Hannah Schlueter
I am a PhD candidate in EECS at MIT, advised by Caroline Uhler.
Publications
Deep learning-based analysis reveals patient-level cancer therapy trajectories using single-cell PBMC chromatin images
Integrating representation learning, permutation, and optimization to detect lineage-related gene expression patterns
Natural synthetic anomalies for self-supervised anomaly detection and localization
Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil
Comparison of statistical tests and power analysis for phosphoproteomics data
About
My research focuses on machine learning methods for biology and health.
Since 2022
PhD candidate, Electrical Engineering & Computer Science
MIT — advised by Caroline Uhler, supported by the Eric and Wendy Schmidt Center
2021 – 2022
Software engineer
Google — Android video editing tools, open-sourced as part of androidx/media
2017 – 2021
MEng, Mathematics & Computer Science
Imperial College London — research with Bernhard Kainz and Seth Flaxman