Invited Talks

Computational Intelligence in Automotive R & D and implications to BMI

Danil Prokhorov, Toyota Tech Center

Abstract

Computational intelligence is traditionally understood as encompassing artificial neural, fuzzy and evolutionary methods and related techniques. In this presentation I will discuss CI methodological issues and illustrate them with several representative applications from the areas of vehicle manufacturing, vehicle system monitoring, control and active safety. I will also share some lessons learned about CI R & D and implications to Brain-Mind research.

Short Biography

Dr. Danil Prokhorov began his technical career in St. Petersburg, Russia, in 1992. He was a research engineer in St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences. He became involved in automotive research in 1995 when he was a Summer intern at Ford Scientific Research Lab in Dearborn, MI.

In 1997 he became a Ford Research staff member involved in application-driven research on neural networks and other machine learning methods. While at Ford, he took active part in several production-bound projects including neural network based engine misfire detection. Since 2005 he is with Toyota Technical Center, Ann Arbor, MI. He is currently in charge of Mobility Research Department with Toyota Research Institute North America, a TTC division. He has more than 100 papers in various journals and conference proceedings, as well as several patents, to his credit. He is also a President-Elect of the International Neural Network Society. His home page is http://home.comcast.net/-dvp/