Meera Krishnamoorthy
About Me
I am a final year Ph.D. candidate in Computer Science at the University of Michigan, on track to graduate in June 2025. My research focuses on developing accurate machine learning models given computational resource constraints (e.g., limited memory and time) and dataset shift (due to unstable correlations or selection bias).
I am advised by Professor Jenna Wiens. Part of my work is funded by a National Physical Science Consortium Fellowship.
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.
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.
Publications
- Meera Krishnamoorthy, Michael Sjoding, Jenna Wiens.
Cross-Validation for Longitudinal Datasets with Unstable 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]
Contact Information
meera (at) alumni (dot) caltech (dot) edu