Vaibhav Adlakha

Member Of Technical Staff at Cohere

Canada
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Summary

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Rockstar
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Vaibhav Adlakha is a PhD candidate at McGill and Mila with eight years of industry and research experience focused on LLM-based embeddings and dense retrieval. He combines academic rigor—guided by Prof. Siva Reddy—with hands-on work at ServiceNow Research and an internship at Cohere, bridging cutting-edge retrieval research and applied engineering. His background includes research on open information extraction and knowledge graphs from IIT Delhi and production experience building device analytics at Samsung R&D Bangalore. Comfortable moving between prototype research and production systems, he excels at turning novel embedding and retrieval ideas into scalable implementations. Based in Canada, he brings a strong math and CS foundation (IIT Guwahati) and a knack for translating complex NLP methods into usable tools for real-world decision-making.
code8 years of coding experience
job9 years of employment as a software developer
bookBachelor of Technology (B.Tech.) Mathematics and Computer Science, Bachelor of Technology (B.Tech.) Mathematics and Computer Science at Indian Institute of Technology, Guwahati
bookDelhi Public School - Rohini
bookMaster of Science - MS Computer Science, Master of Science - MS Computer Science at McGill University
languagesHindi, English
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Stackoverflow

Stats
21reputation
5kreached
2answers
0questions
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Github Skills (87)

similarity-search10
multilabel-classification10
benchmark10
sentence10
neural-search10
semantic-search10
speech10
bug-reporting10
embedding10
clustering10
multilingual10
multimodal10
nlp10
sentence-embeddings10
sentence-transformers10

Programming languages (6)

TypeScriptDockerfileC++JavaScriptPythonPostScript

Github contributions (5)

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McGill-NLP/instruct-qa

Jul 2023 - Aug 2024

Code and Data for "Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering"
Contributions:2 reviews, 21 PRs, 35 pushes in 1 year
question-answering
vaibhavad/mteb

May 2024 - Sep 2025

MTEB: Massive Text Embedding Benchmark
Contributions:75 pushes, 8 branches in 1 year 4 months
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