•Optimized Shell Sort algorithms for large-scale datasets, reducing average-case time complexity by 23% and improving sorting efficiency for datasets exceeding 1.5 million records.
•Designed and deployed advanced machine learning models, including Convolutional Neural Networks (CNNs), achieving 96% accuracy in early detection of hematological and oncological abnormalities in medical imaging.
•Researched and enhanced Multi-Path TCP (MPTCP) protocols, increasing data transfer efficiency by 42% across heterogeneous networks through simulations on CloudLab and FABRIC testbeds.
•Collaborated on large-scale network experiments, resolving kernel compatibility issues and improving real-world MPTCP performance by 27%, enabling seamless data transmission in diverse network environments.