Miguel Á. Carreira-Perpiñán is a professor in the Department of Computer Science and Engineering at the University of California, Merced. His research interests are in machine learning and optimization. He is the recipient of an NSF CAREER award, a Google Faculty Research Award, and best paper awards at AISTATS and Interspeech.
Currently, his research group is mostly focused on machine-learning (ML) models based on decision trees and trained using the tree alternating optimization algorithm (TAO). These models excel with tabular datasets in terms of predictive accuracy, but they are also explainable, as required in many practical applications (financial, legal, government, health), and they can provide insights about the data beyond simple predictive power. This work has resulted in multiple research publications at top ML and artificial intelligence (AI) conferences, as well as a granted patent and the foundation of a startup.