Siddharth Gollapudi

Graduate Student Researcher

Cupertino, California, United States
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Summary

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Siddharth Gollapudi is a researcher-engineer with 11 years of experience building scalable search and ML systems, currently a Graduate Student Researcher in UC Berkeley EECS and a PhD candidate in Computer Science. He spent several years at Microsoft’s algorithms group pioneering hybrid and multivector extensions to DiskANN for large-scale vector search, translating research ideas into production-ready systems. His background includes internships at AWS (where he rewrote the ROS2 cross-compilation tool and productionized its metrics dashboard) and research work at Stanford applying TensorFlow models to proteomics and building cloud-backed search prototypes. Comfortable at the intersection of algorithms, systems, and applied ML, he combines rigorous academic training with hands-on engineering that ships. Based in Cupertino, he brings a habit of accelerating tooling and reproducibility—evident in dashboarding and performance wins—alongside deep interest in search and vector-based representations.
code11 years of coding experience
bookDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Berkeley
bookN/A, Computer Science, N/A, Computer Science at De Anza College
bookMonta Vista High School
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Github Skills (13)

database10
ros8
pokemongo7
script7
telegram6
slack6
python6
automation5
docker5
mqtt4
go3
algorithms2
approximate-nearest-neighbor-search1

Programming languages (4)

C++CSSRustPython

Github contributions (5)

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darvg/dotfiles

Sep 2015 - Feb 2023

Contributions:13 pushes, 4 branches in 7 years 5 months
darvg/DiskANN

Aug 2022 - Aug 2024

Scalable graph based indices for approximate nearest neighbor search
Contributions:2 PRs, 126 pushes, 26 branches in 2 years
graph-basedscalablenearest-neighborapproximate-nearest-neighbor-searchindices
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