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Undergraduate research on speeding up data centers earns ACM first prize
  1. Undergraduate research on speeding up data centers earns ACM first prize

    The student’s project targets critical moments where the next instruction in a program is only available in a slower type of memory.

  2. Rackham Predoctoral Fellowship for design of robust, reliable and repairable software systems

    Subarno Banerjee uses program analysis to improve software systems’ safety and security.

  3. Predoctoral Fellowship for mathematically provable hardware design

    Goel designs algorithms that can automatically demonstrate the correctness of hardware systems.

  4. Programming around Moore’s Law with automatic code translation

    Most programs in use today have to be completely rewritten at a very low level to reap the benefits of hardware acceleration. This system demonstrates how to make that translation automatic.

  5. Emotion recognition has a privacy problem – here’s how to fix it

    Researchers have demonstrated the ability to “unlearn” sensitive identifying data from audio used to train machine learning models.

  6. Generating realistic stock market data for deeper financial research

    A team at Michigan proposed an approach to generating realistic and high-fidelity stock market data to enable broader study of financial markets.

  7. Three faculty earn MIDAS grants to broaden the frontiers of data science

    This round of funding strongly encourages pioneering work with the potential for major expansion.

  8. Best Student Paper Award for work on faster network classification for machine learning

    Comparing graphs the team’s tool is up to an order of magnitude faster than competitive baselines.

  9. CSE faculty bring significant showing to major systems conference

    Researchers designed three new systems to speed up code at several key bottlenecks.

  10. $2M NSF grant to explore data equity systems

    Researchers plan to establish a framework for a national institute that would enable research using sensitive data, while preventing misuse and misinterpretation.