About the Lab

Led by David Sontag, the Clinical Machine Learning Group is interested in advancing machine learning and artificial intelligence, and using these techniques to advance health care.

Broadly, we have two goals:

  • Clinical: To truly make a difference in health care, we need to create algorithms that are useful for solving real clinical problems.
  • Machine learning: We need rigorous solutions, which can pave the way for safe deployment of machine learning in high-stakes settings like healthcare.

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Team

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David Sontag

Professor of EECS

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Michael Oberst

PhD Student

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Monica Agrawal

PhD Student

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Zeshan Hussain

MD/PhD Student

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Christina X Ji

PhD Student

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Chandler Squires

PhD Student

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Hussein Mozannar

PhD Student

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Hunter Lang

PhD Student

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Shannon Shen

PhD Student

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Ilker Demirel

PhD Student

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Elizabeth Bondi-Kelly

Postdoctoral Fellow

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Alejandro Buendia

Research Engineer

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Edward De Brouwer

Visiting student

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Jimin Lee

Undergraduate Researcher

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Niklas Mannhardt

Master’s student

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Penny Brant

Undergraduate Researcher

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Sharon Jiang

Master’s student

Recent Publications

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Sample Efficient Learning of Predictors that Complement Humans

One of the goals of learning algorithms is to complement and reduce the burden on human decision makers. The expert deferral setting …

Leveraging Time Irreversibility with Order-Contrastive Pre-training

Label-scarce, high-dimensional domains such as healthcare present a challenge for modern machine learning techniques. To overcome the …

Single Cell Characterization of Myeloma and its Precursor Conditions Reveals Transcriptional Signatures of Early Tumorigenesis