, including Policy Gradient, PPO (Proximal Policy Optimization), Deep Q Learning, and Actor-Critic, for drone control systems.
• Conducted comprehensive comparative analysis, evaluating performances of these algorithms in comparison to traditional PID controllers.

Picture Book AI

• Developed AI system crafting children's stories and generating accompanying images. Enhanced user experience through coherent content generation.
• Integrated advanced language models for coherent and contextually relevant content generation and enhancing user experience.
• Aimed at benefiting communities and schools with limited access to children's books.

Water Safety Enhancement System

• Designed innovative drowning detection system using custom hydrophonic sensor to capture turbulent water and camera array with Convolutional Neural Networks (CNNs) for real-time analysis from both above and below water, significantly enhancing water safety by alerting authorities on time.