Digvijay Kumar Yarlagadda


I am a PhD student in the Tri-Institutional Program in Computational Biology & Medicine at Cornell University, Sloan Kettering Institute, and Rockefeller University. I am jointly supervised by Joan Massagué and Christina Leslie.

Previously, I was part of Thomas Fuchs Lab at Memorial Sloan-Kettering Cancer Center where I worked on developing computer vision and deep learning algorithms for computational pathology.

I have a master's degree in computer science from University of Missouri-Kansas City, where I was advised by Praveen Rao and funded by dean's international scholar award. I also took on roles to launch products at early stage startups AgShift, Strayos and Zenjoi.

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Research

I'm interested in computer vision and deep learning research, with applications in biology and medicine.

Discrete Representation Learning for Modeling Imaging-Based Spatial Transcriptomics Data
Dig Vijay Kumar Yarlagadda, Joan Massagué, Christina Leslie
International Conference on Computer Vision (ICCV) Bioimage Computing 2023  

Discrete representations can capture multi-scale spatial structures in spatial transcriptomics data.

A system for one-shot learning of cervical cancer cell classification in histopathology images
Dig Vijay Kumar Yarlagadda, Praveen Rao, Deepthi Rao, Ossama Tawfik
SPIE Medical Imaging, 2019  

Memory augmentated neural networks provides a better way to rememeber rare occurances of cancer in histology images.

Deep Multi-Magnification Networks for Multi-Class Breast Cancer Image Segmentation
David Joon Ho, Dig Vijay Kumar Yarlagadda, Timothy M. D'Alfonso, Matthew G. Hanna, Anne Grabenstetter, Peter Ntiamoah, Edi Brogi, Lee K. Tan, Thomas J. Fuchs
Computerized Medical Imaging and Graphics 2021

Segmentation of histopathology images can be improved by training on patches from multiple magnifications.

Scalable storage of whole slide images and fast retrieval of tiles using Apache Spark
Daniel Lopez, Dig Vijay Kumar Yarlagadda, Praveen Rao, Ossama Tawfik, Deepthi Rao
SPIE Medical Imaging, 2018

Using Z-indexing creates more effictive platform for WSI storage and retrieval.

Overcoming an Annotation Hurdle: Digitizing Pen Annotations from Whole Slide Images
Peter J Schüffler*, Dig Vijay Kumar Yarlagadda*, Chad Vanderbilt, Thomas J Fuchs
Journal of pathology informatics, 2021

Computer vision algorithm to extract annotations on large molecular pathology datasets.

Beyond Classification: Whole Slide Tissue Histopathology Analysis By End-To-End Part Learning
Chensu Xie, Hassan Muhammad, Chad M. Vanderbilt, Raul Caso, Dig Vijay Kumar Yarlagadda , Gabriele Campanella, Thomas J. Fuchs
Medical Imaging with Deep Learning (MIDL), 2020  

End to end part learning achieves state-of-the-art performance for multi-label prediction.

(Re) Defining the high-power field for digital pathology
David Kim, Liron Pantanowitz, Peter Schüffler, Dig Vijay Kumar Yarlagadda, Orly Ardon, Victor E Reuter, Meera Hameed, David S Klimstra, Matthew G Hanna
Journal of Pathology Informatics, 2020  

Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center
Peter J Schüffler, Luke Geneslaw, Dig Vijay Kumar Yarlagadda, Matthew G Hanna, Jennifer Samboy, Evangelos Stamelos, Chad Vanderbilt, John Philip, Marc-Henri Jean, Lorraine Corsale, Allyne Manzo, Neeraj HG Paramasivam, John S Ziegler, Jianjiong Gao, Juan C Perin, Young Suk Kim, Umeshkumar K Bhanot, Michael HA Roehrl, Orly Ardon, Sarah Chiang, Dilip D Giri, Carlie S Sigel, Lee K Tan, Melissa Murray, Christina Virgo, Christine England, Yukako Yagi, S Joseph Sirintrapun, David Klimstra, Meera Hameed, Victor E Reuter, Thomas J Fuchs
Journal of the American Medical Informatics Association, 2021  

Signatures of plasticity, metastasis, and immunosuppression in an atlas of human small cell lung cancer
Joseph M Chan, Álvaro Quintanal-Villalonga, Vianne Ran Gao, Yubin Xie, Viola Allaj, Ojasvi Chaudhary, Ignas Masilionis, Jacklynn Egger, Andrew Chow, Thomas Walle, Marissa Mattar, Dig Vijay Kumar Yarlagadda, James L Wang, Fathema Uddin, Michael Offin, Metamia Ciampricotti, Besnik Qeriqi, Amber Bahr, Elisa de Stanchina, Umesh K Bhanot, W Victoria Lai, Matthew J Bott, David R Jones, Arvin Ruiz, Marina K Baine, Yanyun Li, Natasha Rekhtman, John T Poirier, Tal Nawy, Triparna Sen, Linas Mazutis, Travis J Hollmann, Dana Pe'er, Charles M Rudin
Cancer Cell, 2020