Rachit Saluja

Hello friend! I am a PhD student at Cornell University, where I am advised by Prof. Mert Sabuncu. Currently, I am based in New York City where I am affiliated with Cornell Tech and the Department of Radiology at Weill Cornell Medical School. My work involoves applying deep learning and computer vision based techniques to multi-modal brain MR images to build computer aided diagnostic systems. I focus on building ML systems that are tightly integrated with the radiologist's workflow. I aim to translate ML based methods and biomedical image analysis to clinical neuroradiology practices.

Previously, I was the lead ML software engineer at Galileo CDS Inc. where I worked with Prof. R Nick Bryan.

I received my Masters in Electrical Engineering from University of Pennsylvania. I did my bachelors in Electrical and Electronics Engineering at PES Institute of Technology, India.

If you have questions about my research or are interested to collabarate with me, please drop me an email!

Email / CV / Google Scholar / Twitter / Github

Publications

	Longitudinal Assessment of Posttreatment Diffuse Glioma Tissue Volumes with Three-dimensional Convolutional Neural Networks Jeffrey D Rudie, Evan Calabrese, Rachit Saluja, David Weiss, John B Colby, Soonmee Cha, Christopher P Hess, Andreas M Rauschecker, Leo P Sugrue, Javier E Villanueva-Meyer. Radiology: Artificial Intelligence, 2022 Article
	Automated multiclass tissue segmentation of clinical brain MRIs with lesions David A Weiss, Rachit Saluja, Long Xie, James C Gee, Leo P Sugrue, Abhijeet Pradhan, R Nick Bryan, Andreas M Rauschecker, Jeffrey D Rudie. NeuroImage: Clinical, 2021 Article
	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 Article
	Multi-disease segmentation of gliomas and white matter hyperintensities in the BraTS data using a 3D convolutional neural network Jeffrey D Rudie, David A Weiss, Rachit Saluja, Andreas M Rauschecker, Jiancong Wang, Leo Sugrue, Spyridon Bakas, John B Colby. Frontiers in Computational Neuroscience, 2019 Article
	Movement science needs different pose tracking algorithms Nidhi Seethapathi, Shaofei Wang, Rachit Saluja, Gunnar Blohm, Konrad P Kording. arXiv preprint , 2019 Article
	Compressive correlation holography Rachit Saluja, GRKS Subrahmanyam, Deepak Mishra, RV Vinu, Rakesh Kumar Singh. Applied Optics, 2017 Article
	Speech Signal Reconstruction using Two-Step Iterative Shrinkage Thresholding Algorithm Rachit Saluja, Susmita Deb. International Journal of Computer Applications, 2016 Article

Scientific Abstracts

	Multi-disease segmentation of glioblastomas and white matter hyperintensities in the BraTS data using a 4D convolutional neural network Jeffrey D Rudie, David A Weiss, Rachit Saluja, Jiancong Wang, Andreas M Rauschecker, Leo Sugrue, Christopher P Hess, Spyridon Bakas, John B Colby. American Society for Functional Neuroradiology (ASFNR) 2019, San Francisco, CA. Selected for oral presentation
	Generative Adversarial Networks Applied to Brain MRIs for Augmentation of Data from Rare Diseases Rachit Saluja, David A Weiss, Jiancong Wang, Long Xie, James Gee, Andreas M Rauschecker, Jeffrey D Rudie. Society for Imaging Informatics in Medicine Annual Meeting (SIIM) 2019, Denver Colorado. Selected for oral presentation
	Automated Multiclass Tissue Segmentation of 3D Brain Magnetic Resonance Images using a 3D U-Net Convolutional Neural Network David A Weiss, Rachit Saluja, Jiancong Wang, Long Xie, James Gee, Andreas M Rauschecker, Jeffrey D Rudie. Society for Imaging Informatics in Medicine Annual Meeting (SIIM) 2019, Denver Colorado. Selected for oral presentation
	Automated segmentation of abnormal signal on T1 MR for 35 diseases entities using a custom 3D U-Net Convolutional Neural Network Raghav Mattay, Jiancong Wang, Long Xie, David A Weiss, Rachit Saluja, James Gee, Andreas M Rauschecker, Jeffrey D Rudie. Society for Imaging Informatics in Medicine Annual Meeting (SIIM) 2019, Denver Colorado. Selected for oral presentation
	Infant sentiment analysis in behavioral qualification Sofiya Lysenko, Nidhi Seethapathi, Claire Chambers, Rachit Saluja, Laura Prosser, Konrad Kording, Michelle J Johnson RESNA Annual Conference 2019, Toronto, Canada.

Teaching

Teaching Assistant, Digital Audio Basics (ESE 150), Spring 2018, University of Pennsylvania

Teaching Assistant, Introduction to Probability and Statistics (ENM 503), Fall 2017, University of Pennsylvania

Cloned from Jon Barron's webpage.