Fahad is a dedicated postdoctoral research scientist in Biostatistics at the CU Anschutz School of Medicine, with a strong background in statistical science, his Ph.D. dissertation, titled Statistical Machine Learning Models for Biomedical Science, reflects his deep interest in advancing the field of biomedical data science. Fahad's research spans various areas, including machine learning, statistical uncertainty quantification, computational biology, and biostatistics. His recent work focuses on detecting and interpreting patterns in high-dimensional biomedical data, particularly in cancer research. He applies statistical machine learning to enhance human disease diagnosis and monitoring, with a special emphasis on cancer infrared tomography, genomics, and medical imaging. Fahad's interdisciplinary approach integrates advanced statistical modeling, time series analysis, and machine learning techniques to improve the accuracy and reliability of disease prediction, diagnosis, and treatment, contributing significantly to the advancement of biomedical science. Before joining CU Anschutz, Fahad was an ORISE fellow at NCTR, FDA.