Robert Nowak

Robert Nowak is a Professor of Electrical and Computer Engineering at the University of Wisconsin-Madison, holding the Nosbusch Professorship in Engineering. His research focuses on signal processing, machine learning, optimization, and statistics, with notable contributions to neural networks, active learning, and in-context learning. He is affiliated with the School of Computer, Data & Information Sciences and collaborates on interdisciplinary projects involving AI, human-computer interaction, and vision systems.

His work spans theoretical advancements in approximation theory, regularization techniques, and neural network architecture design, alongside applied topics like humor analysis in AI, recommendation systems, and OOD detection. Recent publications emphasize multi-task learning, generative models, and scalable data filtering systems.

Nowak’s research intersects machine learning foundations and practical applications, with a focus on improving data efficiency, generalization, and human alignment in AI systems. He leads projects on active learning strategies for open-world scenarios and develops frameworks for label-efficient learning.