January 2, 2024
We’re pleased to announce that Jan Fuhg has joined UT Austin’s Department of Aerospace Engineering and Engineering Mechanics as an assistant professor. Fuhg, who completed his Ph.D. in mechanical engineering at Cornell University last fall, also holds an M.S. and B.S. in computational engineering from Leibniz University Hannover, Germany. His research group develops theoretical and computational tools for modeling and forecasting the mechanics of materials across different lengths and time scales. To achieve this, Fuhg’s work employs and develops advanced machine learning and numerical simulation methods. Learn more about Fuhg in this Q&A.
Why is your research on materials meaningful?
Materials are everywhere around us – everything is made up of some kind of material. Engineering breakthroughs in the last 200 years or so have involved pushing materials to their limits by constraining them more and more. To do this reliably, we need to understand how these materials work – looking at how they behave if they are loaded, what effect temperature has, etc. This is called material characterization, which is what I do, but within computational simulations.
Material characterization is an important tool for computational mechanics since we need a very accurate understanding of a material’s behavior before we can use it in our simulation. Why do we want to develop simulations? We can’t build everything, and it can be expensive to build physical models, or sometimes even dangerous (e.g., building a structure with people inside). Developing simulations can be a cost-saving and safer solution. But these simulated approximations must be extremely accurate for them to be considered reliable.
My research aims to develop the tools that allow for a broad range of materials to be characterized quickly and accurately. They can then be applied to a wide variety of materials, such as biomedical equipment, prosthetics, artificial bones and more. One example of where this is useful is in the manufacturing process, such as 3D printing, which has the ability to create a lot of different materials very quickly. The turnover from these new manufacturing techniques is very fast, therefore characterization needs to be quick and accurate. Machine learning can have a big impact here.
Why did you decide to join Texas ASE/EM?
Austin’s vibrant culture and the department’s well-respected reputation made it an easy decision to apply. I also saw opportunities to collaborate on interdisciplinary work and develop good industry connections. Overall, UT has the full package, including an environment that allows for great potential and research breakthroughs to be possible. I’m excited to be a part of it.
What do you enjoy most about your research?
I like the prospect that material characterization research will never stop evolving. Current applications and technologies are very reliant on an accurate understanding of materials. We need to do an even better job of pushing the constraints of these materials further so that we can continue to develop technologies that are at low cost, and very reliable and efficient.
Tell us about your teaching philosophy.
I think it’s important that students learn to think scientifically about engineering problems. The recent developments of AI could create a turbulent time in education for the next 10-20 years. Students should be capable of transferring their knowledge and skills to different disciplines. I encourage them to be open-minded and allow them to solve problems in many different ways.
What future do you see for AI?
It’s going to be collaborative, and I think it has huge potential for us to replace the jobs that we don’t want to do. But AI cannot acquire new knowledge easily, so that's where we need to come in as researchers, and that's where our students need to be – pushing further than we are now to advance what's possible.
How do you like to spend your free time?
I like spending my time outdoors like running and hiking. I also love to cook so I am looking forward to learning more about Texas BBQ.
Learn more about Fuhg’s work on his website.
