A highly skilled and motivated display software engineer with expertise in Android and Linux display stack. Experienced in display functional areas including HAL, SurfaceFlinger, Composition architecture, display drivers/post-processing, frame buffer, overlay, framework, different display interfaces, and technologies such as MIPI DSI, HDMI, and DisplayPort. Seeking challenging opportunities in display software development to contribute to the success of the organization. Individual contributor with 5+ years' experience in Requirement Analysis, Design/Development, Unit Testing, and Bug Fixing. Experience with Kernel Driver - Development, Automated Unit Testing, Power Management, and Android. Proficient in Linux, C, C++, Board Bring Up, Kernel, and BSP.
Developed and trained machine learning models using libraries like scikit-learn, TensorFlow. Developed and trained a logistic regression model using scikit-learn to predict customer churn, achieving an accuracy of 85% on a test dataset. worked closely with team members to develop a real-time object detection system using YOLO (You Only Look Once) algorithm Applied sentiment analysis on a Twitter dataset containing 50,000 tweets, categorizing sentiments into positive, negative, and neutral categories for market research. Worked on Spam Mail Detection by utilizing libraries such as numpy, pandas and scikit-learn