Abishkar Chhetri
Co-Founder at Alpen Labs
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolAbishkar Chhetri is a Co-Founder and former software engineer with eight years of experience building and validating AI systems, currently leading a New York tech startup after earning a computer science degree from MIT with a statistics minor. He has shipped language, vision, and reinforcement-learning solutions at Microsoft—contributing to Azure Cognitive Services—and has research experience from MIT Media Lab and industry work in recommender systems and distributed ML pipelines. Known for a methodical engineering approach, he has hands-on QA experience testing XLNet implementations in the prominent microsoft/nlp-recipes repository, highlighting a focus on model reliability as well as development. Comfortable bridging research and product, he combines deep technical interests in NLP, HCI, distributed computing, and cryptography with practical startup execution. Outside work he stays active through football, hiking, and bouldering, which he credits for keeping problem-solving energy high.
8 years of coding experience
5 years of employment as a software developer
Bachelor's degree Computer Science and Engineering, Bachelor's degree Computer Science and Engineering at Massachusetts Institute of TechnologyInternational BaccalaureateDruid Hills High School
English, Nepali, Hindi, Spanish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (7)
machine-learning10
nlp10
xnet10
pytest10
python10
natural-language-processing10
testing10
Programming languages (6)
Github contributions (5)
microsoft/nlp-recipes
Aug 2019 - Sep 2019
Natural Language Processing Best Practices & Examples
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:7 commits, 1 PR, 3 comments in 7 days
Contributions summary:Abishkar primarily contributed to the quality assurance of the project by writing and integrating unit tests. Their work focused on testing the XLNet model, including sequence classification and common functionalities. These tests ensure the reliability and correctness of the XLNet implementation within the nlp-recipes repository, demonstrating a focus on model verification and testing.
natural-language-understandingnluword-embeddingslanguage-processingdialogue-systems
chhetri22/BucketsAndTiles
Jun 2019 - Jul 2019
Contributions:17 PRs, 52 pushes, 17 branches in 27 days
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