Rachit Saluja
- PhD Student - Cornell University, Cornell Tech & Weill Cornell Medicine
- rs2492 cornell.edu
Hello friend! I am an ECE PhD student at Cornell University, where I am advised by Mert Sabuncu. Currently, I am based in New York City where I am affiliated with Cornell Tech
and Weill Cornell Medicine.
My research focuses on understanding the behavior of medical image segmentation models, with particular emphasis on how their internal representations evolve under different training conditions and data perturbations. I study the learning dynamics of these models and analyze it using information-geometric perspectives.
Additionally, I focus on developing human-in-the-loop pipelines for radiology workflows, with an emphasis on reliable clinical deployment. I have also contributed to several open data initiatives supporting reproducible and accessible medical imaging research.
My research focuses on understanding the behavior of medical image segmentation models, with particular emphasis on how their internal representations evolve under different training conditions and data perturbations. I study the learning dynamics of these models and analyze it using information-geometric perspectives.
Additionally, I focus on developing human-in-the-loop pipelines for radiology workflows, with an emphasis on reliable clinical deployment. I have also contributed to several open data initiatives supporting reproducible and accessible medical imaging research.
Selected Publications
My full list of publications can be found on my Google Scholar.
BackSplit: The Importance of Sub-dividing the Background in Biomedical Lesion Segmentation
Rachit Saluja, Asli Cihangir, Ruining Deng, Johannes C. Paetzold, Fengbei Liu, Mert R. Sabuncu Computer Vision and Pattern Recognition (CVPR) - 2026. [paper]FutureMorph: Toward Predicting Future Deformation Fields in Longitudinal Imaging
Samah Khawaled, Rudolf Leonardus Mirjam Van Herten, Rachit Saluja, Mert R Sabuncu Medical Imaging with Deep Learning (MIDL) - 2026. [paper]The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI
Ahmed W. Moawad*, Anastasia Janas*, Ujjwal Baid*, Divya Ramakrishnan*, Rachit Saluja*, Nader Ashraf*, Leon Jekel*, ... , Spyridon Bakas, Jeffrey D. Rudie, Mariam Aboian Machine Learning for Biomedical Imaging (MELBA) - 2025. [paper] [code] [dataset]Cancer type, stage and prognosis assessment from pathology reports using LLMs
Rachit Saluja, Jacob Rosenthal, Annika Windon, Yoav Artzi, David J Pisapia, Benjamin L Liechty, Mert R Sabuncu Scientific Reports - 2025. [paper] [code]BrainMorph: A Foundational Keypoint Model for Robust and Flexible Brain MRI Registration
Alan Q Wang, Rachit Saluja, Heejong Kim, Xinzi He, Adrian Dalca, Mert R Sabuncu Machine Learning for Biomedical Imaging (MELBA) - 2025. [paper] [code]The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI
Maria Correia de Verdier*, Rachit Saluja*, Louis Gagnon, Dominic LaBella, Ujjwall Baid, ... , Spyridon Bakas, Evan Calabrese, Jeffrey D. Rudie arXiv - 2024. [paper] [dataset]A Framework for Interpretability in Machine Learning for Medical Imaging
Alan Q Wang, Batuhan K Karaman, Heejong Kim, Jacob Rosenthal, Rachit Saluja, Sean I Young, Mert R Sabuncu IEEE Access - 2024. [paper]Computer vision to automatically assess infant neuromotor risk
Claire Chambers, Nidhi Seethapathi, Rachit Saluja, Helen Loeb, Samuel R Pierce, Daniel K Bogen, Laura Prosser, Michelle J Johnson, Konrad P Kording IEEE Transactions on Neural Systems and Rehabilitation Engineering - 2020. [paper] [code] [dataset]