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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Irene Chen

PhD Student

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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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Yuria Utsumi

Master’s student

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Ming-Chieh Shih

Postdoctoral Fellow

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Ahmed Alaa

Postdoctoral Associate

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Mercy Asiedu

Postdoctoral Fellow

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Nikolaj Thams

Visiting Student

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Alejandro Buendia

Research Engineer

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Daniel Ajayi

Undergraduate Researcher

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Jimin Lee

Undergraduate Researcher

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Katie Liu

Undergraduate Researcher

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Kyle Liu

Undergraduate Researcher

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Niklas Mannhardt

Undergraduate Researcher

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Sharon Jiang

Undergraduate Researcher

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Sol Rodriguez

Undergraduate Researcher

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Stefan Hegselmann

Visiting Student

Recent Publications

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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

Teaching Humans When To Defer to a Classifier via Exemplars

Expert decision makers are starting to rely on data-driven automated agents to assist them with various tasks. For this collaboration …