Trilok Muniyapla

Highly skilled software developer with extensive experience in advanced SQL, automation testing, and software development. Proficient in Kubernetes, Docker, and cloud services including AWS and Azure DevOps. Demonstrated expertise in Test Driven Development, orchestration, and application scaling. Strong background in machine learning techniques such as linear regression, logistic regression, random forest, k-means clustering, and deep learning for vision using PyTorch and TensorFlow. Adept at project management and agile methodologies with a focus on delivering high-quality solutions. Career goal: to leverage technical skills in a challenging role that drives innovation and efficiency within the tech industry.

Dissertation project – MSc in Artificial intelligence, University of Stirling, Scotland, 01/2021, 11/2022, Improving Tennis Serve accuracy through computer vision, Built a statistical analysis to improve the tennis serves made novice players in comparison with professional players., Applied machine learning models (XGBoost, Multinominal Logistic Regression, Multilayer Perceptron) to identify the 3 different stages of a tennis serves., Input data for the analysis was captured from three cameras positioned to cover different angles., Captured videos were then edited to extract single serves from different players and for each of these clips, body landmark coordinates were extracted using Google's MediaPipe., The project was quoted as one of the best analytical projects for 2022 dissertation and was also recommended by professors to extend the analysis for further research.