Francis Ogoke
Assistant Professor of Mechanical Engineering
I develop machine learning methods for monitoring, simulating, and controlling manufacturing processes. My work focuses on physics-informed deep learning, generative models for uncertainty quantification, and foundation models that can generalize across engineering domains.
Before joining CMU, I was a postdoctoral associate at MIT working with Faez Ahmed and John Hart to study the use of machine learning to assess manufacturability in the design process. I received my Ph.D. from Carnegie Mellon University, where I was advised by Amir Barati Farimani and developed deep learning frameworks for laser powder bed fusion. I hold a B.S.E. in Chemical Engineering from Princeton University.
Team
Shohom Bose-Bandyopadhyay
PhD Student
Manufacturing Data & Quality Prediction
Megan Bynoe
PhD Student
Process Control for Additive Manufacturing
Melik Demirel
PhD Student
Turbulence in Additive Manufacturing & Propulsion
Yan Ting Ng
MS Student
Generative Methods for Physics Simulation
Neal Ramaswamy
MS Student
Control Systems & Advanced Manufacturing
Sangram Kumar Sahoo
Research Assistant
Scalable Physics Surrogate Models
Vaibhav Parekh
Research Assistant
AI Methods for Multi-fidelity Modeling
Join the Lab
Applying:
Email oogoke@andrew.cmu.edu with your CV and a brief note about what problems interest you.
For PhD positions, you must also apply through the CMU MechE PhD program.