Alexander Wu
Operating Room Nurse
Berkeley, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAlexander Wu is an experienced operating room nurse based in Berkeley with 11 years in perioperative care, currently serving as Charge Nurse and Pediatric Orthopedic Lead at UCSF Medical Center. He brings deep practical expertise in sterilization, instrument processing, and both scrub and circulating roles at Level 1 trauma centers, complemented by ACLS and PALS certification. A strong clinical academic background (BS Nursing, magna cum laude, and a prior Human Biology degree from UCSD) underpins his patient-centered leadership and process improvements in the OR. Unusually for a practicing RN, he also contributes to high-profile open-source data and distributed systems projects—adding features to Modin and improving autoscaling in Ray—highlighting a rare blend of clinical operations and technical problem-solving. This mix of hands-on surgical workflow mastery and software-driven systems thinking makes him adept at optimizing clinical processes and cross-disciplinary collaboration.
11 years of coding experience
University of California San DiegoBachelor’s Degree, Nursing, 3.73 Magna Cum Laude, Bachelor’s Degree, Nursing, 3.73 Magna Cum Laude at Samuel Merritt UniversityAcalanes High School
Chinese
Github Skills (23)
autoscaling10
python10
dataframes10
pandas10
cloud-infrastructure10
dataframe10
distributed-computing10
amazon-s310
cluster-manager10
aws-s310
cluster-api10
clustering10
s3-bucket10
data-science9
operation9
Programming languages (10)
Github contributions (5)
ray-project/ray
Jan 2020 - Jan 2023
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:2 releases, 1220 reviews, 293 commits in 3 years
Contributions summary:Alexander contributed to the Ray autoscaler, improving its ability to launch nodes and scale up the cluster. They modified core components to properly handle edge cases and ensure a more stable and robust distributed environment. The contributions also addressed issues regarding resource management, particularly concerning the use of GPUs and other node-level configurations. The user made adjustments to the core components to address issues. They were also responsible for implementing a testing suite for autoscaling using the dashboard's metrics.
pythonconsistsruntimetensorflowserving
modin-project/modin
Jan 2019 - Apr 2019
Modin: Scale your Pandas workflows by changing a single line of code
Role in this project:Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:5 commits, 6 PRs, 22 comments in 2 months
Contributions summary:Alexander contributed significantly to the `modin` library, focusing on extending its functionality and improving its data ingestion capabilities. They implemented the `drop_duplicates` method for the DataFrame, adding core functionality and tests. Furthermore, the user integrated S3 support for reading CSV files, involving changes to input/output operations and incorporating new dependencies like s3fs. They also addressed bugs and refined existing components.
analyticspythonline-of-codedata-sciencedataframe
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