• Re-implemented and tested Smorphi educational robot (inspired by Tetris) curriculum, designed and developed by the SUTD research team.• Contributed to inventory management and quality control at Wefaa Robotics, a startup affiliated with SUTD, streamlining processes and ensuring efficient resource utilization.• Led the development of a cleaning robot based on Smorphi, devising algorithms to process LiDAR maps, create room masks, and generate a matrix representation of the room layout. Implemented algorithms for effective navigation and coverage optimization, enhancing the robot’s ability to navigate and clean efficiently.

• Re-implemented the machine learning and deep learning component of the research paper titled ”sTetro-Deep Learning Powered Staircase Cleaning and Maintenance Reconfigurable Robot”. The focus was on staircase detection using MobileNet SSD for RGB images and MobileNetv2 for depth images.• Employed Support Vector Machine (SVM) as a fusion method to combine the outputs of MobileNet SSD for RGB images and MobileNetv2 for depth images, effectively enhancing the accuracy of staircase detection and navigation for the robot.• Developed a novel approach for staircase detection utilizing a custom-designed deep Convolutional Neural Network (CNN) architecture. This approach aimed to leverage the unique features of staircase environments for improved detection accuracy and robustness.

• Collaborated with cross-functional teams to design and develop a CMS (Content Management System) website.• Implemented responsive web pages and multi-tier user login using Vite-React.js, Redux, and Tailwind CSS.• Gained agile development experience through sprint planning and stand-up meetings.