Taylor Joren
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    • Concept bottleneck language models for protein design
    • Guided Generation of B-cell Receptors with Conditional Walk-Jump Sampling
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    • Prediction of single-cell RNA expression profiles in live cells by Raman microscopy with Raman2RNA
    • Cramming protein language model training in 24 GPU hours
    • Surface ID: a geometry-aware system for protein molecular surface comparison
    • Interpreting Raman spectra using machine learning: towards a non-invasive method of characterizing single cells
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Interpreting Raman spectra using machine learning: towards a non-invasive method of characterizing single cells

Feb 1, 2021·
Taylor Joren
Taylor Joren
· 0 min read
Thesis
Type
Thesis
Publication
Masters Thesis, Massachusetts Institute of Technology
Last updated on Jul 12, 2026
Taylor Joren
Authors
Taylor Joren
Senior Machine Learning Scientist
← Surface ID: a geometry-aware system for protein molecular surface comparison Apr 1, 2023
Simulation-assisted machine learning Oct 1, 2019 →

© 2026 Taylor Joren. This work is licensed under CC BY NC ND 4.0

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