Richard Yu is a UC Berkeley senior studying Computer Science and Data Science with a cognition emphasis, bringing nine years of hands-on software experience across distributed systems, AI, and full-stack projects. He contributes to high-profile open-source messaging platforms like Apache Pulsar and Kafka, where he has fixed critical bugs, improved consumer compatibility, and added operational controls that strengthen robustness at scale. As a CS instructor and tutor at Berkeley, he pairs deep systems knowledge (OS and architecture) with practical teaching and assessment experience, regularly designing exam questions and project reviews. Internship experience at Amazon Project Kuiper and Berkeley Lab complements his academic work with networked systems and scientific tooling expertise. Known for writing fault-injection tests and understanding internal database designs, he blends rigorous engineering with a knack for making complex distributed behaviors observable and reliable.
9 years of coding experience
1 year of employment as a software developer
Bachelor of Arts - BA, Computer Science, Data Science, Bachelor of Arts - BA, Computer Science, Data Science at University of California, Berkeley
Contributions:9 commits, 71 PRs, 531 comments in 2 years 3 months
Contributions summary:Richard contributed to the Apache Kafka project by addressing several issues related to the Kafka Connect JSON converter and the Kafka consumer. They fixed a schema mismatch in the JSON converter and added a timeout parameter to blocking consumer calls. Additionally, the user simplified state store recovery in Kafka Streams and improved stream time accuracy. These changes involved modifications across multiple Java files related to Kafka's core functionalities and related testing.
Apache Pulsar - distributed pub-sub messaging system
Role in this project:
Back-end Developer
Contributions:6 commits, 9 PRs, 143 comments in 4 months
Contributions summary:Richard contributed to the Apache Pulsar messaging system by addressing a NullPointerException in the BrokerService, improving the system's robustness. They also worked on the PulsarKafkaConsumer, adding configuration options for `auto.offset.reset` and modifying its behavior for greater compatibility with Kafka consumers. Furthermore, they implemented the addition of configuration options to disable auto-topic creation and created a REST endpoint to create non-partitioned topics.
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.
Request Free Trial
Richard Yu - Teaching Assistant (UCS2) at UC Berkeley Electrical Engineering & Computer Sciences (EECS)