Blake Mason

Metric learning and active machine learning, focussed on reducing the sample complexity of learning.


Blake Mason grew up in Northern –California and also lived in LA. He did his Bachelors in Electrical Engineering at USC and his Ph.D. in Electrical and Computer Engineering at the UW Madison. Beyond his studies, he is a published poet, choral vocalist, and always loves a good book.


  • PhD, Electrical and Computer Engineering, University of Wisconsin–Madison
  • MS, Electrical and Computer Engineering, University of Wisconsin–Madison
  • BS, Electrical Engineering, University of Southern California

Research Description

My research is focused on developing new algorithms and theory for metric learning and active learning. I combine statistical and algorithmic tools to analyze metric learning from noisy pairwise comparisons, motivated by a collabortive project developing tools for personalized chemistry education at UW–Madison. I am also developing active methods for adaptive multiple testing and applying this to learning nearest neighbors and neighborhood graphs from noisy data. My research has been applied to study chemistry education in large classrooms, fertility and miscarriage, and preference graph detection.


  • Wisconsin Institute for Discovery
  • Institute for the Foundations of Data Science