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About

Manish Prajapat is a leading researcher at the intersection of autonomous racing, safe exploration, and nonlinear control systems. His most prominent work, "AMZ Driverless: The Full Autonomous Racing System" (2020, 11 citations), presents the complete software stack and algorithms that powered an autonomous racecar to navigate unknown tracks at high speeds. This paper demonstrates a robust, extensible architecture that combines perception, planning, and control for real-time racing—a landmark contribution to autonomous driving research. More recently, Prajapat has tackled a fundamental challenge in robotics: safe exploration under uncertainty. In "Safe Guaranteed Exploration for Nonlinear Systems" (2025, 3 citations), he proposes a novel framework that ensures both safety and sufficient exploration in environments with a-priori unknown constraints. This work is critical for autonomous systems that must operate reliably in unstructured settings, from search-and-rescue to planetary rovers. By balancing rigorous safety guarantees with exploration completeness, Prajapat's research pushes the boundaries of what autonomous systems can achieve. His contributions are shaping the next generation of robots that can learn and act in the real world with unprecedented reliability.