Robert Nishihara
Summary
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RockstarRobert Nishihara is a Co-Founder and seasoned software engineer based in the San Francisco Bay Area with 12 years of experience building and scaling distributed systems and AI infrastructure. He co-founded and led Anyscale and is a prominent contributor to Ray, the widely used AI compute engine, where his work emphasizes reliability and performance at the core runtime level. Robert pairs founder-level product and company leadership with deep systems engineering — from implementing non-blocking fetches and core-dump handling to hardening low-level I/O and tests — and has applied similar improvements to Apache Arrow/Plasma and distributed ML tooling. His background includes hands-on reinforcement-learning tooling and numerical libraries, plus research internships at Facebook AI Research, Microsoft Research, Google and other high-profile organizations, underscoring a blend of research rigor and production instincts.
13 years of coding experience
Github Skills (36)
algorithms10
serializable10
c-language10
system-programming10
serializer10
python10
networking10
reinforcement-learning10
numpy10
scala210
serialization10
scala10
apache-arrow10
deserialization10
plasmoid10
Programming languages (7)
Github contributions (5)
ray-project/tutorial
Apr 2017 - Oct 2019
Role in this project:
Back-end Developer
Back-end DeveloperContributions:45 commits, 67 PRs, 22 pushes in 2 years 5 months
Contributions summary:Robert implemented exercises, including adding example models and updating exercises, and modifying rollouts.py with functions like rollouts, add_advantage_values, and collect_samples using NumPy and Ray for a reinforcement learning project. They also modified exercises to use the actor API. These actions involved manipulating reinforcement learning environments and implementing features using Python. The work indicates a focus on developing components for reinforcement learning and possibly building the underlying systems for Reinforcement Learning algorithms.
amplab/SparkNet
Nov 2015 - Apr 2016
Distributed Neural Networks for Spark
Role in this project:Backend Developer
Backend DeveloperContributions:133 commits, 63 PRs, 759 pushes in 5 months
Contributions summary:Robert contributed to the development of the `sparknet` project, which focuses on distributed neural networks for Spark. Their primary contributions involved implementing a new `NDArray` library in Scala, essential for handling numerical computations within the neural network framework. Additionally, they made improvements to existing code, specifically addressing whitespace issues.
neural-networksmachine-learningsparkscaladistributed
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