World's Best Scientists 2026 revealed!
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Rising Stars
2025

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Rising Stars

D-Index
56
Citations
21318
World Ranking
199
National Ranking
27

Computer Science

D-Index
55
Citations
18560
World Ranking
4203
National Ranking
1982

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Zachary C. Lipton is affiliated with Carnegie Mellon University in the United States. Their research primarily spans the broad field of Computer Science, with a significant focus on Artificial Intelligence. Other notable subfields include Computer Vision and Pattern Recognition, Management Science and Operations Research, Safety Research, and Statistics and Probability.

The main topics of their academic work cover a diverse range of subjects within AI and machine learning. These topics include:

  • Topic Modeling
  • Domain Adaptation and Few-Shot Learning
  • Natural Language Processing Techniques
  • Ethics and Social Impacts of AI
  • Explainable Artificial Intelligence (XAI)
  • Advanced Bandit Algorithms Research
  • Adversarial Robustness in Machine Learning

Lipton has a considerable publication record, featuring contributions in various venues. The most frequent publication outlets include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the AAAI/ACM Conference on AI Ethics and Society
  • Annals of Surgical Oncology
  • Communications of the ACM

Their recent papers reflect interdisciplinary studies combining deep learning, medical imaging, and explainability in AI. Notable recent publications include:

  • "Estimating brain age based on a uniform healthy population with deep learning and structural magnetic resonance imaging" (2020) published in Neurobiology of Aging
  • "Dive into Deep Learning" (2021) published in arXiv (Cornell University)
  • "An open repository of real-time COVID-19 indicators" (2021) published in Proceedings of the National Academy of Sciences
  • "Evaluating Explanations: How Much Do Explanations from the Teacher Aid Students?" (2022) published in Transactions of the Association for Computational Linguistics
  • "Symbolic Music Generation with Transformer-GANs" (2021) published in Proceedings of the AAAI Conference on Artificial Intelligence

Collaboration is a significant aspect of their work, with frequent co-authors including:

  • Saurabh Garg
  • Liu Leqi
  • Sivaraman Balakrishnan
  • Shantanu Gupta
  • Pratyush Maini

Best Publications

  • A Critical Review of Recurrent Neural Networks for Sequence Learning

    Zachary C. Lipton;John Berkowitz;Charles Elkan

  • The Mythos of Model Interpretability: In machine learning, the concept of interpretability is both important and slippery.

    Zachary C. Lipton

  • The mythos of model interpretability

    Zachary C. Lipton

  • Learning to Diagnose with LSTM Recurrent Neural Networks

    Zachary C. Lipton;David C. Kale;Charles Elkan;Randall Wetzell

  • Learning to Diagnose with LSTM Recurrent Neural Networks

    Zachary C. Lipton;David C. Kale;Charles Elkan;Randall Wetzel

  • Optimal thresholding of classifiers to maximize F1 measure

    Zachary C. Lipton;Charles Elkan;Balakrishnan Naryanaswamy

  • Born Again Neural Networks

    Tommaso Furlanello;Zachary Chase Lipton;Michael Tschannen;Laurent Itti

  • Deep Active Learning for Named Entity Recognition.

    Yanyao Shen;Hyokun Yun;Zachary C. Lipton;Yakov Kronrod

  • Learning The Difference That Makes A Difference With Counterfactually-Augmented Data

    Divyansh Kaushik;Eduard Hovy;Zachary Lipton

  • Stochastic Activation Pruning for Robust Adversarial Defense

    Guneet S. Dhillon;Kamyar Azizzadenesheli;Zachary C. Lipton;Jeremy D. Bernstein

  • Learning Robust Global Representations by Penalizing Local Predictive Power.

    Haohan Wang;Songwei Ge;Eric P. Xing;Zachary C. Lipton

  • Combating Adversarial Misspellings with Robust Word Recognition

    Danish Pruthi;Bhuwan Dhingra;Zachary C. Lipton

  • How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks

    Divyansh Kaushik;Zachary C. Lipton

  • Differential Privacy and Machine Learning: a Survey and Review.

    Zhanglong Ji;Zachary Chase Lipton;Charles Elkan

  • What is the Effect of Importance Weighting in Deep Learning

    Jonathon Byrd;Zachary Chase Lipton

  • Modeling Missing Data in Clinical Time Series with RNNs

    Zachary C. Lipton;David C. Kale;Randall Wetzel

  • Detecting and Correcting for Label Shift with Black Box Predictors

    Zachary C. Lipton;Yu-Xiang Wang;Alexander J. Smola

  • BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems

    Unknown

  • Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift

    Stephan Rabanser;Stephan Günnemann;Zachary C. Lipton

  • A User Simulator for Task-Completion Dialogues

    Xiujun Li;Zachary C. Lipton;Bhuwan Dhingra;Lihong Li

  • Troubling Trends in Machine Learning Scholarship

    Zachary C. Lipton;Jacob Steinhardt

  • Learning Robust Representations by Projecting Superficial Statistics Out

    Haohan Wang;Zexue He;Zachary C. Lipton;Eric P. Xing

  • Dive into Deep Learning.

    Aston Zhang;Zachary C. Lipton;Mu Li;Alexander J. Smola

  • Learning Robust Global Representations by Penalizing Local Predictive Power

    Haohan Wang;Songwei Ge;Zachary C. Lipton;Eric P. Xing

Frequent Co-Authors

Anima Anandkumar
Anima Anandkumar Nvidia (United Kingdom)
Julian McAuley
Julian McAuley University of California, San Diego
Charles Elkan
Charles Elkan University of California, San Diego
Saurabh Kumar Garg
Saurabh Kumar Garg University of Tasmania
Jianfeng Gao
Jianfeng Gao Microsoft (United States)
Alexander J. Smola
Alexander J. Smola Amazon (United States)
Jeffrey P. Bigham
Jeffrey P. Bigham Carnegie Mellon University
Graham Neubig
Graham Neubig Carnegie Mellon University
Eric P. Xing
Eric P. Xing Mohamed bin Zayed University of Artificial Intelligence
Byron C. Wallace
Byron C. Wallace Northeastern University

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