Dr. DeBlasio's expertise is historically in algorithms and machine learning for computational biology, specifically in the areas of algorithm configuration, high-throughput genomics, and string hashing schemes. Recent collaborations have pulled his work towards the use of machine learning for analyzing hyper- and multi-spectral imaging for domain awareness.Prior to UTEP, he was at Carnegie Mellon University, where he was a Lane Fellow in the School of Computer Science for the last three years. Dr. DeBlasio earned a doctoral degree in computer science from the University of Arizona. He recently published, Parameter Advising for Multiple Sequence Alignment, a book in the Springer Computational Biology series. He is member of the International Society for Computational Biology (ISCB), and recently completed serving on the ISCB Board of Directors. His term on the board brought upon numerous speaking engagements, empowering tomorrow’s leaders in computational science. Dr. DeBlasio's work, and the work of his students, can be found on his website, http://deblasiolab.org.