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About

Yee-Pien Yang is a prominent researcher in human-robot interaction (HRI) and autonomous vehicle control, with a focus on bridging communication gaps between humans and machines. His work centers on developing intuitive interfaces for robots, including speech synthesis and recognition with lip synchronization, as well as gesture-based tracking for more natural interaction. In the realm of self-driving electric vehicles, Yang has made significant contributions through hardware-in-the-loop (HiL) simulations that integrate dynamic path planning and model predictive control (MPC), enabling realistic testing of autonomous parking and driving maneuvers. His most-cited paper, "Human robot interactions using speech synthesis and recognition with lip synchronization" (2011), has garnered 16 citations, highlighting its foundational role in advancing robot communication capabilities. Another key work, "Hardware-in-the-Loop Simulation of Self-Driving Electric Vehicles by Dynamic Path Planning and Model Predictive Control" (2021), with 9 citations, demonstrates his innovative approach to bridging simulation and real-world vehicle control. Yang’s research not only enhances robot autonomy but also paves the way for safer, more responsive human-robot collaboration in both domestic and industrial settings.