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Dr. Ryan Soklaski

Ryan Soklaski is a technical staff member of Lincoln Laboratory’s Intelligence & Decision Technologies group. There, he researches machine learning techniques that are performant under data-restricted circumstances, and works as a core developer for a lab-internal machine learning library. He is also the lead instructor of the CogWorks course at the Beaver Works Summer Institute, and the creator of the educational site “Python Like You Mean It”.

Prior to joining the laboratory, Ryan earned his PhD in theoretical condensed matter physics at Washington University in St. Louis. His doctoral thesis involved conducting physics simulations on high-performance computing clusters to study the physical mechanisms that drive the glass formation process in metallic liquids. His interests include methods of numerical analysis, developing software in Python, and quantum mechanics.

Courses taught by Dr. Ryan Soklaski

BWSI Python Core 2023

BWSI Python Core 2023

2023

  • Free
  • Oct 01, 2023
  • 2023
  • Dr. Ryan Soklaski
  • Duration: 50 Weeks
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BWSI Python Core 2023

Duration: 50 Weeks 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:
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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