Matthew is a computational scientist and software developer with expertise in bioinformatics, scientific computing, and high-performance simulation. He currently serves as a Senior Scientist in the Department of Radiation Oncology at Washington University in St. Louis, where he leads and supports research in translational genomics, including the development of machine learning algorithms, bioinformatics pipelines, and high-throughput data analysis tools for cancer biology and immunotherapy research.
Matthew brings over a decade of experience in software design, algorithm development, and scientific programming across both academic and commercial environments. Prior to joining Washington University, he operated Inkman Software Solutions, where he developed custom software applications for engineering and data management. His earlier research experience includes graduate work at California Institute of Technology’s Computational Flow Physics Group, where he performed large-scale fluid dynamics simulations using high-performance computing methods, and served as system administrator for the group’s HPC cluster.
His technical skill set spans a wide array of programming languages and platforms as well as frameworks for machine learning, parallel computing (MPI), and scientific modeling. He has worked extensively in both Linux and Windows environments, and is highly proficient with tools such as Jupyter, Visual Studio, and RStudio.
Matthew holds an M.S. in Mechanical Engineering from California Institute of Technology and a B.S. summa cum laude in Mechanical Engineering from Northwestern University. His work has been featured in Nature, Cancer Discovery, Science Translational Medicine, and other leading journals. He is a named contributor on numerous high-impact publications involving genomic analysis, immuno-oncology, and advanced computational modeling.