Havan Agrawal
Software Engineer at Google
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolHavan Agrawal is a software engineer based in Seattle with over a decade of professional experience and a Master’s in Data Science from the University of Washington. Currently at Google, he brings strong back-end and algorithmic skills grounded in Java and Scala, and a track record of improving reliability through test automation. His open-source contributions include enhancing the test suite and fixing a subtle bug in the popular spotpy statistical optimization tool, and regularly adding LeetCode solutions that demonstrate practical problem-solving and refactoring ability. Prior roles across Amazon Lab126 and Morgan Stanley show experience in both product-focused internships and production engineering in finance. Colleagues would describe him as a detail-oriented engineer who pairs rigorous statistical thinking with hands-on software craftsmanship.
11 years of coding experience
2 years of employment as a software developer
Bachelor of Engineering (B.E.), Bachelor of Engineering (B.E.) at KJ Somaiya College of Engineering, VidyaviharMaster of Science - MS, Master of Science - MS at University of WashingtonP. G. Garodia High School
Hindi, English
Stackoverflow
1,039reputation
86kreached
44answers
0questions
Github Skills (20)
unit-testing10
algorithms10
pytest10
python10
lintcode10
testing10
data-structure10
java10
numpy10
javas10
data-structures10
statistic9
statistics9
iview7
recursion6
Programming languages (9)
Github contributions (5)
thouska/spotpy
Jan 2018 - Mar 2018
A Statistical Parameter Optimization Tool
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:64 commits, 13 PRs, 26 comments in 1 month
Contributions summary:Havan primarily contributed to the testing framework of the `spotpy` repository, a statistical parameter optimization tool. Their work focused on adding comprehensive unit tests for various objective functions, including bias, pbias, nashsutcliffe, log-Nash-Sutcliffe, log_p, correlation coefficient, rsquared, MSE, RMSE, RRMSE, agreement index, covariance, DMSE, KGE, RSR and Volume Error. Furthermore, the user identified and addressed a bug within the DMSE function while enhancing the test suite.
optimizationstatisticalmachine-learningparameterparameter-estimation
fishercoder1534/Leetcode
Apr 2019 - May 2019
Solutions to LeetCode problems; updated daily. Subscribe to my YouTube channel for more.
Role in this project:Back-end Developer
Back-end DeveloperContributions:9 commits, 13 PRs, 7 comments in 11 days
Contributions summary:Havan primarily contributes solutions to LeetCode problems, focusing on algorithms and data structures. Their commits involve adding new solutions and improving existing ones, demonstrating proficiency in Java. The user's work includes implementing solutions for various LeetCode problems, writing unit tests, and showcasing an understanding of problem-solving techniques. They also demonstrate an ability to refactor and optimize existing solutions.
pythonmysqlleetcodeyoutube-channelproblems
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