Led the development of a production-grade SwiftUI iOS application that secured the 'Best App Award'. Architected a scalable backend by integrating REST APIs and Docker on Microsoft Azure, improving operational efficiency by 20%. Engineered performance optimizations that reduced data load time by 97.8% (less than 150ms) through efficient API integration and load testing with K6 and Grafana.

Spearheaded the development of a pipeline inspection robot featuring real-time crack detection and data transmission with sub-5ms latency via WebSockets. Directed the collaboration of four cross-functional technical teams to ensure seamless project execution and system integration. Optimized robotic movement and control logic while integrating an AWS-based backend for real-time fault logging and visualization.

Engineered a high-precision duplicate image detection solution using OpenAI's CLIP model for visual feature extraction. Reduced processing time by 50% by leveraging multithreading and parallel processing techniques on a dataset of over 10,000 images.Implemented DBSCAN clustering to enhance de-duplication accuracy by 30%, earning the 'Excellence Award' for impactful research.

Developed an MQTT client for TIVA microcontrollers using the HiveMQ broker, reducing data transmission latency by 10% across industrial IoT networks. Designed and deployed a real-time data visualization portal using React.js and Flask, which improved microcontroller performance monitoring by 20%. Strengthened full-stack IoT system design skills by enabling smoother communication between distributed embedded systems.