Shubham Agarwal
Senior Machine Learning Engineer at Entrupy
Bengaluru, Karnataka, India
Summary
🤩
Rockstar🎓
Top SchoolShubham Agarwal is a Senior Machine Learning Engineer based in Bengaluru with a decade of experience building computer vision and robotics solutions for automation. He has applied ML to production problems across startups and large tech—working on ads prediction at Twitter, research systems and open-source projects at Intel, and vision-driven products at Entrupy and Konica Minolta. Shubham contributes to prominent open-source work like Open3D, improving 3D file I/O and tensor handling for point clouds and meshes, reflecting a blend of low-level systems skill and applied ML. Comfortable across the stack from embedded drivers and Android integrations to research-grade policy learning for distributed robots, he pairs strong engineering rigor with practical deployment experience. His background combines an IIT Gandhinagar B.Tech and an MS from UCLA, underscoring solid academic foundations driving real-world computer vision impact.
10 years of coding experience
8 years of employment as a software developer
Bachelor of Technology (B.Tech.), Electrical Engineering, 8.84/10, Bachelor of Technology (B.Tech.), Electrical Engineering, 8.84/10 at Indian Institute of Technology GandhinagarMaster's degree, Electrical Engineering, 3.81/4, Master's degree, Electrical Engineering, 3.81/4 at University of California, Los Angeles
English, Hindi, French
Github Skills (13)
file-processing10
file-handling10
c-language10
tensor10
cprogramming-language10
point-cloud10
file-access10
fileio10
3d9
cpp9
ply9
mesh-processing8
computer-graphics7
Programming languages (4)
Github contributions (5)
isl-org/Open3D
Oct 2020 - Sep 2021
Open3D: A Modern Library for 3D Data Processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:48 reviews, 20 commits, 24 PRs in 10 months
Contributions summary:Shubham primarily contributed to the `open3d` library by implementing and modifying file I/O functionalities, specifically for reading and writing point clouds and triangle meshes using the PTS and PLY file formats. Their contributions included enhancing the library's capability to handle custom attributes within point clouds, fixing bugs, and improving tensor handling during file operations. They also updated the documentation and test infrastructure to reflect the changes.
python3d-perceptionodometrytensorflowpointcloud
ishan793/EE239-Big-Data-Analysis
Jan 2016 - Feb 2016
Contributions:41 pushes in 1 month
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