Bringing transparency to a black box
Machine learning is a type of artificial intelligence in which researchers train computers to analyze enormous data sets to find patterns and extract other helpful insights. A variety of industries and disciplines are already taking advantage of the speed and capabilities offered by machine learning algorithms, including finance, logistics and many STEM research fields.
The latter is where Appelö’s interests lie.
“My team and I try to create methods that make doing computer simulations faster, more accurate and more predictive,” said Appelö, whose research group is currently focused on things like plasmas, complex fluids and electromagnetic waves.
“Machine learning offers new opportunities to do this, but you have to be careful about enforcing the physics and constraints of reality,” he said. “You can’t treat it like a black box and trust it completely.”
Machine learning has the promise to accelerate research in STEM fields, but this will require people with unique training and expertise. MSU has won an NSF grant to help prepare that next-generation workforce. Credit: This image was created by the DALL·E 2 AI system.
Appelö and his colleagues saw an opportunity to get MSU’s students in on the ground floor of unpacking that black box with support from NSF. In the new program, the research and innovation that goes into harnessing the power of machine learning will become part of students’ existing doctoral training.
In particular, the program will focus on using machine learning to accelerate simulations spanning a broad range of size scales found in many STEM problems.
Think of drug design, wherein the shape and composition of a molecule can impact the health of an entire organism. Similar scale considerations are also present in engineering materials for better batteries, building reactors for fusion energy and furthering many more applications.
That’s in part why MSU is a natural fit for this traineeship program, Appelö said. The university attracts students with a diverse range of interests and it has the faculty to support them — a feature that originally drew Appelö to MSU and its CMSE department.
“Our approach is really in the spirit of CMSE. It’s a department that’s highly interdisciplinary and convergent,” Appelö said. “For the grant, we put together a team of co-investigators and senior personnel that cover a lot of different things in a program that has a unique structure to provide students with more interaction and engagement.”
To reach its technical goals, the new program will be integrated with existing STEM graduate programs to offer more instruction- and research-based opportunities emphasizing machine learning. MSU is also leveraging partnerships that will enable students to participate in internships in industry and national laboratories.
“This is an important component to keep things very real for our students,” Appelö said. “These places are in the business of solving real problems.”
The MSU team also wants to ensure its students are building the nontechnical skills they’ll need for success. To that end, the program also will include training and experience in outreach, entrepreneurship and communication.
“We want to make sure we’re really training tomorrow’s Ph.D. leaders in computational and STEM fields,” Appelö said. “There’s a need, and we’re excited to help enable a better education in this field.”