Philip Sterne, Ph.D.


College of Computational Sciences


  • Ph.D. in Physics from Cambridge University
  • Top dissertation for MSc Artificial Intelligence at Edinburgh
  • Commonwealth Scholar; Mandela Cambridge Scholar
  • Started the machine learning team at, and helped grow the business to $200M in annual revenue
  • Reviewer for NIPS (the top machine learning conference)

Philip Sterne has solid foundations in both the theoretical and practical application of Machine Learning. With his Ph.D. in Physics from Cambridge University, he has contributed to the understanding of statistical inference in random graphs. In his commercial career, he has built machine learning applications in banking and online retailing. His main research interest is in understanding the brain as performing optimal statistical inference under certain constraints.

With several years of lecturing experience under his belt, Professor Sterne has found that the best teaching happens when the lecturer is approachable and enthusiastic and for optimal learning, students are pointed in interesting directions and allowed to tackle the material themselves (with a little light guidance whenever obstacles arise). Professor Sterne teaches the Computation: Solving Problems with Algorithms Core Course and the Machine Learning for Science and Profit Concentration Course.