2026 Zachary C. Lipton: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Rising Stars	56	199	199	27	27	190	21318
Computer Science	55	4203	4086	1983	1914	185	18560

Zachary C. Lipton publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Zachary C. Lipton sits on this spectrum.

32 publications 991+

This scientist: 185 publications — 41st percentile

41% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Zachary C. Lipton D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Zachary C. Lipton sits on this spectrum.

30 D-Index 131+

This scientist: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

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

2532
Citations
The Mythos of Model Interpretability: In machine learning, the concept of interpretability is both important and slippery.

Zachary C. Lipton

2126
Citations
The mythos of model interpretability

Zachary C. Lipton

2116
Citations
Learning to Diagnose with LSTM Recurrent Neural Networks

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

1141
Citations
Learning to Diagnose with LSTM Recurrent Neural Networks

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

724
Citations
Optimal thresholding of classifiers to maximize F1 measure

Zachary C. Lipton;Charles Elkan;Balakrishnan Naryanaswamy

646
Citations
Born Again Neural Networks

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

633
Citations
Deep Active Learning for Named Entity Recognition.

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

459
Citations
Learning The Difference That Makes A Difference With Counterfactually-Augmented Data

Divyansh Kaushik;Eduard Hovy;Zachary Lipton

436
Citations
Stochastic Activation Pruning for Robust Adversarial Defense

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

391
Citations
Learning Robust Global Representations by Penalizing Local Predictive Power.

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

292
Citations
Combating Adversarial Misspellings with Robust Word Recognition

Danish Pruthi;Bhuwan Dhingra;Zachary C. Lipton

288
Citations
How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks

Divyansh Kaushik;Zachary C. Lipton

281
Citations
Differential Privacy and Machine Learning: a Survey and Review.

Zhanglong Ji;Zachary Chase Lipton;Charles Elkan

236
Citations
What is the Effect of Importance Weighting in Deep Learning

Jonathon Byrd;Zachary Chase Lipton

231
Citations
Modeling Missing Data in Clinical Time Series with RNNs

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

221
Citations
Detecting and Correcting for Label Shift with Black Box Predictors

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

211
Citations
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems

Unknown

207
Citations
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift

Stephan Rabanser;Stephan Günnemann;Zachary C. Lipton

196
Citations
A User Simulator for Task-Completion Dialogues

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

187
Citations
Troubling Trends in Machine Learning Scholarship

Zachary C. Lipton;Jacob Steinhardt

185
Citations
Learning Robust Representations by Projecting Superficial Statistics Out

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

145
Citations
Dive into Deep Learning.

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

120
Citations
Learning Robust Global Representations by Penalizing Local Predictive Power

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

89
Citations

Frequent Co-Authors

Anima Anandkumar Nvidia (United Kingdom)

Julian McAuley University of California, San Diego

Charles Elkan University of California, San Diego

Saurabh Kumar Garg University of Tasmania

Jianfeng Gao Microsoft (United States)

Alexander J. Smola Amazon (United States)

Jeffrey P. Bigham Carnegie Mellon University

Graham Neubig Carnegie Mellon University

Eric P. Xing Mohamed bin Zayed University of Artificial Intelligence

Byron C. Wallace Northeastern University

External Links

Personal website of Zachary C. Lipton Google Scholar page

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