Ishika Roy - Senior Analytics Libraries Developer at NVIDIA

Ishika Roy

Senior Analytics Libraries Developer at NVIDIA

Austin, Texas, United States

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Summary

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Rockstar

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Top School

Ishika Roy is a Senior Analytics Libraries Developer at NVIDIA with seven years of experience building high-performance, GPU-accelerated data and graph analytics libraries. Currently pursuing an MS in Electrical and Computer Engineering at Georgia Tech, she focuses on computer architecture, performance analysis, HPC, cloud applications, and embedded systems. Her open-source contributions to RAPIDS projects like raft, cuGraph, and cuDF show hands-on C++/CUDA backend work—implementing CSV parsing, error handling utilities, and performance-focused algorithm primitives. She blends deep systems-level thinking with practical Python integrations and testing, enabling production-ready analytics workflows. Prior internships span embedded targets at MathWorks and visualization at a cloud startup, reflecting versatility across low-level hardware interfaces and user-facing tools. Based in Austin, she brings a rare mix of GPU expertise and embedded-systems experience that accelerates both data pipelines and deployable edge solutions.

7 years of coding experience

2 years of employment as a software developer

Master’s Degree, Electrical and Computer Engineering, 3.8, Master’s Degree, Electrical and Computer Engineering, 3.8 at Georgia Institute of Technology

Bachelor’s Degree, Electronics and Telecommunication Engineering, 8.98/10, Bachelor’s Degree, Electronics and Telecommunication Engineering, 8.98/10 at Fr Conceicao Rodrigues Institute of Technology

English, Hindi, Bengali

Github Skills (24)

csv-parse10

c-language10

python10

dataframes10

gpu-programming10

cudf10

machine-learning10

dataframe10

gpu10

csv-parsing10

cuda10

error-handling10

cprogramming-language10

pandas9

graph-algorithms9

Programming languages (5)

C++ShellJupyter NotebookPythonCuda

Github contributions (5)

rapidsai/cugraph

Dec 2018 - Sep 2021

cuGraph - RAPIDS Graph Analytics Library

Role in this project:

Back-end Developer

Contributions:157 reviews, 492 commits, 106 PRs in 2 years 9 months

Contributions summary:Ishika's commits primarily involve implementing and merging changes related to the `error_utils.h` file, which is crucial for managing errors within the CUDA runtime environment. The commits include fixes for transforming between gdf and cudf data types, and the addition and refinement of error handling utilities to improve code stability and debugging capabilities. The changes indicate a focus on backend development with a strong emphasis on GPU-accelerated graph analytics using CUDA, which directly aligns with the repository's purpose as a RAPIDS Graph Analytics Library.

cudagraph-analysisanalyticsgraph-analyticsgraphml

rapidsai/cudf

Sep 2018 - Dec 2018

cuDF - GPU DataFrame Library

Role in this project:

Back-end Developer & Data Engineer

Contributions:25 commits, 4 PRs, 35 comments in 2 months

Contributions summary:Ishika primarily contributed to the cuDF library by implementing and testing a CSV reader, including the addition of parameters such as 'dayfirst' and 'quoting'. Their work involved creating Python wrappers and tests, modifying C++ code for CSV parsing, and integrating with pandas for data validation. They also addressed code style issues and added documentation, contributing to the library's functionality and usability.

cudadataframe-librarydata-analysiscppcudf

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