Meera Krishnamoorthy

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About Me

I am a fifth year Ph.D. student in Computer Science at the University of Michigan. My research focuses on developing model architectures, model components, and evaluation techniques to allow for accurate and efficient machine learning in healthcare.

I am advised by Professor Jenna Wiens. Part of my work is funded by a Graduate Fellowship for STEM Diversity.

I received my bachelor's degree from Caltech (major: EE, minor: CS).

In the past, I have developed computational tools for multiple domains, including autonomous systems control, astronomy, and population studies.

Here is my CV.

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News

• April 4, 2024: Our paper defining and developing methods for multiple instance learning with absolute position information was accepted to CHIL 2024.
• March 22, 2024: Our comment on the off-label use of AI models in healthcare was published in Nature Medicine.
• February 2, 2023: I was invited to present our work on AMAISE at the University of Michigan DCMB's Tools and Technology Seminar (Video Link)
• June 9, 2022: Our paper presenting AMAISE (A Machine learning Approach to Index-free Sequence Enrichment) was published in Nature Communications Biology (related blog post, related article).

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Publications

• Meera Krishnamoorthy, Michael W. Sjoding, Jenna Wiens.
  Off-label use of artificial intelligence models in healthcare
  Comment, Nature Medicine (2024)
  [Article]


• Meera Krishnamoorthy, Piyush Ranjan, John R. Erb-Downward, Robert P. Dickson, Jenna Wiens.
  AMAISE: a machine learning approach to index-free sequence enrichment
  Journal Paper, Nature Communications Biology 5, 568 (2022)
  [Article] [PDF] [Blog Post]


• Andrew J. Taylor, Victor D. Dorobantu, Meera Krishnamoorthy , Hoang M. Le, Yisong Yue, Aaron D. Ames.
  A Control Lyapunov Perspective on Episodic Learning via Projection to State Stability
  Conference Paper, IEEE Conference on Decision and Control (2019)
  [PDF]

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Contact Information

meera (at) alumni (dot) caltech (dot) edu