Zhongqiang Chen

Sunnyvale, California, United States

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Summary

🤩

Rockstar

🎓

Top School

Zhongqiang Chen is a blockchain and AI-focused software engineer with a Ph.D. in Computer Science and roughly 4 years of recent experience building decentralized systems and machine-learned security and search solutions from Sunnyvale. He has deep expertise in Bitcoin, Hyperledger Fabric, and Ethereum fundamentals—consensus, crypto, P2P networks, and smart contracts—and architects cross-chain communication and alternative ledger structures like DAGs and block lattices. Earlier roles at Yahoo! and Fortinet saw him apply deep learning, CRFs, and classical ML to intent detection, NER, sentiment, image/video indexing, and intrusion detection, often creating massive labeled datasets and multi-label taxonomies to improve real-world performance. His open-source contributions include back-end refactors to Apache Celeborn to enhance MapPartition shuffle writes, reflecting practical systems work at scale. Comfortable spanning research and production, he combines rigorous academic training with applied engineering to detect zero-day threats and scale information retrieval in complex, heterogeneous environments.

4 years of coding experience

2 years of employment as a software developer

Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at New York University

Master’s Degree, Computer Science, Master’s Degree, Computer Science at Tsinghua University

Github Skills (8)

javas10

big-data10

spark10

shuffle10

network-protocol10

java10

scala10

filesystem9

Programming languages (2)

JavaShell

Github contributions (5)

apache/celeborn

Nov 2022 - Jan 2023

Apache Celeborn is an elastic and high-performance service for shuffle and spilled data.

Role in this project:

Back-end Developer

Contributions:1 release, 146 reviews, 19 commits in 1 month

Contributions summary:Zhongqiang primarily contributed to the refactoring and extension of the `PushDataHandler` within the `apache/celeborn` repository, focusing on enhancements to support MapPartition shuffle writes. Their work involved adding message support, integrating handshake, region start, and region finish operations. The user also addressed issues related to transport client management and made necessary changes to the `FileWriter` class to support MapPartition functionality.

bigdataaccumuloparquetelasticconnector

zhongqiangczq/celeborn

Nov 2022 - Sep 2023

Celeborn provides an elastic and high-performance service for shuffle and spilled data.

Contributions:272 pushes, 90 branches in 10 months

elasticconnectorshuffleperformancefilebeat

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