Karen Feng

Menlo Park, California, United States

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Summary

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Rockstar

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Top School

Karen Feng is a PhD student in Biomedical Informatics at Stanford with 12 years of software engineering experience bridging large-scale data systems and computational biology. Previously a senior software engineer at Databricks, she worked on Spark SQL compiler and healthcare-focused platform features while contributing significant back-end improvements and tests to cornerstone open-source projects like Apache Spark and Delta Lake. Her research background at Princeton includes published work on contextual bandits and scalable genomics methods, blending rigorous statistical thinking with production-grade systems engineering. Based in Menlo Park, she combines hands-on contributions to high-impact projects (e.g., adding SQL-exposed functions and Spark UI log paging) with ongoing research that tightens the loop between algorithmic innovation and real-world bioinformatics tooling.

12 years of coding experience

8 years of employment as a software developer

Doctor of Philosophy - PhD, Biomedical Informatics, Doctor of Philosophy - PhD, Biomedical Informatics at Stanford University School of Medicine

High School, High School at Monta Vista High School

Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Princeton University

English, Chinese

Github Skills (29)

unit-testing10

apache-spark10

spark10

delta-lake10

python10

testing10

big-data10

java10

scala10

javas10

uid10

front-end-development10

sql10

parquet10

bioinformatics10

Programming languages (6)

JavaRCSSScalaHTMLPython

Github contributions (5)

mesos/spark

Jul 2013 - Aug 2013

Lightning-fast cluster computing in Java, Scala and Python.

Role in this project:

Back-end Developer

Contributions:85 commits in 28 days

Contributions summary:Karen primarily contributed to the Spark UI, developing features for viewing and interacting with logs from executors. Their work focused on implementing log paging functionality, allowing users to navigate large log files efficiently. The commits also included refactoring and style improvements in the UI code, with the addition of byte ranges and the ability to view log files. Overall, the commits focus on enhancing the user interface for monitoring and debugging Spark applications.

pythoncluster-computinglightningsparkscala

bigdatagenomics/adam

Jun 2014 - Apr 2019

ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.

Role in this project:

Back-end Developer

Contributions:8 commits, 3 PRs, 2 comments in 4 years 11 months

Contributions summary:Karen primarily contributed to the back-end functionality of the ADAM genomics analysis platform. Their work focused on modifying the ADAMMain class to integrate global Parquet logging and removing unnecessary commands. They also created command categories, added a genome visualization tool and implemented a frequency visualization tool. Additionally, the user worked on allowing for the export of query name sorted SAM files.

pythonbioinformaticsadamlicensedbig-data

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