Zongheng Yang

zongheng@cs.berkeley.edu
Favorite coffee shops:
Verve, West Santa Cruz
Cosube, Portland
Coffee Collective, Copenhagen

I'm a PhD student in Berkeley's RISELab, where I'm advised by Ion Stoica and collaborate closely with Joe Hellerstein. I research applying advances in deep learning to computer systems.

In my previous life, I worked at Google Brain (TensorFlow & deep learning models; 2016-2017), Databricks (intern; 2014), and Twitter (intern; 2013). I received my Bachelors in CS and in math from UC Berkeley. During my undergrad, I worked on various big data systems in the AMPLab.

Publications

Earlier Work

Earlier Projects

  • Ray: contributed a fault-tolerant and highly available control-state storage (chain-replicated redis).
  • TensorFlow: my public work at Google Brain included working on TensorFlow. One of my contributions is a new checkpoint format with much better efficiency.
  • Succinct/ZipG: a data store that queries directly on compressed files. I worked on ZipG, a distributed graph store on top that focuses on memory-efficiency.
  • SparkR: an R front-end for Apache Spark. Talk: SparkR: Enabling Interactive Data Science at Scale. Spark Summit, June 2014, San Francisco.
  • Apache Spark: I was a Spark contributor, mostly on Spark SQL.