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About

P. Panjan is a researcher whose work sits at the intersection of laser surface engineering, materials science, and computational mathematics. Specializing in robot laser hardening of metals and steels, Panjan has made notable contributions to understanding and optimizing laser surface treatment processes, particularly addressing the practical challenge of overlapping laser beam paths in robotic applications — a foundational concern in industrial laser hardening that has attracted 11 citations since its 2013 publication. A distinctive hallmark of Panjan's research is the innovative application of fractal geometry to characterize materials processed through laser techniques. By employing fractal dimensions to analyze surface morphology, porosity, and microstructural complexity — properties ill-suited to classical Euclidean description — Panjan has advanced quantitative methods for evaluating hardened specimens. This includes a 2017 contribution introducing a novel method for estimating the Hurst exponent in 3D objects, reflecting an interdisciplinary fluency bridging mathematics, computer science, and engineering. Panjan has also explored intelligent systems, using neural networks to predict specimen hardness, demonstrating forward-thinking integration of machine learning into materials processing optimization. Collectively, this body of work establishes Panjan as a methodologically creative researcher pushing laser hardening science toward more rigorous, computationally informed foundations.