Mr. Ford specializes in data mining, machine learning, and optimization via the use of evolutionary algorithms. At Exponent, he has worked on projects involving traditional data analysis/regression, automatic/aided target recognition, and software development of business intelligence tools. He works and develops solutions in Windows and/or Linux as dictated by the needs of his projects.
As a graduate student in Computation and Neural Systems at the California Institute of Technology (Caltech), Mr. Ford applied evolutionary algorithms to various tasks including the optimization of various computational chemistry packages. A significant part of his dissertation outlined his theory that quantal effects may play a role in synaptic plasticity, a process that is thought to play a central role in learning and memory. In addition, he has experience with various experimental techniques employed in biochemistry to study neural systems. Mr. Ford successfully defended his Ph.D. thesis in September of 2011 and will have his degree conferred in the spring of 2012.
Finally, Mr. Ford was an active member of several student organizations as an undergraduate and graduate student, including the Graduate Student Council and the Intellectual Property Law Club at Caltech. During his time at Caltech, he had the honor of leading their Graduate Student Council as the Chairman of the Board. Prior to joining Exponent, he also worked in supercomputing at the Pittsburgh Supercomputing Center and as an independent technical consultant supporting the drafting of patents and data mining for the litigation of intellectual property.
Boxe CS, Worden JR, Bowman KW, Kulawik SS, Neu JL, Ford WC, Oster-man GB, Herman RL, Eldering A, Tarasick DW, Thompson AM, Doughty DC, Homann MR, Oltmans SJ. Validation of northern latitude tropospheric emission spectrometer stare ozone profiles with ARC-IONS sondes during ARCTAS. Atmospheric Chemistry and Physics 2010; 10:9901–9914.
Stiles JR, Ford WD, Pattillo JM, Deernick TE, Ellisman MH, Bartol Jr TM, Sejnowski TJ. Spatially realistic computational physiology: Past, present, and future. G. Joubert, et al. (eds), Parallel Computing: Software Technology, Algorithms, Architectures & Applications, Elsevier, Amsterdam, pp. 685–694, 2004.