Ajay Thorve
Senior Software Engineer at NVIDIA
Washington, District of Columbia, United States
Summary
🤩
Rockstar🎓
Top SchoolAjay Thorve is a Senior Software Engineer at NVIDIA with nine years of experience building GPU-accelerated data and visualization tooling, blending JavaScript, Python, cloud, and WebGL expertise. At RAPIDS he contributes to high-performance back-end systems—integrating cuDF and CuPy into datashader workflows to speed large-scale rendering and visualization. His background spans AI infrastructure, real-time collaborative tools at NYU, and production web and mobile projects, reflecting a strong full-stack and systems remit. He’s an engaging speaker on accelerating visualization workflows (JupyterCon, PyPizza) and brings practical research experience to production engineering. Notably, he has deep hands-on experience bridging GPU DataFrame APIs with visualization pipelines to unlock interactive performance on massive datasets.
9 years of coding experience
4 years of employment as a software developer
Bachelor of Engineering (BE), Computer Engineering, 70%, Bachelor of Engineering (BE), Computer Engineering, 70% at St. Francis Institute Of TechnologyMaster of Science (MS), Computer Science, 3.73, Master of Science (MS), Computer Science, 3.73 at New York UniversityHSC, Science, 75%, HSC, Science, 75% at Sir Parashurambhau College, Pune
English, Hindi, Marathi
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (16)
data-visualizations10
gpu-programming10
cudf10
data-visualization10
data-visualisation10
numba10
python10
cupy10
data-engineering9
pandas8
raster7
datashader7
rasterizing7
rasterizer7
rasterize7
Programming languages (9)
Github contributions (5)
holoviz/datashader
Aug 2020 - Mar 2022
Quickly and accurately render even the largest data.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:8 reviews, 5 commits, 4 PRs in 1 year 7 months
Contributions summary:Ajay primarily contributed to integrating and updating the project's interaction with cuDF, a GPU-accelerated DataFrame library. They addressed API updates, minimum version requirements, and efficient data conversion between cuDF and other array formats like cupy. Their work involved modifying code within multiple modules, including those related to data processing and glyph rendering, to leverage cuDF's capabilities for accelerated computation, and fix an incorrect version comparison. Additionally, the user made updates to support cupy integration in the spread and dynspread functions.
renderrasterizationdata-visualizationsdatashaderholoviz
collabassess/Xblocks-in-OpenEdx
Oct 2017 - Feb 2018
Contributions:113 commits, 52 PRs, 104 pushes in 3 months
installationopenedx
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.