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machine learning, programming, big data, modeling & simulation, high-performance computing

This FIRE stream will end in 2022.

WHAT WE DO

Key Points:

  • Deep Learning & Artificial Intelligence

  • Data Processing, Programming & Modeling

  • Collaborative, hands-on, project-based learning

Detailed Description:

We focus on research projects in the field of machine learning, deep learning, and artificial intelligence using recently developed techniques, perspectives, and applications for market-relevant areas such as computer vision, natural language processing, and data analytics.

Our past projects include:

  • 3D Object Detection and Localization for Autonomous Vehicles

  • Object Recognition and Tracking for Surveillance Videos

  • Extreme Image Compression from Learned Objects

  • ...

  • and please visit our website for a detailed list of our past projects.

WHY IT MATTERS

Key Points:

  • Recent growths in big data, computational tools, and state-of-the-art research.

  • Machine learning applies to a variety of fields.

  • Outcomes can lead to broad impact.

  • Great career opportunities.

Detailed Description:

Machine learning is a crucial and sought-after skill with the recent growths in big data.
 

We work on projects that could lead to broad impact by making use of state-of-the-art research and computational tools.
 

Machine learning applies to a variety of automated tasks, such as:

  • Self-Driving Cars

  • Face Recognition

  • Malware Detection

  • Content Recommendations

  • and many more...

WHAT YOU LEARN

Key Points:

  • Analyze state-of-the-art techniques and open-source repositories.

  • Utilize and evaluate machine learning models using deep learning frameworks.

  • Collaborate to design, implement, and apply a machine learning model for real-world usage.

 

Detailed Description:

Analyze state-of-the-art techniques from recent scholarly papers and open-source repositories.

 

Perform data preprocessing, training, optimization, and evaluation of machine learning models using deep learning frameworks (such as Keras, Tensorflow, and PyTorch).
 

Collaborate in a teamwork environment to design, implement, and apply machine learning models for real-world usage.