Sasank Chilamkurthy
Founder & CEO at JOHNAIC
Bengaluru, Karnataka, India
Summary
🤩
Rockstar🎓
Top SchoolSasank Chilamkurthy is a founder and CEO with 11 years of experience building AI products and open-source tooling, most recently creating hardware to broaden access to on-device AI at JOHNAIC. A core AI researcher and engineer by training, he was a founding technologist at Qure.ai where he led development of clinical products (including qER) and published in top venues such as The Lancet. He is an active PyTorch contributor—improving torchnet, torchvision docs and tutorials—and has enabled practical ML workflows by adding pretrained model support to popular repositories like EfficientNet-PyTorch. Comfortable bridging research and production, he combines deep technical work (signal processing and ML) with product sensibility from early startup days at Housing.com. Based in Bengaluru and fluent in open-source collaboration, he often surface-tests ideas publicly (and is notably active on Twitter), showing a preference for pragmatic, reproducible engineering.
11 years of coding experience
8 years of employment as a software developer
Indian Institute of Technology Bombay
Telugu, English, Hindi
Stackoverflow
1,070reputation
97kreached
5answers
0questions
pytorch
top-5%
Github Skills (29)
pytorch10
restructuredtext10
python10
pre-trained-model10
sphinx10
data-set10
machine-learning10
rs10
lark10
data-management10
datasets10
computer-vision10
efficientnet10
documentation10
trainings9
Programming languages (21)
Github contributions (5)
pytorch/tutorials
Mar 2017 - Jun 2018
PyTorch tutorials.
Role in this project:
Technical Writer
Technical WriterContributions:148 commits, 97 PRs, 146 pushes in 1 year 3 months
Contributions summary:Sasank's contributions primarily focused on creating and updating documentation for the PyTorch tutorials repository. This included adding and modifying content within existing tutorials, correcting formatting issues, and incorporating new examples. The user also updated the repository's CSS and layout to improve the overall presentation of the documentation. Furthermore, the user contributed to the table of contents, ensuring proper organization of the tutorials.
deep-learningpytorchpytorch-tutorials
pytorch/tnt
Feb 2017 - Mar 2017
A lightweight library for PyTorch training tools and utilities
Role in this project:Back-end Developer
Back-end DeveloperContributions:14 commits, 3 PRs, 8 comments in 19 days
Contributions summary:Sasank primarily focused on enhancing the `torchnet` library's dataset functionalities. Their contributions included adding comprehensive docstrings to various dataset classes, improving code formatting, and fixing minor bugs. Furthermore, the user implemented `ConcatDataset`, `SplitDataset`, and added seeding to `ShuffleDataset`, expanding the library's capabilities for data handling and manipulation. These changes streamlined the library's usability and provided critical building blocks for data processing within PyTorch.
pytorchpythondeep-learningreinforcement-learningmachine-learning
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