Andrew Harp
Chief Technology Officer at Curie
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAndrew Harp is a seasoned technology leader and Chief Technology Officer based in San Francisco with 16 years of experience building AI-driven systems across industry and research. He brings deep expertise in machine learning, computer vision, graphics, and game AI from a long tenure at Google where he contributed to projects ranging from Everyday Robots and Google Brain to Google Glass and Maps. Andrew pairs strategic leadership with hands-on engineering—his open-source contributions include substantive backend work on the XLA machine learning compiler and full-stack improvements to TensorBoard’s visualization tooling. He has a track record of shipping low-level performance fixes and high-level UX improvements, demonstrating fluency across compilers, TypeScript front ends, and robotics perception. Trained with an MS in Computer Science from UT Austin and a BS from Georgia Tech, he combines academic rigor with product-focused delivery. Colleagues describe him as an engineer who comfortably moves between research prototypes and production-grade systems, often surfacing subtle algorithmic improvements that boost real-world performance.
16 years of coding experience
18 years of employment as a software developer
MS Computer Science, MS Computer Science at The University of Texas at AustinBachelor of Science Computer Science, Bachelor of Science Computer Science at Georgia Institute of Technology
Github Skills (15)
xla10
compiler10
typescript10
c-language10
typescripts10
tensorflow10
cprogramming-language10
typescript-types10
computer-engineering9
javascript9
debugging9
polymer8
optimization8
front-end-development8
python4
Programming languages (6)
Github contributions (5)
tensorflow/tensorboard
Jul 2016 - Mar 2017
TensorFlow's Visualization Toolkit
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:10 commits in 7 months
Contributions summary:Andrew contributed to the `tensorboard` repository, which is TensorFlow's visualization toolkit. The commits show modifications to TypeScript code, specifically within the `components/tf-storage` and `components/tf-graph` directories. The changes include adding and modifying functionalities related to URI storage, Polymer component initialization and observers, and updating graph demo components. The user also addressed conflicts and fixed indentation in the `__main__.py` file, indicating familiarity with backend aspects.
tensorflowvisualization
openxla/xla
Feb 2017 - Jan 2018
A machine learning compiler for GPUs, CPUs, and ML accelerators
Role in this project:Back-end Developer
Back-end DeveloperContributions:11 commits in 11 months
Contributions summary:Andrew's commits primarily involve changes to the XLA compiler's source code. These modifications include bug fixes, code refactoring, and the implementation of new functionalities related to mathematical operations like `Pow`, `SqrtF32`. The changes span across various files, including header and source files in the client and service directories. The user also addresses merge conflicts and integrates changes from github, indicating ongoing development and maintenance of the compiler.
compilermachine-learning
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.