Eric Zhu
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolEric Zhu is a PhD-trained software engineer in Seattle with 14 years of experience building algorithms and systems for data discovery and heterogeneous data management. He maintains two popular open-source libraries—most notably a datasketch toolkit implementing MinHash, HyperLogLog and related probabilistic structures—and has strengthened testing and robustness in Microsoft’s autogen agent framework. His work blends research-grade algorithm design with pragmatic backend engineering, including serialization, benchmarking, and structured-output improvements for production AI agents. Interested in disruptive data technologies, he focuses on scalable, approximate methods that make large, messy datasets tractable. Colleagues rely on him for deep technical judgment that crosses research and shipping-quality software.
14 years of coding experience
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at University of Toronto
Github Skills (16)
testing10
unit-testing10
data-structures10
data-serialization10
pytest10
computer-engineering10
python10
unit-test10
data-structure10
hyperloglog10
serialization10
numpy9
data-science9
code-analysis9
benchmark8
Programming languages (11)
Github contributions (5)
microsoft/autogen
Sep 2023 - Apr 2025
A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour
Role in this project:
Software Engineer & Test Automation
Software Engineer & Test AutomationContributions:19 releases, 2009 reviews, 859 PRs in 1 year 6 months
Contributions summary:Eric's commits primarily focused on enhancing the robustness and testing capabilities of the `flaml` submodule within the `autogen` repository. They implemented new tests for training logs, Python loggers, and the overall `flaml` module, thereby increasing test coverage. Furthermore, the user contributed to fixing code, clarifying API documentation and modifying core features such as structured output.
agenticagentic-agiagentsaiautogen
ekzhu/datasketch
Mar 2015 - Aug 2022
MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW
Role in this project:Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:28 releases, 31 reviews, 191 commits in 7 years 6 months
Contributions summary:Eric primarily contributed to the core data structure and related functionality of the project, evidenced by the addition and refinement of MinHash, HyperLogLog, and related similarity measures. Their work included the implementation and optimization of these probabilistic data structures, serialization capabilities, and benchmark creation for measuring performance and accuracy. The user also demonstrated expertise in applying these data sketches for cardinality estimation and Jaccard similarity calculations.
operationpythonensembledata-summarydatalog
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