Sanjana Kottalavadi Shivashankarappa

MSc Robotics & Embedded AI student at Maynooth University with hands-on experience in computer vision, embedded systems, and AI-driven automation. Skilled in Python, C, OpenCV, YOLOv8, and microcontroller programming, with projects and internships covering real-time vision systems, reinforcement learning, and hardware integration. Adept at designing intelligent embedded solutions for healthcare, robotics, and automation, combining AI models with embedded hardware for end-to-end deployment.

Software Engineer Intern with knowledge in troubleshooting software, detecting bugs and errors and using wireframe models. Quick to respond to queries and resolve issues. Aspiring to enhance skills and be part of sustainable workforce.

• Hand Hygiene Monitoring Using Front-Facing Webcam (MSc Thesis) — Python, OpenCV, MediaPipe, YOLOv8, Designed a real-time computer vision system for monitoring hand hygiene compliance in healthcare settings.
• Concept Prototype of a Client Care Note System with Non-Verbal Cue Analysis (Team Project) — Python, OpenCV, Built a prototype system integrating gesture and facial expression analysis to support patient care documentation.
• Automating the Chrome Dino Game Using Reinforcement Learning (Individual Project) — Python, RL Algorithms, Developed an autonomous game-playing agent using Q-learning for adaptive decision-making.
• AR-Based Hand Hygiene Compliance and Guidance System (Individual Project) — Unity/AR frameworks, Computer Vision, Created an AR-based interactive guide for proper hand hygiene protocol adherence.
• Pothole Detection Using Ultrasonic Sensors (Mini Project) — Arduino, Ultrasonic Sensors, Designed a road hazard detection prototype for smart city applications.
• Automatic Parking System (Bachelor's Final Project) — IR Sensors, Servo Motors, LCD Display, Arduino, Developed an automated parking prototype using embedded hardware and control algorithms.

• Delivered multiple interdisciplinary projects combining AI software and embedded hardware.
• Participated in research initiatives involving YOLOv8-based object detection and reinforcement learning.

References available upon request