Illia Polosukhin
Co-Founder at NEAR Protocol
San Francisco, California, Portugal
Summary
🤩
Rockstar🎓
Top SchoolIllia Polosukhin is a Co-Founder and AI researcher with 15 years of experience building machine intelligence, developer tooling, and blockchain infrastructure. He led work on TensorFlow's TF.Learn (skflow) at Google Research, helping migrate it into TensorFlow's contrib, and today co-leads NEAR Protocol where he contributes code and documentation across SDKs including Rust smart contracts and near-api-js. He blends deep learning and natural language expertise with full-stack engineering—working on everything from protobuf-backed RPCs to smart-contract refactors—and is motivated by using software and data to make the world better. Based in San Francisco with ties to Portugal, he pairs research-level insight with hands-on product and open-source delivery.
16 years of coding experience
9 years of employment as a software developer
National Technical University "Kharkiv Polytechnic Institute"
English, Russian, Ukrainian, Chinese, French
Stackoverflow
1,835reputation
116kreached
31answers
6questions
classification
top-5%
tensorflow
top-5%
Github Skills (36)
near-protocol10
json-rpc10
markdown10
javascript10
documentations10
python10
nearprotocol10
rustwasm10
machine-learning10
tensorflow210
wasmer10
javascripts10
markdown-it10
sdk10
tensorflow10
Programming languages (15)
Github contributions (5)
tensorflow/skflow
Mar 2016 - Jan 2017
Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 21 commits, 56 PRs in 10 months
Contributions summary:Illia primarily focused on transitioning the `skflow` library from a standalone project to integration within TensorFlow's `contrib` module. Their contributions involved updating the codebase to reflect this migration, including modifying import statements, updating the README, and adjusting build scripts. The changes reflect efforts to deprecate the separate `skflow` library and integrate its functionality within the core TensorFlow ecosystem. This also included updating installation instructions.
pythondeep-learningmachinelearningneural-networksmachine-learning
near/near-api-js
Jan 2019 - Apr 2021
JavaScript library to interact with NEAR Protocol via RPC API
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:93 commits, 31 PRs, 74 pushes in 2 years 3 months
Contributions summary:Illia primarily contributed to the JavaScript library for interacting with the NEAR Protocol. Their work involved refactoring transactions, integrating protobufs for the `TransactionBody`, and implementing JSON RPC support, including `broadcast_tx_async` and query functionality. The user also addressed bugs, updated dependencies and refactored parts of the code. They focused on improving the user experience with the NEAR protocol.
apijavascript-libraryrpcethereumrpc-api
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