Hannah Schlueter

I am a PhD candidate in EECS at MIT, advised by Caroline Uhler. My research focuses on machine learning for biology and health.

Hannah Schlueter

Publications

Schematic: blood sample to PBMC nucleus imaging to patient similarity trajectories
Deep learning-based analysis reveals patient-level cancer therapy trajectories using single-cell PBMC chromatin images
Hannah M. Schlüter*, Trinadha Rao Sornapudi*, Dominic Leiser, Sandra Koller, Zeynep Karavelioglu, Caroline Uhler, G. V. Shivashankar
Manuscript in revision AACR 2026 Abstract
Annotated radial lineage tree after PORCELAN optimization, with the primary tumor and metastatic clades circled
Integrating representation learning, permutation, and optimization to detect lineage-related gene expression patterns
Hannah M. Schlüter, Caroline Uhler
Nature Communications, 2025 News Code Paper
Chest radiographs with ground-truth anomaly masks and predicted anomaly heatmaps
Natural synthetic anomalies for self-supervised anomaly detection and localization
Hannah M. Schlüter, Jeremy Tan, Benjamin Hou, Bernhard Kainz
European Conference on Computer Vision, 2022 Code Paper
Daily hospital admissions and deaths in Manaus, March 2020 to March 2021
Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil
Nuno R. Faria, Thomas A. Mellan, Charles Whittaker, …, Hannah M. Schlüter, … (72 authors)
Science, 2021 Paper
Graphical model of the peptide-level simulation used to benchmark statistical tests
Comparison of statistical tests and power analysis for phosphoproteomics data
Lei J. Ding, Hannah M. Schlüter, Matthew J. Szucs, Rushdy Ahmad, Zheyang Wu, Weifeng Xu
Journal of Proteome Research, 2019 Code Paper

About

CV
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
MEngA four-year integrated master’s, awarded directly from undergraduate entry with no separate bachelor’s along the way., Mathematics & Computer Science Imperial College London — research with Bernhard Kainz and Seth Flaxman