1. Launched configurable AWS EMR setups and Graviton EC2 instances, reducing cost from $1M to $400K; Transformed model processing to parallel State Machines, improving matcher step runtime by 53.46%.

2. Enhanced product matching by deploying an image + text machine learning model, achieving a 56% increase in feature effectiveness and 89% precision in matching, through S3 artifact, workflow testing, and validation.

3. Streamlined configurations via Amazon Config Store, boosting scalability and cutting oncall tickets by 15 yearly.

1. Optimized on-the-fly model checking and software verification for concurrent C programs with Nested DFS and SCC-based search algorithms.

2. Researched advanced search optimization algorithms combined with partial order reduction techniques that eliminate the state-space in multithreaded programs and cut search duration by 50%.

3. Built and reproduced counter-examples with original program statements and the corresponding property states, successfully identifying and eliminating 80% of bugs, thereby improving code reliability and performance.

1. Developed automated software verification systems for mobile and web applications, which enabled a 20% time saving in identifying technical issues.

2. Conducted QA methodologies, including black box, functional, and stress testing to ensure software performance.

3. Utilized Wireshark for packet analysis, employing Regular Expression filters to detect malware from streams.