Ayush Dattagupta
Senior Software Engineer at NVIDIA
California, United States
Summary
🤩
Rockstar🎓
Top SchoolAyush Dattagupta is a Senior Software Engineer at NVIDIA with eight years of experience building high-performance ML and data-processing systems, blending production-grade backend development with GPU-accelerated data science. He holds an MS in Computer Science from UCLA and a top-ranked BE from BITS Pilani Dubai, and has repeatedly contributed to the RAPIDS cuDF ecosystem—improving groupby/multiindex behavior and enabling GPU DataFrame operations for real-world ETL and weblog stream processing. His background spans C++ geospatial raster work at Esri to end-to-end GPU ML pipelines and Airflow/Spark optimizations, reflecting both low-level systems expertise and data workflow pragmatism. Colleagues rely on him to navigate tricky edge cases in high-throughput data paths and to translate research-grade acceleration into maintainable engineering.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Engineering - BE, Computer Science, 9.83/10.00, Bachelor of Engineering - BE, Computer Science, 9.83/10.00 at Birla Institute Of Technology and Science, Pilani DubaiMaster of Science - MS, Computer Science, 3.91/4.00, Master of Science - MS, Computer Science, 3.91/4.00 at University of California, Los Angeles
English, Hindi, Bengali
Github Skills (14)
dataframes10
data-transformation10
cudf10
stream-processing10
rapids10
gpu-acceleration10
python10
dataframe10
data-analysis10
jupyter-notebook9
cuda9
cpp8
pandas7
machine-learning6
Programming languages (10)
Github contributions (5)
rapidsai/cudf
Sep 2018 - Sep 2021
cuDF - GPU DataFrame Library
Role in this project:
Back-end Developer
Back-end DeveloperContributions:30 reviews, 120 commits, 31 PRs in 3 years 1 month
Contributions summary:Ayush's commits primarily focused on enhancing the cuDF library, a GPU DataFrame library. They implemented improvements to series creation, handled scalar values within the DataFrame, and fixed style issues. Moreover, the user contributed to the groupby functionality, particularly addressing edge cases such as empty groupbys and multi-index operations. Finally, they worked on the multiindex object, introducing slicing capabilities and improving error handling.
cudadataframe-librarydata-analysiscppcudf
rapidsai-community/notebooks-contrib
Jul 2019 - Oct 2020
RAPIDS Community Notebooks
Role in this project:Data Scientist
Data ScientistContributions:23 commits, 9 PRs, 46 comments in 1 year 3 months
Contributions summary:Ayush contributed to a notebook focused on stream processing of weblogs using the RAPIDS cuDF library. Their changes involve processing log data, calculating metrics like traffic and errors, and saving these metrics to files. The user's commits demonstrate an understanding of data loading, data manipulation, and the use of cuDF for GPU-accelerated data processing.
jupyter-notebooknotebooksrapids
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