Research/Areas of Interest: Interpretable machine learning, human-in-the-loop machine learning


  • Bachelor of Science, Computer Science, New York University, New York, United States, 2016
  • PhD, Harvard University, Cambridge, United States, 2023


Isaac ("Ike") Lage is a Ph.D. candidate at Harvard University where he works on developing techniques to learn interpretable and intuitive machine learning models by incorporating user feedback into optimization. The aim of his research is to develop machine learning models that can effectively assist human decision makers to make better decisions in the context of broader sociotechnical systems.