Maya Varma

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PhD Candidate
Stanford University
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about me

I am a PhD candidate in the Department of Computer Science at Stanford University, where I am a member of the Center for Artificial Intelligence in Medicine & Imaging (AIMI). My research focuses on the development of artificial intelligence methods for healthcare challenges, with a particular focus on medical imaging applications. I am grateful to be supported by the Knight-Hennessy Fellowship, the U.S. Department of Defense NDSEG Fellowship, and the Quad Fellowship.

Previously, I graduated with a BS in computer science and a minor in electrical engineering from Stanford University (Class of ‘20). I was recognized as a Frederick E. Terman Scholar, a distinction awarded to the top thirty graduating seniors from the Stanford School of Engineering by GPA. For my senior honors thesis at the Wall Lab, I developed artificial intelligence techniques for improving the diagnosis of autism spectrum disorder. My research was awarded the David M. Kennedy Prize for the best thesis in the School of Engineering and the Ben Wegbreit Prize for the best thesis in computer science.

In high school, I won first place at the Intel Science Talent Search (STS) and presented my research at the White House.

honors & awards
research
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(* indicates equal contribution)


Domino: Discovering Systematic Errors with Cross-Modal Embeddings
International Conference on Learning Representations (ICLR), 2022
ribbon Oral Presentation (Top 1.5% of Submissions) Sabri Eyuboglu*, Maya Varma*, Khaled Saab*, Jean-Benoit Delbrouck, Christopher Lee-Messer, Jared Dunnmon, James Zou, Christopher Ré
[paper] [code]


RaVL: Discovering and Mitigating Spurious Correlations in Fine-Tuned Vision-Language Models
Conference on Neural Information Processing Systems (NeurIPS), 2024
Maya Varma, Jean-Benoit Delbrouck, Zhihong Chen, Akshay Chaudhari, Curtis Langlotz
[paper] [code]


ViLLA: Fine‑Grained Vision‑Language Representation Learning from Real‑World Data
International Conference on Computer Vision (ICCV), 2023
Maya Varma, Jean-Benoit Delbrouck, Sarah Hooper, Akshay Chaudhari, Curtis Langlotz
[paper] [code]


Automated Abnormality Detection in Lower Extremity Radiographs Using Deep Learning
Nature Machine Intelligence, 2019
Maya Varma, Mandy Lu, Rachel Gardner, Jared Dunnmon, Nishith Khandwala, Pranav Rajpurkar, Jin Long, Christopher Beaulieu, Katie Shpanskaya, Li Fei-Fei, Matthew Lungren, Bhavik Patel
[paper] [code] [dataset]


MedVAE: Efficient Automated Interpretation of Medical Images with Large-Scale Generalizable Autoencoders
Medical Imaging with Deep Learning (MIDL), 2025
ribbon Best Paper Award ribbon Oral Presentation Maya Varma*, Ashwin Kumar*, Rogier van der Sluijs*, Sophie Ostmeier, Louis Blankemeier, Pierre Chambon, Christian Bluethgen, Jip Prince, Curtis Langlotz, Akshay Chaudhari
[paper] [code] [models]


Toward Expanding the Scope of Radiology Report Summarization to Multiple Anatomies and Modalities
Association for Computational Linguistics (ACL), 2023
Zhihong Chen*, Maya Varma*, Xiang Wan, Curtis Langlotz, Jean-Benoit Delbrouck*
[paper] [data]


LieRE: Lie Rotational Positional Encodings
International Conference on Machine Learning (ICML), 2025
Sophie Ostmeier, Brian Axelrod, Maya Varma, Michael Moseley, Akshay Chaudhari, Curtis Langlotz
[paper] [code]


Foundation Models in Radiology: What, How, Why, and Why Not
Radiology, 2025
Magdalini Paschali, Zhihong Chen, Louis Blankemeier, Maya Varma, Alaa Youssef, Christian Bluethgen, Curtis Langlotz, Sergios Gatidis, Akshay Chaudhari
[paper]


CheXalign: Preference Fine-Tuning in Chest X-Ray Interpretation Models Without Human Feedback
Association for Computational Linguistics (ACL), 2025
Dennis Hein, Zhihong Chen, Sophie Ostmeier, Justin Xu, Maya Varma, Eduardo Pontes Reis, Arne Edward Michalson, Christian Bluethgen, Hyun Joo Shin, Curtis Langlotz, Akshay S Chaudhari
[paper]


Automated Structured Radiology Report Generation
Association for Computational Linguistics (ACL), 2025
Jean-Benoit Delbrouck, Justin Xu, Johannes Moll, Alois Thomas, Zhihong Chen, Sophie Ostmeier, Asfandyar Azhar, Kelvin Zhenghao Li, Andrew Johnston, Christian Bluethgen, Eduardo Reis, Mohamed Muneer, Maya Varma, Curtis Langlotz
[paper] [project page] [models]


Identification of Social Engagement Indicators Associated With Autism Spectrum Disorder Using a Game-Based Mobile App
Journal of Medical Internet Research, 2022
Maya Varma, Peter Washington, Brianna Chrisman, Aaron Kline, Emilie Leblanc, Kelley Paskov, Nate Stockham, Jae-Yoon Jung, Min Woo Sun, Dennis Wall
[paper]


Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder
Pacific Symposium of Biocomputing, 2019
ribbon Oral Presentation Maya Varma, Kelley Paskov, Jae-Yoon Jung, Brianna Chrisman, Nate Stockham, Peter Washington, Dennis Wall
[paper]