Incoming Assistant Professor / University of Utah Mechanical Engineering
Joseph Kirchhoff
Mechanics, sensing, and computation for advanced composite manufacturing.
I build experimental and computational tools that help engineers understand what is happening inside composite manufacturing processes, infer what cannot be measured directly, and make better decisions while a structure is being made.
About
Making manufacturing measurable, modelable, and controllable.
I am currently a postdoctoral researcher at NASA Langley Research Center, where I work with Tyler Hudson on OATMEAL and energy-efficient thermoplastic composite processing. In Fall 2027, I will join the University of Utah Department of Mechanical Engineering as an assistant professor.
At Utah, I will launch a research group focused on digitally integrated, energy-efficient manufacturing of high-performance structures, including settings where sensing, automation, and trustworthy models must support decisions without constant human oversight. I completed my Ph.D. at UT Austin, co-advised by Prof. Omar Ghattas and Prof. Mehran Tehrani.
Research program
Three thrusts for the future Utah research group.
Extending OATMEAL toward thermoplastic material systems designed for high-rate processing, embedded sensing, and closed-loop manufacturing.
02 / real-time inference Surrogate-enabled inverse frameworksRecovering spatially varying manufacturing state from indirect observations using PDE-constrained optimization, neural operators, reduced models, and uncertainty-aware inference.
03 / resilient autonomy Manufacturing autonomy for remote environmentsClosing the loop between process models, sensing, inversion, and control so composite manufacturing can adapt in operator-sparse settings, including space and other remote aerospace environments.
Approach
Manufacturing physics, sensing, and autonomy in the same loop.
The group I am building at Utah will connect material processing experiments, in-situ sensing, thermal and mechanical characterization, and computation for high-dimensional inverse problems, surrogate modeling, optimization, and uncertainty quantification.
Future group
Lab launching Fall 2027. Conversations welcome now.
I would love to meet prospective graduate students during my 2026-2027 postdoctoral year. Strong fits may be interested in composites, computational mechanics, inverse problems, scientific machine learning, controls, or experimental mechanics.
I am especially excited about collaborations that connect manufacturing science, aerospace structures, uncertainty quantification, autonomous systems, remote operations, and real process data.
Send a short note describing your interests, current work, and how you think our research questions might overlap.
Emailjoseph dot kirchhoff @ utah.edu
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