Daniel McKenzie

Assistant Professor, Applied Mathematics and Statistics

Daniel McKenzie

Daniel McKenzie is an applied mathematician, joining the AMS department at Mines in Fall 2022. He received his B.Sc from the University of Cape Town (South Africa), his PhD from the University of Georgia, and completed his postdoctoral work at the University of California, Los Angeles.

His research lies on the intersection of machine learning and signal processing. More specifically, he is interested in zeroth-order optimization, learning to optimize, and high-dimensional unsupervised learning. At Mines he is looking forward to applying his machine learning expertise in inter-disciplinary collaborations.
Daniel enjoys teaching, particularly courses on data science and computational mathematics, and working with students. In fact, several of his favorite research papers have an undergraduate coauthor.

Outside of work, he enjoys hiking, reading fiction, watching sports, and spending time with his family.


Chauvenet Hall 235


Personal website: https://danielmckenzie.github.io/


  • B.Sc(hons) in Mathematics and Applied Mathematics. University of Cape Town, 2010
  • M.Sc in Mathematics. University of Cape Town, 2014
  • PhD in Mathematics. University of Georgia, 2019

Research Areas

  • Zeroth-order optimization and applications
  • Signal processing, particularly compressed sensing
  • Learning-to-optimize for inverse problems
  • Nonlinear dimensionality reduction
  • First passage percolation