CV
Curriculum vitae. A PDF version is also available for download.
Contact Information
| Name | Govinda M. Kamath |
| Professional Title | Senior Scientist, 10x Genomics |
Professional Summary
Applied ML researcher/engineer with 5+ years turning algorithms into production systems used by biologists and engineers, spanning fundamental academic research (PhD, Stanford) and biotech industry practice (10x Genomics). I work in tight collaboration with experimental biologists to design analyses and build pipelines they can depend on — across single-cell, spatial transcriptomics, and imaging platforms — with a career-long focus on making biological inference rigorous: avoiding false discoveries and building methods scientists can actually trust.
Experience
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2021 - present Pleasanton, CA
Senior Scientist
10x Genomics
- Visium HD spatial transcriptomics: worked in a tight loop with biologists on assay and protocol development, designing and optimizing metrics for sensitivity, specificity, and false-positive detection. Algorithms that extract spatial signal from data — effectively a 30,000-sparse-channel image — ship in Visium HD and run in production for every Visium HD customer.
- Production ML pipelines: led end-to-end development of ML models for cell-type annotation and nucleus segmentation — from data collection and labeling through training, evaluation, and production deployment — across all three 10x Genomics platforms: Visium, Xenium, and Chromium (single-cell).
- Engineering infrastructure: own production-quality pipelines end-to-end within 10x Genomics’ large shared codebase (primarily Python and Rust, also Go and C/C++), shipped in released software, with reproducible builds via Bazel.
- Agentic AI for single-cell workflows: building a tool-use agentic environment that automates single-cell analysis workflows, using eval-driven development to measure agent performance, correctness, and failure modes.
- Led a team of 3 ML scientists/engineers building ML algorithms from data collection through production.
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2019 - 2021 Cambridge, MA
Postdoctoral Researcher
Microsoft Research New England
- Research on knowledge distillation, bandit-based rank-one models, and connections between sequence alignment and compression; published at ICLR and NeurIPS.
- Advised by Lester Mackey.
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2019 - 2019 Palo Alto, CA
PhD Intern
Applied Protocol Research
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2018 - 2018 Mountain View, CA
Machine Learning Resident
Google X
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2017 - 2017 Bangalore, India
Research Intern, Theory Group
Microsoft Research
- Worked on spectral clustering on a planted block model.
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2016 - 2016 Redmond, WA
Research Intern, Theory Group
Microsoft Research
- Worked on the DNA storage project: trace reconstruction and data analysis.
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2012 - 2013 Bangalore, India
Research Associate, Codes and Signal Design Lab
Indian Institute of Science (IISc)
- Project: Codes for Distributed Storage (funded by NetApp Inc.).
Education
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2014 - 2019 Stanford, CA
PhD
Stanford University
Electrical Engineering
- Advisor: David Tse.
- Thesis: Almost linear time algorithms for problems from Computational Genomics.
- GPA: 4.0/4.0
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2013 - 2014 Berkeley, CA
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2010 - 2012 Bangalore, India
Master of Engineering (M.E.)
Indian Institute of Science (IISc)
Electrical Communication Engineering
- Thesis: On codes for Distributed Storage and Locality of Error Correction.
- Class rank: 1/28
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2006 - 2010 Surathkal, India
Bachelor of Technology (B.Tech.)
National Institute of Technology Karnataka (NITK)
Electronics and Communication Engineering
- Class rank: 1/74