Prince Kwabena Appiah Boadu
I’m a systems engineer and ai/robotics researcher. I build autonomous systems and study the places where machine learning, software engineering, and design meet.
This site is my working archive: research notes, open-source systems, long-form essays, and manuscripts shaped by the questions I’m currently following.
At the moment, I’m teaching a practical course on robotics and continuing work across robot learning, perception, and infrastructure for intelligent systems.
Recent writing
Oct 29, 2026Ask hard, then back offComputer SystemsJul 31, 2026Book Review: How Minds Change - David McRaneyPsychologyJul 6, 2026Rigid Body MotionsRoboticsMay 17, 2026Building an Oware Engine and a Ladder of RL AgentsMachine LearningMay 7, 2026A Hybrid Computer Vision Pipeline for Real-Time Traffic Density EstimationMachine LearningApr 6, 2026Configuration Space of RobotsRobotics
Recent manuscripts
2026Seamless Deployment of Machine Learning Inference at the Far Edge: An Empirical AWS IoT Greengrass Architecture for Industrial Predictive MaintenanceEdge Computing · IIoT2026Real-Time Traffic Density Estimation: A Hybrid Computer Vision and Predictive Machine Learning PipelineComputer Vision2026Adaptive Network Traffic Shaping with Deep Reinforcement Learning: A PPO-Driven Token Bucket on ns-3Reinforcement Learning · Networking2026The Evolution of xDSL Technologies: Broadband Demands, Technical Principles, and Copper LimitationsNetworking2024A Comprehensive Survey of Side-Channel Attacks in IoT Devices: Techniques and CountermeasuresIoT Security
Selected work
2026Real-Time Traffic Density EstimationA two-stage pipeline for traffic monitoring. The first stage pairs an object detector with a spatial logic layer that filters detections against a precomputed road mask, so only on-road vehicles contribute to density measurements.2025Humanoid Balancing Policy with MjLabA stabilizing control policy for the 29-DOF Unitree G1 humanoid trained with PPO and a small Actor-Critic network (512 → 256 → 128). Built on the mjlab framework with MuJoCo Warp to simulate 4,096 parallel environments directly on the GPU, bypassing CPU bottlenecks.