Tomonori Honda has broad experience in engineering design and big data modeling, specializing in formalizing design theory for complex systems. His main research areas include design for system reliability, prognosis, and maintenance scheduling; design synthesis for complex multidisciplinary systems; and behavioral design theory.
Prior to joining PARC, Tomonori served as a principal data scientist at Edmunds.com, where he led the modeling and analytics effort including reinforcement learning framework for real-time ads targeting using big data. He also worked as a junior analytics manager at Opera Solutions, where he explored different techniques to improve model performances and won an in-house modeling competition.
Dr. Honda received his Ph.D. and M.S. in Mechanical Engineering from California Institute of Technology and B.S. in Mechanical Engineering and Nuclear Engineering from University of California, Berkeley. He had continued his Ph.D. research at Massachusetts Institute of Technology as a Postdoctroal Scholar and Research Scientist for several years. He has published over 25 papers in journals and peer-reviewed conferences. He has also won the 2013 JALA Ten Award from Society of Laboratory Automation and Screening (SLAS) and the 2013 ASME Design Theory and Methodology Best Paper Award.
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