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Dr. Michael Yee

Dr. Michael Yee is a Member of the Technical Staff in the Artificial Intelligence Technology Group. His research interests include robust and resilient AI, probabilistic programming, and sparse machine learning. Previous work has spanned information retrieval, text analytics, graph analytics, and distributed systems. Michael has been a recitation instructor for MIT’s 6.033 Computer System Engineering undergraduate course, and has helped teach the natural language week of a Beaver Works Summer Institute class for high school students.

Michael received his BS in Mathematics and Computer Science from Gordon College, and an SM and PhD in Operations Research from MIT. During his graduate studies, he enjoyed summer internships at a DoD agency and at MIT Lincoln Laboratory. His dissertation focused on techniques for inferring decision-making processes informed by bounded rationality.

Courses taught by Dr. Michael Yee

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Trusted Analytics

Trusted Analytics

Dr. Sarah Mcguire Dr. Julie Mullen Ms. Lauren Milechin Dr. Jeremy Kepner Dr. Michael Yee Mr. Justin Goodwin Dr. Vijay Gadepally
Self-paced

The Trusted Analytics course introduces students to topics of Artificial Intelligence and Machine Learning with an emphasis on building trust.  The issue of trust affects confidence in the analytics and artificial intelligence-machine learning systems in tandem with developing the trust . . .

  • Free
  • Mar 31, 2022
  • Self-paced
  • Dr. Sarah Mcguire, Dr. Julie Mullen, Ms. Lauren Milechin, Dr. Jeremy Kepner, Dr. Michael Yee, Mr. Justin Goodwin, Dr. Vijay Gadepally
  • Duration:
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Trusted Analytics

The Trusted Analytics course introduces students to topics of Artificial Intelligence and Machine Learning with an emphasis on building trust.  The issue of trust affects confidence in the analytics and artificial intelligence-machine learning systems in tandem with developing the trust . . .

Duration: Read More