Zachary Lipton
Also known as Zachary Chase Lipton, Zack Lipton
Zachary Lipton studies machine learning for healthcare and natural language processing, and he co-authored the open-source book Dive into Deep Learning. Born in 1985, the jazz saxophonist from New Rochelle, New York completed undergraduate studies at Columbia University and, in 2017, a computer-science doctorate at the University of California, San Diego. In May 2015 he published a critical review of recurrent neural networks with John Berkowitz and Charles Elkan, and in 2016 he published The Mythos of Model Interpretability and launched the Approximately Correct blog. While an assistant professor of business technologies at Carnegie Mellon's Tepper School, he received an Amazon Web Services Machine Learning Research Award in May 2019 for work on breast cancer diagnosis. As of October 2026, he is the Raj Reddy Associate Professor of Machine Learning at Carnegie Mellon, director of the Approximately Correct Machine Intelligence lab, and cofounder and chief technology officer at Abridge.
- Now at
- Carnegie Mellon University and Abridge
- Works
- 232
- Citations
- 15,400
- h-index
- 47
Publication numbers from OpenAlex, as of 17 October 2026.
Timeline
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1985–2017
A doctorate after Columbia
Born in 1985, he is a jazz saxophonist from New Rochelle, New York. He completes undergraduate studies at Columbia University and, in 2017, a computer-science PhD at the University of California, San Diego. Charles Elkan and Julian McAuley advise the dissertation Learning from Temporally-Structured Human Activities Data.
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May 2015
A review of recurrent networks
In May 2015 he, John Berkowitz, and Charles Elkan publish A Critical Review of Recurrent Neural Networks for Sequence Learning.
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2016
Interpretability and a public blog
He publishes The Mythos of Model Interpretability and presents it at the 2016 ICML Workshop on Human Interpretability in Machine Learning. He also launches the Approximately Correct blog in 2016 to bridge technical and social perspectives on machine learning.
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May 2019
An AWS research award
In May 2019 he is an assistant professor of business technologies at the Tepper School and receives the Amazon Web Services Machine Learning Research Award, with a $100,000 gift, for work on the accuracy of breast cancer diagnosis.
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February 2023
Dive into Deep Learning
With Aston Zhang, Mu Li, and Alexander J. Smola, he co-authors Dive into Deep Learning, an open-source book drafted in Jupyter notebooks. In February 2023 a Cambridge University Press edition is forthcoming.
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2023
Abridge chief scientific officer
Abridge appoints him chief scientific officer in February 2023. He is an assistant professor of machine learning at Carnegie Mellon, has experience as a research scientist at Amazon AI, and has been a long-time advisor on the company's clinical conversations. The company welcomes him as chief technology officer in 2023.
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As of October 2026
Professor and Abridge CTO
He is the Raj Reddy Associate Professor of Machine Learning at Carnegie Mellon University, where he directs the Approximately Correct Machine Intelligence lab. His research covers healthcare and natural language processing. He is cofounder and chief technology officer at Abridge, whose product listens to doctor-patient conversations and drafts after-visit notes.
Sources and credits
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- Zachary Lipton - Wikipedia
- [1506.00019] A Critical Review of Recurrent Neural Networks for Sequence Learning
- [1606.03490] The Mythos of Model Interpretability
- Zachary Lipton | Associate Professor, Machine Learning, CMU
- Zachary Lipton - Software and Societal Systems Department - School of Computer Science - Carnegie Mellon University
- Personal Mention - The Piper - Carnegie Mellon University
- Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
- News - Carnegie Mellon University
- Amazon AI Researcher Zachary Lipton Joins Abridge as Chief Scientific Officer
- Key Highlights and Achievements | A Year of Abridge
- Zachary Lipton, PhD | Abridge Blog Author