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About

Tomasz Praczyk is a leading researcher in autonomous maritime robotics, with a primary focus on biomimetic underwater vehicles (BUVs) and intelligent navigation systems. His work bridges the gap between biological inspiration and practical engineering, particularly in the development of Autonomous Surface Vehicles (ASVs) and Autonomous Underwater Vehicles (AUVs) that mimic fish-like undulating propulsion. Praczyk’s most significant contribution is his pioneering neural anti-collision system for ASVs, which has garnered 68 citations and remains a cornerstone reference in the field. He has further advanced collision avoidance for biomimetic AUVs, demonstrating how neural networks can enable safe, autonomous operation in complex underwater environments. His research also extends to neuro-evolutionary techniques, such as the Hill-Climb-Assembler Encoding (HCAE), which optimizes small to mid-scale neural networks for classification and control tasks—a lightweight yet powerful tool for real-world robotic applications. With over 130 total citations across his most-cited works, Praczyk’s impact is evident in both the academic community and practical robotics, where his systems enhance the autonomy and reliability of underwater vehicles for surveillance, exploration, and defense. His work is essential reading for anyone interested in the intersection of artificial intelligence, robotics, and marine technology.