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 David Fawcett
P 248.204.3560
E dfawcett@ltu.edu

David Fawcett

Math + Computer Science
Adjunct Faculty

David Fawcett holds a Masters degrees in Computer Science & Computer Control Systems (MSECE) and Electrical Engineering (MSEE, BSEE) all from Wayne State. He worked at Ford Motor Co. 32 years and held various Engineering/CAE/CAD/ and Management positions in his Ford career. While at Ford Engineering staff he was on the team that introduced computer graphics for body surface design called PDGS. He also developed software for visualizations and error checking for Finite Element meshes which allowed an entire car body to be analyzed.  At the Ford Electronics Division he helped introduce CAD, CAE and Expert Systems to aid the interface between design and manufacturing. During the “Ford 2000” restructuring, starting in 1995, he was Operations Research & KBE Manager and helped bring Knowledge Based Engineering (KBE) into being. After early retirement from Ford in 2000, he consulted for several years, and also joined the faculty of LTU in 2001.

He has been teaching at LTU as an Adjunct for 15 years. Professor Fawcett has taught Data Structures, C++ (CSI & CS II), Artificial Intelligence, Software Engineering, Computer Animation, and is currently teaching Cryptography (on-ground/on-line) and Data Structures (on-ground/on-line)  and plans to expand his online teaching to other courses. He is currently developing the Introduction to Algorithms graduate level course to be taught this fall.

Professor Fawcett has written many applications and teaching tools in diverse areas of computer science and engineering including Digital Signal Processing for voice, Fuzzy Logic, Neural Nets, Data Structures, Source Code Management and Complexity Analysis, Symbolic Mathematics, Rubik’s Cube Solver and more. Professor Fawcett has presented papers and published in the SAE Journal, Design Automation, Audio Engineering Society, Association for the Advancement of Artificial Intelligence (AAAI) and other publications.

He is also a trained musician and finds a strong correlation between music and mathematics.