His main research areas are statistical pattern recognition, machine learning, signal and image processing, and systems biology.
He has worked extensively in the field of error estimation for pattern recognition and machine learning, having published with Edward R. Dougherty the first book dedicated to this topic.
He worked as a post-doctoral researcher at the University of Texas MD Anderson Cancer Center, under the supervision of Louise Strong and Edward R. Dougherty.
Braga-Neto invented, with his Ph.D. student Levi McClenny, self-adaptive physics-informed neural networks, which accelerate the convergence of PINNs in the case of difficult (stiff) PDE problems.
In 2015, Braga Neto published, in collaboration with Edward R. Dougherty, the first book dedicated to the topic of error estimation for pattern recognition and machine learning.