Ph.D. researcher · University of Central Florida
I'm Nam Nguyen. I build dynamics models that combine physics with learning, measure how far they can be trusted, and put them inside controllers for race cars, quadrotors, and manipulators.
Open to ML and robotics internships
Research
My work sits at the intersection of three things: modeling a system, measuring how far the model can be trusted, and using it to control the system.
Learn how a system behaves from data, with physics built into the model so it holds up when data is scarce.
Measure how far the model can be trusted, so a controller knows when it is working outside what the model has seen.
Use the model to act: controllers that plan ahead, adapt online, and run on real hardware.
15% faster laps than standard MPC in a full-size race-car simulator
It estimates tire–road grip online and retunes its own cost weights through a differentiable MPC, so it holds pace when the surface changes.
IROS 2026 · PittsburghPresenting AD-MPCC
ACC 2025 · DenverPresenting Taylor neural networks
25% more accurate multi-step prediction than standard ML
A network that learns the derivative term of a Taylor expansion and keeps the system's monotonic behavior by construction.
HardwareArduino temperature-control lab, running MPC at 1°C steady-state error
Beyond the lab
Community
A YouTube series I founded and host for Vietnamese engineering researchers around the world.
Teaching
Hardware
Background
Education
University of Central Florida
Northern Arizona University
Hanoi University of Science and Technology
Availability
F-1 visa. Authorized to work in the US via CPT/OPT, with no sponsorship needed for internships.
Get in touchContact
I'm open to internship conversations and research collaborations in machine learning, robotics, and control.