Hua-Ta (Eric) Liang is a robotics engineer specializing in autonomous systems, computer vision, and machine learning. Completing his Master's in Autonomy and Robotics at the University of Illinois Urbana-Champaign, he has developed full-stack solutions for autonomous vehicles, UAVs, unmanned surface vessels, and IoT systems.

His expertise spans the complete autonomy pipeline: perception (YOLO, Visual SLAM, sensor fusion), path planning (A*, trajectory optimization), and control (PID, Pure Pursuit, reinforcement learning). Recent projects include vision-based autonomous driving for full-scale vehicles, a sonar-mapping system for unmanned surface vessels and a DDQN agent for urban navigation in CARLA.

As a research assistant at National Taiwan University, Hua-Ta built an end-to-end IoT solution for dairy cattle health monitoring, integrating IMU sensors, XGBoost models, and PostgreSQL databases. This work resulted in publications in Smart Agricultural Technology and the 2023 ASABE International Conference. His undergraduate thesis on building a GPS-denied UAV navigation earned a fellowship from Taiwan's Ministry of Science and Technology.

Hua-Ta's work demonstrates strong systems integration skills, having successfully deployed autonomous solutions across diverse platforms from embedded systems to full-scale vehicles. He is actively seeking opportunities in robotics and autonomous systems where he can contribute to building reliable, innovative solutions that tackle real-world challenges.