honors & awards

• 2025 Best Paper Award, MIDL Conference
• 2024 Rising Star in Electrical Engineering and Computer Science (Awarded by MIT)
• 2024 Rising Star in Data Science (Awarded by UC San Diego, Stanford University, and University of Chicago)
• 2024 Rising Star in Machine Learning (Awarded by University of Maryland College Park)
• Graduate Fellowships:
  • 2024-2025 Quad Fellowship
  • 2020-2025 Knight-Hennessy Scholar
  • 2020-2023 National Defense Science and Engineering Graduate (NDSEG) Fellowship
  • 2020 NSF Graduate Research Fellowship (GRFP) Recipient
• Undergraduate Honors Thesis Awards:
  • 2020 David M. Kennedy Prize (awarded to the single best thesis in engineering and applied sciences)
  • 2020 Ben Wegbreit Prize for Top Computer Science Thesis
  • 2020 Firestone Medal for Excellence in Undergraduate Research (awarded to top 10% of theses)
• 2020 Frederick E. Terman Scholar (awarded to top 30 graduating seniors from the Stanford School of Engineering by GPA)
• 2019 Barry S. Goldwater Scholar
• 2016 Intel Science Talent Search (STS) First Place Award
• 2016 Davidson Fellow
• 2016 White House Science Fair Presenter
• 2016 Coca Cola Scholar
• 2016 Dr. Bart Kamen Memorial Scholar (FIRST Robotics)
• Lists: Teen Vogue 21 Under 21, Huffington Post 20 Under 20, HerCampus Magazine 22 Under 22 Most Inspiring College Women, Popular Mechanics 15 Young Innovators, National Gallery for America’s Young Inventors

  
  

research

View Mode:

Selected Works All Works

(* indicates equal contribution)

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Domino: Discovering Systematic Errors with Cross-Modal Embeddings

International Conference on Learning Representations (ICLR), 2022
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]

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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]

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TRoVe: Discovering Error-Inducing Static Feature Biases in Temporal Vision-Language Models

Conference on Neural Information Processing Systems (NeurIPS), 2025
Maya Varma, Jean-Benoit Delbrouck, Sophie Ostmeier, Akshay Chaudhari, Curtis Langlotz
[paper] [code]

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MedVAE: Efficient Automated Interpretation of Medical Images with Large-Scale Generalizable Autoencoders

Medical Imaging with Deep Learning (MIDL), 2025
Best Paper Award 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]

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CheXagent: A Vision-Language Foundation Model to Enhance Efficiency of Chest X-Ray Interpretation

Technical Report, 2024
Zhihong Chen*, Maya Varma*, Justin Xu, Magdalini Paschali, Dave Van Veen, Andrew Johnston,..., Sergios Gatidis, Jean-Benoit Delbrouck, Akshay Chaudhari, Curtis Langlotz
[paper] [code] [models]

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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]

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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] [data]

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SMMILE: An Expert‑Driven Benchmark for Multimodal Medical In‑Context Learning

Conference on Neural Information Processing Systems (NeurIPS), 2025
Melanie Rieff*, Maya Varma*, Ossian Rabow, Subathra Adithan, Julie Kim, Ken Chang, Hannah Lee, Nidhi Rohatgi, Christian Bluethgen, Mohamed S. Muneer, Jean-Benoit Delbrouck, Michael Moor
[paper] [code] [data]

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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]

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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]

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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]

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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]

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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]

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Thesis

• Undergraduate Honors Thesis: Artificial Intelligence Methods for Improved Diagnosis of Autism Spectrum Disorder
  Maya Varma, 2020
  Department of Computer Science, Stanford University
  David M. Kennedy Prize for Best Thesis, School of Engineering
  Ben Wegbreit Prize for Best Thesis, Department of Computer Science
  Firestone Medal for Excellence in Undergraduate Research

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Patents

• Intelligent traffic alerting and control system
  Maya Varma, 2015
  US Patent 9035797

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Technical Reports

• CheXagent: A vision-language foundation model to enhance efficiency of chest x-ray interpretation
  Z Chen*, M Varma*, J Xu, M Paschali, D Van Veen, A Johnston, A Youssef, L Blankemeier, C Bluethgen, S Altmayer, JMJ Valanarasu, MSE Muneer, EP Reis, JP Cohen, C Olsen, TM Abraham, EB Tsai, CF Beaulieu, J Jitsev, S Gatidis, JB Delbrouck, AS Chaudhari, C Langlotz
  2024

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Publications

2026

• From detection to mitigation: Addressing bias in deep learning models for chest x-ray diagnosis
  C Mottez, L Fay, M Varma, S Ostmeier, and C Langlotz
  Pacific Symposium of Biocomputing (PSB), 2026

2025

• TRoVe: Discovering error-inducing static feature biases in temporal vision-language models
  M Varma, JB Delbrouck, S Ostmeier, A Chaudhari, C Langlotz
  Conference on Neural Information Processing Systems (NeurIPS), 2025

• SMMILE: An expert‑driven benchmark for multimodal medical in‑context learning
  M Rieff*, M Varma*, O Rabow, S Adithan, J Kim, K Chang, H Lee, N Rohatgi, C Bluethgen, MS Muneer, JB Delbrouck, M Moor
  Conference on Neural Information Processing Systems (NeurIPS), 2025

• CheXalign: Preference fine-tuning in chest X-ray interpretation models without human feedback
  D Hein, Z Chen, S Ostmeier, J Xu, M Varma, E Reis, A Michalson, C Bluethgen, H Shin, C Langlotz, A Chaudhari
  Association for Computational Linguistics (ACL), 2025

• Automated structured radiology report generation
  JB Delbrouck, J Xu, J Moll, A Thomas, Z Chen, S Ostmeier, A Azhar, K Li, A Johnston, C Bluethgen, E Reis, M Muneer, M Varma, C Langlotz
  Association for Computational Linguistics (ACL), 2025

• LieRE: Lie rotational positional encodings
  S Ostmeier, B Axelrod, M Varma, M Moseley, C Langlotz, A Chaudhari
  International Conference on Machine Learning (ICML), 2025

• MedVAE: Efficient automated interpretation of medical images with large-scale generalizable autoencoders
  M Varma*, A Kumar*, R van der Sluijs*, S Ostmeier, L Blankemeier, P Chambon, C Bluethgen, J Prince, C Langlotz, A Chaudhari
  Medical Imaging with Deep Learning (MIDL), 2025
  Best Paper Award Oral Presentation

• Using deep feature distances for evaluating the perceptual quality of MR image reconstructions
  P Adamson, A Desai, J Dominic, M Varma, C Bluethgen, J Wood, A Syed, R Boutin, K Stevens, S Vasanawala, J Pauly, B Gunel, A Chaudhari
  Magnetic Resonance in Medicine, 2025

• Foundation models in radiology: What, how, why, and why not
  M Paschali, Z Chen, L Blankemeier, M Varma, A Youssef, C Bluethgen, C Langlotz, S Gatidis, A Chaudhari
  Radiology, 2025

2024

• RaVL: Discovering and mitigating spurious correlations in fine-tuned vision-language models
  M Varma, JB Delbrouck, Z Chen, A Chaudhari, C Langlotz
  Conference on Neural Information Processing Systems (NeurIPS), 2024

• GREEN: Generative radiology report evaluation and error notation
  S Ostmeier, J Xu, Z Chen, M Varma, L Blankemeier, C Bluethgen, AE Michalson, M Moseley, C Langlotz, AS Chaudhari, JB Delbrouck
  Findings of EMNLP, 2024

• RadGraph-XL: A large-scale expert-annotated dataset for entity and relation extraction from radiology reports
  JB Delbrouck, P Chambon, Z Chen, M Varma, A Johnston, L Blankemeier, DV Veen, T Bui, S Truong, C Langlotz
  Findings of the Association for Computational Lingustics (ACL), 2024

2023

• ViLLA: Fine‑grained vision‑language representation learning from real‑world data
  M Varma, JB Delbrouck, S Hooper, A Chaudhari, C Langlotz
  International Conference on Computer Vision (ICCV), 2023

• Toward expanding the scope of radiology report summarization to multiple anatomies and modalities
  Z Chen*, M Varma*, X Wan, C Langlotz, JB Delbrouck*
  Association for Computational Linguistics (ACL), 2023

• Graph representations and algorithms in biomedicine
  B Chrisman, M Varma, S Maleki, M Brbic, C Joslyn, M Zitnik
  Pacific Symposium of Biocomputing, 2023

2022

• ViLMedic: A framework for research at the intersection of vision and language in medical AI
  JB Delbrouck, K Saab, M Varma, S Eyuboglu, P Chambon, J Dunnmon, J Zambrano, A Chaudhari, C Langlotz
  Association for Computational Linguistics (ACL), 2022

• Improved digital therapy for developmental pediatrics using domain-specific artificial intelligence
  P Washington, H Kalantarian, J Kent, A Husic, A Kline, E Leblanc, C Hou, OC Mutlu, K Dunlap, Y Penev, M Varma, NT Stockham, B Chrisman, K Paskov, MW Sun, JY Jung, C Voss, N Haber, DP Wall
  JMIR Pediatrics and Parenting, 2022

• Domino: Discovering systematic errors with cross-modal embeddings
  S Eyuboglu*, M Varma*, K Saab*, JB Delbrouck, C Lee-Messer, J Dunnmon, J Zou, C Ré
  International Conference on Learning Representations (ICLR), 2022
  Oral Presentation (Top 1.5% of Submissions)

• Identification of social engagement indicators associated with autism spectrum disorder using a game-based mobile app
  M Varma, P Washington, B Chrisman, A Kline, E Leblanc, K Paskov, N Stockham, JY Jung, MW Sun, DP Wall
  Journal of Medical Internet Research, 2022

2021

• Improved detection of disease-associated gut microbes using 16S sequence-based biomarkers
  BS Chrisman, KM Paskov, N Stockham, JY Jung, M Varma, PY Washington, C Tataru, S Iwai, TZ DeSantis, M David, DP Wall
  BMC Bioinformatics, 2021

• Cross-domain data integration for named entity disambiguation in biomedical text
  M Varma, L Orr, S Wu, M Leszczynski, X Ling, C Ré
  Findings of EMNLP, 2021

• A maximum flow-based network approach for identification of stable noncoding biomarkers associated with the multigenic neurological condition, autism
  M Varma, KM Paskov, BS Chrisman, MW Sun, JY Jung, NT Stockham, PY Washington, DP Wall
  BMC BioData Mining, 2021

• Estimating sequencing error rates using families
  K Paskov, JY Jung, B Chrisman, NT Stockham, P Washington, M Varma, MW Sun, DP Wall
  BMC BioData Mining, 2021

• Crowdsourced privacy-preserved feature tagging of short home videos for machine learning ASD detection
  P Washington, Q Tariq, E Leblanc, B Chrisman, K Dunlap, A Kline, H Kalantarian, Y Penev, K Paskov, C Voss, N Stockham, M Varma, A Husic, J Kent, N Haber, T Winograd, DP Wall
  Scientific Reports, 2021

• Indels in SARS-CoV-2 occur at template-switching hotspots
  BS Chrisman, K Paskov, NT Stockham, K Tabatabaei, JY Jung, P Washington, M Varma, MW Sun, S Maleki, DP Wall
  BMC BioData Mining, 2021

• Selection of trustworthy crowd workers for telemedical diagnosis of pediatric autism spectrum disorder
  P Washington, E Leblanc, K Dunlap, Y Penev, M Varma, JY Jung, B Chrisman, MW Sun, N Stockham, KM Paskov, H Kalantarian, C Voss, N Haber, DP Wall
  Pacific Symposium of Biocomputing, 2021

2020

• Feature replacement methods enable reliable home video analysis for machine learning detection of autism
  E Leblanc, P Washington, M Varma, K Dunlap, Y Penev, A Kline, DP Wall
  Scientific Reports, 2020

• Game theoretic centrality: a novel approach to prioritize disease candidate genes by combining biological networks with the Shapley value
  MW Sun, S Moretti, KM Paskov, NT Stockham, M Varma, BS Chrisman, PY Washington, JY Jung, DP Wall
  BMC Bioinformatics, 2020

• Precision telemedicine through crowdsourced machine learning: testing variability of crowd workers for video-based autism feature recognition
  P Washington, E Leblanc, K Dunlap, Y Penev, A Kline, K Paskov, MW Sun, B Chrisman, N Stockham, M Varma, C Voss, N Haber, DP Wall
  Journal of Personalized Medicine, 2020

• Feature selection and dimension reduction of social autism data
  P Washington, KM Paskov, H Kalantarian, N Stockham, C Voss, A Kline, R Patnaik, B Chrisman, M Varma, Q Tariq, K Dunlap, J Schwartz, N Haber, DP Wall
  Pacific Symposium of Biocomputing, 2020

2019

• Data-driven diagnostics and the potential of mobile artificial intelligence for digital therapeutic phenotyping in computational psychiatry
  P Washington, N Park, P Srivastava, C Voss, A Kline, M Varma, Q Tariq, H Kalantarian, J Schwartz, R Patnaik, N Haber, DP Wall
  Biological Psychiatry, 2019

• Automated abnormality detection in lower extremity radiographs using deep learning
  M Varma, M Lu, R Gardner, J Dunnmon, N Khandwala, P Rajpurkar, J Long, C Beaulieu, K Shpanskaya, L Fei-Fei, MP Lungren, BN Patel.
  Nature Machine Intelligence, 2019

• Coalitional game theory facilitates identification of non-coding variants associated with autism
  MW Sun, A Gupta, M Varma, KM Paskov, JY Jung, NT Stockham, DP Wall
  Biomedical Informatics Insights, 2019

• Validity of online screening for autism: crowdsourcing study comparing paid and unpaid diagnostic tasks
  P Washington, H Kalantarian, Q Tariq, J Schwartz, K Dunlap, B Chrisman, M Varma, M Ning, A Kline, N Stockham, K Paskov, C Voss, N Haber, DP Wall
  Journal of Medical Internet Research, 2019

• Outgroup machine learning approach identifies single nucleotide variants in noncoding DNA associated with autism spectrum disorder
  M Varma, KM Paskov, JY Jung, B Chrisman, NT Stockham, P Washington, DP Wall
  Pacific Symposium on Biocomputing, 2019
  Oral Presentation

2018

• Analysis of sex and recurrence ratios in simplex and multiplex autism spectrum disorder implicates sex-specific alleles as inheritance mechanism
  B Chrisman, M Varma, P Washington, K Paskov, N Stockham, JY Jung, DP Wall
  IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018
   

2017

• Cross-disorder comparative analysis of comorbid conditions reveals novel autism candidate genes
  L Diaz-Beltran, FJ Esteban, M Varma, A Ozturk, M David, DP Wall
  BMC Genomics, 2017

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Workshop Papers

• MedVAL: Toward expert-level medical text validation with language models
  A Aali, V Bikia, M Varma, N Chiou, S Ostmeier, A Singhvi, M Paschali, A Kumar, A Johnston, K Amador-Martinez, EJP Guerrero, PNC Rivera, S Gatidis, C Bluethgen, EP Reis, E Zandee van Rilland, P Hosamani, KR Keet, M Go, E Ling, DB Larson, C Langlotz, R Daneshjou, J Hom, S Koyejo, E Alsentzer, AS Chaudhari
  Workshop on GenAI for Health @ NeurIPS, 2025
  Oral Presentation

• TRoVe: Discovering error-inducing static feature biases in temporal vision-language models
  M Varma, JB Delbrouck, S Ostmeier, A Chaudhari, C Langlotz
  Workshop on Reliable and Responsible Foundation Models @ ICML, 2025

• Overview of the first shared task on clinical text generation: RRG24 and Discharge Me
  J Xu, Z Chen, A Johnston, L Blankemeier, M Varma, J Hom, WJ Collins, A Modi, R Lloyd, B Hopkins, C Langlotz, JB Delbrouck
  Workshop on Biomedical Natural Language Processing @ ACL, 2024
  Oral Presentation

• CheXagent: Towards a foundation model for chest x-ray interpretation
  Z Chen*, M Varma*, JB Delbrouck*, M Paschali, L Blankemeier, DV Veen, JMJ Valanarasu, A Youssef, JP Cohen, EP Reis, E Tsai, A Johnston, C Olsen, TM Abraham, S Gatidis, AS Chaudhari, C Langlotz
  AAAI 2024 Spring Symposium on Clinical Foundation Models, 2024
  Oral Presentation

• Diagnostically lossless compression of medical images
  R van der Sluijs*, M Varma*, J Prince, C Langlotz, A Chaudhari
  Workshop on Neural Compression @ ICML, 2023

• Overview of the RadSum23 shared task on multi‑modal and multi‑anatomical radiology report summarization
  JB Delbrouck, M Varma, P Chambon, C Langlotz
  Workshop on Biomedical Natural Language Processing @ ACL, 2023
  Oral Presentation

• Toward expanding the scope of radiology report summarization to multiple anatomies and modalities
  JB Delbrouck, M Varma, C Langlotz
  Extended Abstract, Machine Learning for Health (ML4H) Symposium, 2022

• Determining question-answer plausibility in crowdsourced datasets using multi-task learning
  R Gardner, M Varma, C Zhu, R Krishna
  Workshop on Noisy User-generated Text (W-NUT) @ EMNLP, 2020