ASME

Journal of Computing and Information Science in Engineering

Matthew I.  
Campbell, Ph.D
CAMPBELL

Areas of Interest

ARTIFICIAL INTELLIGENCE METHODS FOR COMPUTATIONAL DESIGN SYNTHESIS
MANUFACTURING PLANNING
Oregon State University, USA
Dr. Matt Campbell is a mechanical engineering professor with research focusing on automating difficult or tedious engineering design tasks. For over 20 years, he has focused on methods that independently create solutions for typical mechanical engineering design problems like gear trains, sheet metal, planar mechanisms, and planning for manufacturing, assembly and disassembly. In 2020, he was named an ASME fellow for his achievements in machine design, design theory, artificial intelligence, graph theory and numerical optimization. Prior to his current position within the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University, he was a William J. Murray Fellow at the Cockrell School of Engineering at The University of Texas at Austin, a Hans Fischer Senior Fellow at the Technical University of Munich, and a 2005 NSF CAREER awardee. He has over a hundred published articles and has been acknowledged with best paper awards at conferences by the ASME, ASEE, and the Design Society. He received his PhD from Carnegie Mellon University in 2000 with honors and membership in Phi Kappa Phi and Pi Tau Sigma.

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Announcements

July 17 Spotlight: “Information Embedding in Additively Manufactured Parts Through Printing Speed Control” 

A recording is now available for the July 17, 2024 JCISE Spotlight talk by Professor Jitesh Panchal on paper co-authored with Karim A. ElSayed entitled “Information Embedding in Additively Manufactured Parts Through Printing Speed Control” J. Comput. Inf. Sci. Eng. J. Comput. Inf. Sci. Eng. Jul 2024, 24(7): 071005 (10 pages) Paper No: JCISE-23-1496 https://doi.org/10.1115/1.4065089.

Announcements

June 18, 2024 Spotlight: “Updating Nonlinear Stochastic Dynamics of an Uncertain Nozzle Model Using Probabilistic Learning With Partial Observability and Incomplete Dataset”

A recording is now available on Youtube for the June 18, 2024 Spotlight talk by Professor Christian Soize (Université Gustave Eiffel) on his paper “Updating Nonlinear Stochastic Dynamics of an Uncertain Nozzle Model Using Probabilistic Learning With Partial Observability and Incomplete Dataset,”

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