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Thomas Tam

Health Innovation • CMU Startup • Applied AI @ NASA and Pitt • Nucleate Pittsburgh

Thomas Tam is a Machine Learning Engineer at NASA, where he specializes in developing and implementing machine learning algorithms for various applications. His educational background includes a Bachelor of Arts in Applied Mathematics from the University of California, Berkeley, and a Master of Science in Computer Science from the Technical University of Munich, where he focused on machine learning.

Professional Experience

  • NASA: As a Machine Learning Engineer, Thomas works on projects that leverage advanced machine learning techniques to enhance NASA's capabilities in data analysis and decision-making processes.
  • Technical Skills: He is proficient in programming languages such as Python and C++, and has experience with machine learning frameworks and tools.

Contributions and Research

Thomas has been involved in various research projects that integrate machine learning with aerospace applications. His work contributes to NASA's mission by improving the efficiency and effectiveness of data processing and analysis.

Online Presence

Thomas maintains an active LinkedIn profile under the username "thomasyctam," where he shares insights related to artificial intelligence and machine learning, reflecting his engagement with the tech community.

This combination of education, professional experience, and active participation in the field positions Thomas Tam as a significant contributor to the advancements in machine learning at NASA.

Highlights

Jan 1 · nas.nasa.gov
Advanced Modeling and Simulation (AMS) Seminars
Jan 17 · youtube.com
I interviewed a machine learning engineer! - YouTube
I interviewed a machine learning engineer! - YouTube

Related Questions

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Thomas Tam
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Location

Pittsburgh, Pennsylvania, United States