Nishant Desai
Founding Engineer at Sunday
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolNishant Desai is a founding engineer and machine learning researcher with 12 years of experience building production-grade AI systems from Berkeley labs to Tesla Autopilot and early-stage startups. He combines deep academic training in CS and statistics (UC Berkeley MS/BA) and AI-safety research with hands-on deployment of perception and decision systems at scale, most recently as a staff ML engineer on Autopilot. Comfortable wearing both research and engineering hats, he has contributed to data-driven education resources and course notebooks as well as mission-critical vehicle software. Now based in the San Francisco Bay Area, he focuses on turning uncertain research ideas into robust products, applying rigorous statistical thinking to real-world ML problems.
12 years of coding experience
8 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at University of California, Berkeley
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
data-analysis10
jupyter-notebook10
hypothesis-testing10
hypothesis-tests10
statistical-inference10
python9
linear-regression9
pandas8
Programming languages (3)
Github contributions (5)
data-8/data8assets
Oct 2016 - Nov 2016
Assets for data8.org
Role in this project:
Data Scientist
Data ScientistContributions:23 commits, 23 pushes in 1 month
Contributions summary:Nishant primarily worked on Jupyter notebooks, likely for a data science course or project. The commits focus on data analysis, hypothesis testing, and statistical inference, specifically related to analyzing survey data and interpreting confidence intervals. The contributions involve exploring concepts related to linear regression, specifically with the goal of predicting waiting times using eruption durations.
data-analysisdataframestextbookassets
nishdesai/nishdesai.github.io
Sep 2016 - Aug 2018
Contributions:16 pushes, 1 branch in 1 year 11 months
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