Shlok Sabarwal
Software Engineer at Tesla
Madison, Wisconsin, United States
Summary
🤩
Rockstar🎓
Top SchoolShlok Sabarwal is a software engineer and UW–Madison senior studying Computer Science and Data Science, currently working at Tesla after internships at Samsung Research America and Apple. He blends research and production: as an undergraduate AI researcher at SBEL he built low-latency, sensor-fusion ML models and gained hands-on HPC/CUDA experience for simulation workflows. His open-source contributions span CI/CD and packaging for the high-performance Chrono physics engine and time-series model/feature work in sktime, highlighting both systems automation and applied ML expertise. With eight years of practical experience across research, product, and DevOps roles, he excels at taking deep learning models from experimental code to deployable pipelines. Uncommonly for someone still in school, he has shipped cross-platform build automation and conda packaging fixes that improve reproducibility for complex C++ and ML projects.
8 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Majors: Computer Science, Data Science; Minor: Economic Analytics, Senior, Bachelor's degree, Majors: Computer Science, Data Science; Minor: Economic Analytics, Senior at University of Wisconsin-MadisonHigh School Diploma, General Studies, High School Diploma, General Studies at The Shishukunj International School
Github Skills (27)
python10
data-science10
classification10
scikit10
machine-learning10
conda10
time-series10
cmake10
classify10
forecasting10
sktime10
ci-cd-pipeline10
build-automation10
scikit-learn10
forecast10
Programming languages (4)
Github contributions (5)
projectchrono/chrono
Dec 2021 - Dec 2022
High-performance C++ library for multiphysics and multibody dynamics simulations
Role in this project:
DevOps Engineer & Automation Engineer
DevOps Engineer & Automation EngineerContributions:92 commits, 16 PRs, 314 pushes in 1 year
Contributions summary:Shlok primarily focused on enhancing the continuous integration and continuous deployment (CI/CD) pipeline for Windows builds within the project. Their contributions included modifying build scripts (bld.bat, build.sh) and configuration files (.gitlab-ci.yml, buildMacOS.sh), and addressing deployment issues related to compiler versions and package dependencies, particularly around conda builds. Furthermore, the user worked on packaging and upload scripts to ensure correct package deployment.
c-plus-plussimulationroboticssimulationsmultibody
sktime/sktime
Apr 2024 - Sep 2024
A unified framework for machine learning with time series
Role in this project:Data Scientist
Data ScientistContributions:38 reviews, 10 PRs, 99 comments in 5 months
Contributions summary:Shlok primarily contributes to the `sktime` repository by implementing and testing machine-learning related feature extractors and models, specifically targeting time series analysis. They added test parameters for the LSTM-FCNN network, expanding its testing capabilities. Furthermore, the user implemented an ADI/CV feature extractor, categorizing time series data and incorporating the use of testing parameters. The user also integrated new sktime datatypes for easier use with the GluonTS library.
forecastingtime-series-analysistime-series-regressiondata-sciencedeep-learning
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