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About

Jianliang Ai is a leading researcher in autonomous aerial systems, with a primary focus on the guidance, control, and motion planning of unmanned aerial vehicles (UAVs) and air combat platforms. His work addresses two critical frontiers: enabling runway-free recovery for fixed-wing UAVs—a key enabler for their deployment in expeditionary and defense roles—and advancing the longstanding challenge of autonomous air combat. In his highly cited 2019 review on autonomous air combat guidance and control (36 citations), Ai systematically surveyed decades of research, identifying the unresolved complexities of highly dynamic, stochastic combat scenarios. He further contributed to sequential decision-making under uncertainty, developing a simulation-based projected policy iteration method for quadrotor robot games (2019). More recently, his 2024 comprehensive review on runway-free UAV recovery (7 citations) synthesizes solutions for a critical operational bottleneck, highlighting his sustained influence on practical UAV autonomy. Ai’s work bridges theoretical control and learning methods with real-world operational requirements, making him a key voice in the evolution of intelligent, self-reliant aerial systems.