Meera Krishnamoorthy

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About Me

I am a sixth year Ph.D. student in Computer Science at the University of Michigan. My research focuses on developing accurate machine learning models given resource constraints (i.e. memory and time) and unreliable data (i.e. with time-varying spurious correlations).

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

• June 27, 2024: Presented our work on multiple instance learning with absolute position information at CHIL 2024.
• March 22, 2024: Our comment on the off-label use of AI models in healthcare was published in Nature Medicine.

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Publications

• Meera Krishnamoorthy, Jenna Wiens.
  Cross-Validation for Longitudinal Datasets with Time-Varying Spurious Correlations
  Conference Paper, Under Review


• Meera Krishnamoorthy, Jenna Wiens.
  Multiple Instance Learning with Absolute Position Information
  Conference Paper, Conference on Health, Inference, and Learning (CHIL) (2024)
  [Article]


• 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] [Video Link]

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Contact Information

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