SAI TEJASWI ENUKONDA

Results-driven System Verification Engineer with a strong background in designing, implementing, and optimizing verification strategies for complex hardware and software systems. Seeking to leverage expertise in verification methodologies, test planning, and debugging in a challenging environment to ensure product quality and reliability. Committed to driving project success through rigorous testing, collaborative problem-solving, and continuous learning.

• Distributed Dual Coordinate Ascent in General Tree Networks and Communication Network Effect on Synchronous Machine Learning, Conducted research on the convergence rate of distributed dual coordinate ascent algorithms for large-scale machine learning in tree-structured networks, addressing challenges posed by limited data storage and communication. Developed a recursive analysis framework to evaluate the convergence rates of distributed algorithms, enhancing understanding of network effects on performance. Designed and executed numerical experiments to demonstrate the effectiveness of the proposed algorithm in scenarios with restricted communication between local workers and central nodes. Investigated adaptive strategies for managing local and global iterations based on network delays, significantly enhancing convergence performance in distributed machine learning tasks.
• Creating a Simon game on STM32 Nucleo board, Designed and implemented a Simon Game on the STM32 Nucleo board, verifying functionality through structured test cases to ensure accurate LED sequencing and user input handling. Developed verification protocols for the Simon Game on STM32, including button debouncing and timing accuracy tests, ensuring reliable gameplay across different input patterns. Utilized STM32's GPIO and timer modules to implement and conducted extensive debugging and validation of the Simon Game software, achieving 100% functionality and responsiveness benchmarks on STM32 Nucleo hardware.