Bhaven Patel
Software Engineer, AI Platform
California, United States
Summary
👤
Senior🎓
Top SchoolBhaven Patel is a Software Engineer focused on AI platform and production ML with eight years of experience building cloud-native systems and healthcare-focused data science. A Harvard MEng in Computational Science and Engineering, he has applied ML to clinical problems—developing models that predicted ICU potassium levels with high precision—and built pipelines for high-throughput DNA sequencing and microscopy analysis. He’s held senior engineering and principal roles across cloud platform teams, shipping infrastructure and CI/CD improvements at scale, and now contributes to AI platform work at Pano AI. Comfortable bridging research and production, Bhaven combines biology-trained domain insight from Stanford with software engineering rigor, and maintains reproducible tools and analyses on his GitHub. An underrated strength is his teaching and mentorship background—he led a 7‑TA cohort and taught systems development to 130+ students—helping him communicate complex systems to cross-functional teams.
9 years of coding experience
11 years of employment as a software developer
Master's of Engineering Computational Science and Engineering, Master's of Engineering Computational Science and Engineering at Harvard UniversityJunipero Serra High SchoolBachelor’s Degree Biology Concentration in Biochemistry and Biophysics | Minor in Computer Science, Bachelor’s Degree Biology Concentration in Biochemistry and Biophysics | Minor in Computer Science at Stanford University
English, Gujarati, Spanish
Github Skills (10)
sentiment5
bioinformatics3
flask2
python2
sentiment-analysis2
nvidia-docker1
machine-learning1
nlp1
docker1
natural-language-processing1
Programming languages (4)
Github contributions (5)
testing-for-CS207/cs207-FinalProject
Oct 2019 - Oct 2025
repo for testing CS207 project for 2019
Contributions:1 PR, 4 pushes, 3 branches in 6 years 1 month
testing
bhavenp/deployable_sentiment_analysis
May 2020 - Aug 2020
Repo to deploy a sentiment analysis model using a Flask application.
Contributions:24 PRs, 67 pushes, 17 branches in 2 months
pythonflasksentimentmodel-analysisflask-application
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