I am an Associate Professor of Mechanical Engineering at Saint Martin's University and an Affiliate Associate Professor at the University of Washington. I work in robotics, real-time computing, and augmented cognition, grounded in both technical and humanistic inquiry.
My current research explores machine learning for nonlinear control systems, embodied artificial intelligence, and the intersection between psychoanalysis and artificial intelligence. I've published peer-reviewed papers in the areas of control systems, instrumentation, mechatronics, nanoMRI, information architecture, artificial intelligence (AI), AI policy, augmented cognition, and engineering education. I'm the lead author of a recent textbook published by The MIT Press, An Introduction to Real-Time Computing for Mechanical Engineers.
I earned my Ph.D. in Mechanical Engineering from the University of Washington in 2014, where my dissertation introduced the theory and experiment of separative magnetization transport for nanoMRI. Complementing my engineering research, I'm a candidate analyst at the Lacanian School of Psychoanalysis, where I investigate the symbolic structures that shape human thought, language, and computation.
I've taught courses in mechatronics, system dynamics, control systems, robotics, real-time computing, engineering computing, AI, engineering mathematics, and machine design at both the undergraduate and graduate levels. I use a variety of pedagogical approaches, including project-based learning, flipped classrooms, and experiential learning, to engage students in hands-on, real-world applications of engineering principles.
In service to the profession and my institutions, I direct the M.S. in Mechanical Engineering program, advise student chapters of ASME and NSBE, and have chaired the faculty in the Hal & Inge Marcus School of Engineering. I also mentor student researchers and lead collaborations in cross-disciplinary projects spanning robotics, artificial intelligence, and cognition.