publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

2025

  1. Accelerating scRNA-seq Analysis: Automated cell type annotation using representation learning and vector search
    Stephen R. Williams, Fedor Grab, Govinda M. Kamath, Yerdos Ordabayev, Jeff Mellen, Patrick Roelli, Kristian Cibulskis, Erik Lehnert, Fen Xie, Miguel Covarrubias, Nur-Taz Rahman, Timothy Tickle, Emre Erhan, Nicolas Malfroy-Camine, Kevin Lydon, Mehrtash Babadi, and Nigel F. Delaney
    bioRxiv, 2025
    Describes the automated cell-type annotation algorithm shipped in Cell Ranger.
  2. High-definition spatial transcriptomic profiling of immune cell populations in colorectal cancer
    Michelli F. Oliveira, Juan P. Romero, Meii Chung, Stephen Williams, Andrew D. Gottscho, Anushka Gupta, Susan E. Pilipauskas, Syrus Mohabbat, Nandhini Raman, David Sukovich, David Patterson, Visium HD Development Team, and Sarah E. B. Taylor
    Nature Genetics, 2025
    As part of the Visium HD Development Team that built the product demonstrated in the paper.
  3. Spatial Transcriptomic Profiling of the Tumor Microenvironment at Single-Cell-Scale Resolution Using Visium HD 3’
    Anuj Patel, Debashish Chitnis, Josh Gu, Anushka Gupta, Marco Serra, Zixue Ma, Monica Nagendran, Joey Arthur, Govinda M. Kamath, David Sukovich, Sean Osinski, and Augusto M. Tentori
    Journal of Molecular Diagnostics, 2025
  4. Visium HD 3’ enables unbiased whole transcriptome spatial profiling of tumor microenvironment in fresh frozen cancer tissues at single cell-scale resolution
    Debashish Chitnis, Marco Serra, Josh Gu, Anushka Gupta, Nancy Conejo, Aarushi Kalaimani, Govinda M. Kamath, Zixue Ma, Monica Nagendran, Joey Arthur, Julia Cowen, Anuj Patel, David Sukovich, and Augusto M. Tentori
    Cancer Research, 2025
    AACR 2025 conference abstract

2024

  1. Reference free spot deconvolution in spatial transcriptomics
    Stephen R. Williams, Govinda M. Kamath, and Joey G. Arthur
    2024
    US Patent Application US20240287599A1
  2. Whole transcriptome spatial profiling of the tumor microenvironment in FFPE, fresh frozen, and fixed frozen tissues
    Jun Chiang, Naishitha Anaparthy, Nancy Conejo, Monica Nagendran, David Sukovich, David Patterson, Lauren Gutgesell, Govinda M. Kamath, and Augusto M. Tentori
    Journal for ImmunoTherapy of Cancer, 2024
    SITC 2024 conference abstract

2023

  1. High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis
    Amanda Janesick, Robert Shelansky, Andrew D. Gottscho, Florian Wagner, Stephen R. Williams, Morgane Rouault, Ghezal Beliakoff, Carolyn A. Morrison, Michelli F. Oliveira, Jordan T. Sicherman, Andrew Kohlway, Jawad Abousoud, Tingsheng Yu Drennon, Seayar H. Mohabbat, 10x Development Teams, and Sarah E. B. Taylor
    Nature Communications, 2023
    As part of the 10x Development Teams that built the products demonstrated in the paper.
  2. Spatially resolved whole-transcriptome analysis with simultaneous highly multiplexed immune cell epitope detection in multiple cancer tissues
    Anushka Gupta, Stephen Williams, Lauren Gutgasell, Benton Veire, Ace Santiago, Hardeep Singh, Rena Chan, Alex Hermes, Govinda M. Kamath, Anuj Patel, and David Sukovich
    The Journal of Immunology, 2023
    AAI 2023 conference abstract
  3. Application of spatially resolved transcriptomics to screen multiple tumor biospecimens using tissue microarrays
    Syrus Mohabbat, Hardeep Singh, Stephen R. Williams, Lauren M. M. Gutgesell, David J. Sukovich, Govinda M. Kamath, Hanyoup Kim, Amanda Janesick, Robert Shelansky, Ghezal Beliakoff, Augusto M. Tentori, Albert Kim, Cedric R. Uytingco, and Sarah E. B. Taylor
    Cancer Research, 2023
    AACR 2023 conference abstract

2021

  1. Knowledge Distillation as Semiparametric Inference
    Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, and Lester Mackey
    In International Conference on Learning Representations, 2021
  2. Bandit-Based Monte Carlo Optimization for Nearest Neighbors
    Vivek Bagaria*, Tavor Baharav*, Govinda M. Kamath*, and David N. Tse
    IEEE Journal on Selected Areas in Information Theory, 2021
    * Co-first authors
  3. Genome-scale screens identify factors regulating tumor cell responses to natural killer cells
    Michal Sheffer, Emily Lowry, Nicky Beelen, Minasri Borah, Suha Naffar-Abu Amara, Chris C. Mader, Jennifer A. Roth, Aviad Tsherniak, Samuel S. Freeman, Olga Dashevsky, Sara Gandolfi, Samantha Bender, Jordan G. Bryan, Cong Zhu, Li Wang, Ifrah Tariq, Govinda M. Kamath, Ricardo De Matos Simoes, Eugen Dhimolea, Channing Yu, Yiguo Hu, Olli Dufva, Marios Giannakis, Vasilis Syrgkanis, Ernest Fraenkel, Todd Golub, Rizwan Romee, Satu Mustjoki, Aedin C. Culhane, Lotte Wieten, and Constantine S. Mitsiades
    Nature Genetics, 2021
  4. Sketching and sequence alignment: A rate-distortion perspective
    Ilan Shomorony and Govinda M. Kamath
    In IEEE International Symposium on Information Theory, 2021

2020

  1. Adaptive Learning of Rank-One Models for Efficient Pairwise Sequence Alignment
    Govinda M. Kamath*, Tavor Baharav*, and Ilan Shomorony
    In Advances in Neural Information Processing Systems, 2020
    * Co-first authors
  2. Spectral Jaccard Similarity: A new approach to estimating pairwise sequence alignments
    Tavor Baharav*, Govinda M. Kamath*, David N. Tse, and Ilan Shomorony
    Cell Patterns, 2020
    * Co-first authors
  3. crispr2vec: Machine Learning Model Predicts Off-Target Cuts of CRISPR systems
    Tara Basu Trivedi, Ron Boger, Govinda M. Kamath, Georgios Evangelopoulos, Jamie Cate, Jennifer Doudna, and Jack Hidary
    bioRxiv, 2020

2019

  1. Valid post-clustering differential analysis for single-cell RNA-Seq
    Jesse M. Zhang, Govinda M. Kamath, and David N. Tse
    Cell Systems, 2019
    Also presented at RECOMB 2019
  2. Proof-of-Stake Longest Chain Protocols Revisited
    Xintong Wang, Govinda M. Kamath, Vivek Bagaria, Sreeram Kannan, Sewoong Oh, David N. Tse, and Pramod Viswanath
    2019
  3. Almost Linear Time Algorithms for Problems of Computational Genomics
    Govinda M. Kamath
    Stanford University, 2019

2018

  1. Adaptive Monte-Carlo Optimization
    Vivek Bagaria*, Govinda M. Kamath*, and David N. Tse
    arXiv preprint arXiv:1805.08321, 2018
    * Co-first authors
  2. Medoids in almost linear time via multi-armed bandits
    Vivek Bagaria*, Govinda M. Kamath*, Vasilis Ntranos*, Martin J. Zhang*, and David N. Tse
    In International Conference on Artificial Intelligence and Statistics, 2018
    * Co-first authors
  3. Random access in large-scale DNA data storage
    Lee Organick, Siena Dumas Ang, Yuan-Jyue Chen, Randolph Lopez, Sergey Yekhanin, Konstantin Makarychev, Miklos Z. Racz, Govinda M. Kamath, Parikshit Gopalan, Bichlien Nguyen, Christopher Takahashi, Sharon Newman, Hsing-Yeh Parker, Cyrus Rashtchian, Kendall Stewart, Gagan Gupta, Robert Carlson, John Mulligan, Douglas Carmean, Georg Seelig, Luis Ceze, and Karin Strauss
    Nature Biotechnology, 2018
    Work done as an intern at Microsoft Research, Redmond: data analysis, modeling, and characterization of the storage channel.

2017

  1. HINGE: long-read assembly achieves optimal repeat resolution
    Govinda M. Kamath*, Ilan Shomorony*, Fei Xia*, Thomas A. Courtade, and David N. Tse
    Genome Research, 2017
    * Co-first authors. Press coverage: GenomeWeb

2016

  1. Community Recovery in Graphs with Locality
    Yuxin Chen, Govinda M. Kamath, Changho Suh, and David N. Tse
    In International Conference on Machine Learning, 2016
  2. Partial Assembly: A Rate-Distortion Perspective
    Ilan Shomorony, Govinda M. Kamath, Fei Xia, Thomas A. Courtade, and David N. Tse
    In IEEE International Symposium on Information Theory, 2016
  3. Fast and accurate single-cell RNA-Seq analysis by clustering of transcript-compatibility counts
    Genome Biology, 2016
    * Co-first authors

2015

  1. Learning the Language of the Genome using RNNs
    Jesse Zhang and Govinda M. Kamath
    2015
  2. Optimal Haplotype Assembly from High-Throughput Mate Pair Reads
    Govinda M. Kamath, Eren Sasoglu, and David N. Tse
    In IEEE International Symposium on Information Theory, 2015

2014

  1. Codes With Local Regeneration and Erasure Correction
    Govinda M. Kamath, Narayanamoorthy Prakash, Lalitha Vadlamani, and P. Vijay Kumar
    IEEE Transactions on Information Theory, 2014
    Earlier version published at ISIT 2013

2013

  1. Explicit MBR All-Symbol Locality Codes
    Govinda M. Kamath, Narayanamoorthy Prakash, Lalitha Vadlamani, P. Vijay Kumar, Natalia Silberstein, Ankit S. Rawat, O. Ozan Koyluoglu, and Sriram Vishwanath
    In IEEE International Symposium on Information Theory, 2013

2012

  1. Optimal Linear Codes with a Local-Error-Correction Property
    Narayanamoorthy Prakash, Govinda M. Kamath, Lalitha Vadlamani, and P. Vijay Kumar
    In IEEE International Symposium on Information Theory, 2012
  2. NCC
    Regenerating codes: a reformulated storage-bandwidth trade-off and a new construction
    Govinda M. Kamath and P. Vijay Kumar
    In National Conference on Communications, 2012
  3. NCC
    On t-designs and bounds relating query complexity to error resilience in locally correctable codes
    Lalitha Vadlamani, Narayanamoorthy Prakash, Govinda M. Kamath, and P. Vijay Kumar
    In National Conference on Communications, 2012