A dedicated physicist with over 18 years of experience in experimental condensed matter physics and advanced computational modeling, now leveraging high-performance computing, machine learning, and data-driven analytics to solve complex scientific and cybersecurity problems. Expert in designing and executing computationally intensive simulations and experiments using Python, Material Studio, VASP, CASTEP, LabVIEW, and modern machine learning frameworks. Highly skilled in numerical modeling, Monte Carlo simulation, optimization algorithms, statistical inference, and large-scale data analysis applied to materials science, nanotechnology, and cyber-physical systems. Proficient in translating physical laws into predictive algorithms and AI models for intelligent decision-making, anomaly detection, and system optimization. Experienced in a wide range of experimental techniques, including XRD, Raman, FTIR, UV-Vis and fluorescence spectroscopy, SEM, AFM, TEM, DSC, and TGA. Committed to mentoring the next generation of computational scientists and engineers and advancing discovery through physics-informed AI, secure computing, and scalable analytics.