Zhuoyang Pan

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About

Zhuoyang Pan is an emerging researcher in the field of real-time computing and intelligent scheduling, with a primary focus on deep reinforcement learning (DRL) and optimization algorithms. His most-cited work, "A DRL-based online real-time task scheduling method with ISSA strategy" (2024), introduces a novel approach that integrates DRL with an improved sparrow search algorithm (ISSA) to address the challenges of dynamic task scheduling in real-time systems. This paper, which has garnered 7 citations in a short time, demonstrates his ability to blend theoretical advances with practical solutions for time-critical applications. Pan’s contributions lie in enhancing the efficiency and adaptability of scheduling methods, particularly for environments where tasks must meet strict deadlines. His research has implications for cyber-physical systems, edge computing, and industrial automation. As a rising scholar, Pan’s work is gaining attention for its innovative use of reinforcement learning to optimize decision-making under constraints, marking him as a promising voice in the intersection of AI and real-time systems.