edly

Ms. Kimberlee Chang

Ms. Kimberlee Chang is a Member of the Technical Staff at MIT Lincoln Laboratory. She earned her BS in astrophysics from the University of Wisconsin at Madison and her MS in electrical engineering at Tufts University. Since joining MIT Lincoln Laboratory, she has supported a variety of mission areas including, space situational awareness, air traffic control and humanitarian assistance and disaster response. Her primary research area is human machine collaboration and her recent work focuses on the use of gaming technology as a platform to train and benchmark human-AI teaming systems.

Courses taught by Ms. Kimberlee Chang

Trusted Analytics

Trusted Analytics

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:
Read More

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

Artificial Intelligence Foundations

Artificial Intelligence Foundations

Self-paced

The course begins with a brief history of Artificial Intelligence (AI), including a survey of representative AI success stories and covers topics such as AI data requirements and conditioning, a selection of AI techniques including supervised learning, unsupervised learning and . . .

  • Free
  • Apr 06, 2022
  • Self-paced
  • Dr. Sarah Mcguire, Dr. Julie Mullen, Ms. Lauren Milechin, Dr. Vijay Gadepally, Dr. Charlie Dagli, Dr. Mykel Kochenderfer, Dr. Olga Simek, Dr. Rajmonda Caceres, Dr. Ryan Soklaski, Mr. David Martinez
  • Duration:
Read More

Artificial Intelligence Foundations

The course begins with a brief history of Artificial Intelligence (AI), including a survey of representative AI success stories and covers topics such as AI data requirements and conditioning, a selection of AI techniques including supervised learning, unsupervised learning and . . .

Duration: Read More