Matthew Campbell

Developing insights into the future of engineering design, Dr. Matthew Campbell is a distinguished professor in the College of Engineering at Oregon State University. With a PhD in Mechanical Engineering from Carnegie Mellon University, Dr. Campbell's expertise lies in the intersection of computational geometry, artificial intelligence, automation, machine learning, and design optimization. His pioneering work focuses on automating complex engineering design tasks, making significant strides in the field by leveraging numerical optimization and AI technologies. Dr. Campbell's contributions to the field have been widely recognized, earning him the prestigious 2017 OSU Industry Partnering Award. His prolific academic career is marked by an extensive publication record, with over a hundred articles that have advanced the understanding and application of computational methods in engineering. His research not only pushes the boundaries of what is possible in engineering design but also bridges the gap between theoretical advancements and practical applications. Before his tenure at Oregon State University, which began in 2013, Dr. Campbell enriched his academic and research experience at the University of Texas at Austin and the Technical University of Munich. These positions allowed him to cultivate a diverse and comprehensive perspective on global engineering challenges and solutions. His international experience has been instrumental in shaping his approach to research and teaching, fostering a collaborative environment that encourages innovation and critical thinking. At Oregon State University, Dr. Campbell is committed to mentoring the next generation of engineers, guiding students through the complexities of modern engineering problems with a focus on interdisciplinary collaboration. His teaching philosophy emphasizes the importance of integrating theoretical knowledge with practical skills, preparing students to tackle real-world challenges with confidence and creativity. Dr. Campbell's ongoing research projects continue to explore the potential of AI and machine learning in transforming engineering practices. By developing new methodologies and tools, he aims to enhance the efficiency and effectiveness of engineering design processes, ultimately contributing to the advancement of technology and industry standards. His work not only benefits the academic community but also has significant implications for industry partners seeking innovative solutions to complex engineering problems.