From student to professor: Francis Ogoke joins MechE

When Francis Ogoke first arrived at Carnegie Mellon as a graduate student, he was driven by a question that still defines his work today: how can computation help us better understand the physical world? Now, as an assistant professor in the Department of Mechanical Engineering Ogoke explores that question in a lab of his own. 

As an undergraduate student at Princeton University, Ogoke was fascinated by the way computation could be used to tackle engineering challenges by modeling complex physical systems. When he began searching for a graduate program, Carnegie Mellon stood out for its expertise in bridging machine learning with a wide range of engineering disciplines.

“I completed my PhD under Amir Barati Farimani, focusing on developing machine learning tools to better understand and control additive manufacturing processes. Within this field, a key challenge is that the  physical systems involved are hard to model and even harder to observe directly,” Ogoke said. “In additive manufacturing, changes at the microscale significantly influence the performance and integrity of printed parts, so we need to understand how behavior across different time and length scales connect.”

As a graduate student, Ogoke experienced firsthand the advanced collaboration that defines CMU’s College of Engineering. Working alongside experts in thermoscience and manufacturing, in collaboration with Sandia National Laboratories and the Army Research Laboratory, he learned how to approach problems that no single discipline, or person, can solve alone.

After completing his PhD, he spent a year at MIT as a postdoctoral researcher working at the intersection of AI, design, and manufacturing. 

Now back at CMU as faculty, Ogoke’s FORGE Lab is developing AI methods to enhance, understand, and control engineering processes, from additive manufacturing to digital twins and beyond. Looking ahead he envisions expanding these methods to other situations where simulation and control remain challenging like climate and weather modeling, battery systems, and broader thermal-fluid applications. 

Teaching at CMU has a special meaning for Ogoke, because as a former student he understands both the intensity and the opportunity of the student experience.

The CMU community is so collaborative, it’s truly somewhere everyone is celebrated and embraced.

Francis Ogoke

“CMU students are so passionate about what they’re doing and it’s really cool to work with them and learn from them everyday,” he said. “The community is so collaborative, it’s truly somewhere everyone is celebrated and embraced. I believe my experience does make me uniquely qualified to appreciate what these students are experiencing, and to act as an anchor for them.”

Ogoke is teaching Intro to Deep Learning and is focused on preparing students for what is to come as they embed AI and machine learning within their careers. He recognizes that come 2030, there will be brand new tools in practice that they will have never seen before, but by understanding the underlying concepts of why and how tools today work, his students can transfer the concept from fundamental math to any state of the art software we may see in the next decade. 

Outside of the lab, Ogoke finds balance through running and music. During his time as a CMU graduate student, he played trombone in the university orchestra. While he doesn’t play as often as he would like these days, he still gets his musical fix as a proud supporter of The Pittsburgh Symphony Orchestra.