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Zachary C. Lipton

Carnegie Mellon University · US
Area of research
Artificial Intelligence
Research interest
Research interests include Topic Modeling, Natural Language Processing Techniques, Domain Adaptation and Few-Shot Learning, and Adversarial Robustness in Machine Learning.
h-index
45
citations
10,338
works
264
NIH funding
primary concept
email

Recent publications

AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation
Journal of the American Medical Informatics Association 2025cited by 19position: middledoi
The Impact of Differential Feature Under-reporting on Algorithmic Fairness
The 2024 ACM Conference on Fairness, Accountability, and Transparency 2024cited by 2position: contributordoi
From Preference Elicitation to Participatory ML: A Critical Survey & Guidelines for Future Research
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society 2023cited by 25position: contributordoi
A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems 2023cited by 2position: contributordoi
Identifying Game-Based Digital Biomarkers of Cognitive Risk for Adolescent Substance Misuse: Protocol for a Proof-of-Concept Study.
2023cited by 1position: contributordoi
Identifying Game-Based Digital Biomarkers of Cognitive Risk for Adolescent Substance Misuse: Protocol for a Proof-of-Concept Study (Preprint)
2023cited by 0position: contributordoi
Mortality Risk Score for Critically Ill Patients with Viral or Unspecified Pneumonia: Assisting Clinicians with COVID-19 ECMO Planning
Lecture Notes in Computer Science 2020cited by 1position: contributordoi
Born Again Neural Networks
CaltechAUTHORS (California Institute of Technology) 2018cited by 276position: middle
Optimal Thresholding of Classifiers to Maximize F1 Measure
Lecture notes in computer science 2014cited by 573position: firstdoi

Grants

Collaborative Research: RI: Medium: Expert-in-the-Loop Neural Summarization for Consequential Domains
NSF2211955$583,7462022–2026PIRePORTER

Frequent collaborators

· 6 papers (2020–2024)Kammarauche Aneni · Elsevier, Inc.2 papers (2023–2023)Robert McDougal · Kings County Hospital Center2 papers (2023–2023)Youngsun Cho · University of Würzburg2 papers (2023–2023)Ching-Hua Chen · IBM Research2 papers (2023–2023)Lynn Fiellin · Dartmouth College2 papers (2023–2023)Megan G. Jiao · National Institutes of Health2 papers (2023–2023)Isabella Gomati de la Vega · Pontificia Universidad Javeriana2 papers (2023–2023)Saatvik Kher · Pomona College2 papers (2023–2023)Jenny Meyer · Fairfield University2 papers (2023–2023)Feza Anaise Umutoni · Yale University2 papers (2023–2023)Yoav Wald · New York University1 papers (2025–2025)Madhur Nayan · New York University1 papers (2025–2025)Charles Elkan · University of California, San Diego1 papers (2014–2014)Iñigo Urteaga · Columbia University1 papers (2025–2025)Daniel Malinsky · New York University1 papers (2025–2025)Pierre Elias · McGill University Health Centre1 papers (2025–2025)Julia E. Vogt · ETH Zurich1 papers (2025–2025)Noémie Elhadad · New York University1 papers (2025–2025)George Hripcsak · Columbia University Irving Medical Center1 papers (2025–2025)