Dr. Muhammad Sajid has dedicated his career to advancing the field of subsurface geophysics and reservoir management, with a specific focus on hydrocarbon exploration, production, and Carbon Capture, Utilization, and Storage (CCUS) initiatives. His impressive track record includes the development and deployment of cutting-edge technologies for subsurface reservoir characterization, overburden and seal analysis, and subsurface structure analysis. These tools not only improve the accuracy and efficiency of hydrocarbon resource extraction but also contribute significantly to the advancement of CCUS studies, addressing the critical need for sustainable energy solutions. Dr. Sajid holds two Master’s degrees and a Ph.D. in geoscience and possesses over 17 years of experience in the oil and gas industry. His expertise lies in seismic attributes, highresolution reservoir characterization attributes analysis, and advanced seismic interpretation. He has successfully developed several advanced seismic technologies with practical applications in the upstream field. These technologies include algorithms for dip-guided seismic bandwidth expansion (non-stationary differential resolution or NSDR and structural-oriented dip-guided enhanced non-stationary differential resolution or eNSDR), e-coherency for structureoriented denoising, spectral analysis, and decomposition, AI seismic attributes, as well as advanced Artificial Intelligencebased Seismic Features Recognition and Extraction technologies with vectorization capabilities for 2D, 2.5D, and 3D architectures, seismic inversion, and reservoir characterization. Dr. Sajid has also played a pivotal role in staff development within geoscience seismic interpretation, conducting research and driving technological innovation. His work is wellrecognized, with publications in top journals and conferences. With over 17 years of experience in the oil industry, he currently serves as a principal geophysicist at PETRONAS, where he remains committed to exploring advanced technologies such as AI, ML, signal processing, and high-resolution reservoir characterization.