INTERPRETABLE AI - Key Persons


Dimitris Bertsimas

Job Titles:
  • Co - Founders
  • Co - Founding Partner
Dimitris is a Co-Founding Partner of Interpretable AI, the Boeing Professor of Operations Research, and the Associate Dean for Business Analytics at MIT. He has received numerous research awards, has written over 200 research papers and 5 graduate textbooks that are used around the world. He was a Co-Founder of Dynamic Ideas LLC, the assets of which were sold to American Express in 2002.

Dr Daisy Zhuo - Founder

Job Titles:
  • Co - Founder
  • Co - Founding Partner
Daisy is a Co-Founding Partner of Interpretable AI. She has expertise in developing scalable machine learning techniques including Optimal Imputations, with extensive research and industry experience in applications of analytics and AI systems in health care. She has a PhD in Operations Research from MIT.

Dr Jack Dunn - Founder

Job Titles:
  • Co - Founder
  • Co - Founding Partner
Jack is a Co-Founding Partner of Interpretable AI. He has developed many novel analytics approaches including the Optimal Trees methodology, and has considerable experience applying machine learning and AI to problems in both research and industry settings. He is the co-author of the award-winning graduate level textbook Machine Learning Under a Modern Optimization Lens. Jack has a PhD in Operations Research from MIT.

Luca Mingardi

Job Titles:
  • Research Scientist
Luca is a Research Scientist at Interpretable AI. He is passionate about applying the newest technologies and developments in machine learning to bring value to businesses, and strives to have a significant impact on society through the use of analytics. He holds a Master of Business Analytics from MIT.

Maxime Amram

Job Titles:
  • Research Scientist
Research Scientist Maxime Amram presenting the broad applicability of Interpretable AI solutions in industrial settings at the MIT Paris Symposium Maxime is a Research Scientist at Interpretable AI. He leverages his expertise in machine learning to drive value for organizations, with extensive experience in the latest deep learning developments. He studied data science during his master's at MIT and holds a MS in Applied Mathematics from École Centrale Paris.