Kuhu Shukla
Spark Rapids And GPUs at The Apache Software Foundation
Urbana-Champaign Area United States
Summary
🤩
Rockstar🎓
Top SchoolKuhu Shukla is a software engineer with six years of experience focused on distributed systems, big data, and GPU-accelerated analytics. Currently at NVIDIA working on Spark Rapids and GPU integration, she brings deep expertise in Spark, RAPIDS, and performance engineering from prior senior roles and a stint as Principal Engineer at Aviatrix. An active member and committer in the Apache Tez community since 2017, she combines open-source stewardship with hands-on production delivery in YARN/HDFS/Tez ecosystems from her time on Yahoo’s Hadoop core team. Her background spans networking automation and tooling at Juniper and Cisco, giving her practical systems-level fluency beyond pure data processing. Based in the Urbana-Champaign area and holding an MS in Computer Science from NC State, she pairs academic rigor with pragmatic engineering to accelerate large-scale data workflows on GPUs. Notably, her career bridges both cloud-native networking and cutting-edge GPU data‑processing, enabling cross-disciplinary solutions that squeeze out performance at scale.
6 years of coding experience
11 years of employment as a software developer
Master of Science (M.S.) Computer Science, Master of Science (M.S.) Computer Science at North Carolina State UniversityB.E. Computer Science, B.E. Computer Science at Manipal Institute of Technology
Github Skills (39)
opencl10
spark-ml10
spark10
python10
data-science10
r10
dataframes10
pandas10
cudf10
big-data10
apache10
java10
dataframe10
scala10
rapids10
Programming languages (4)
Github contributions (5)
kuhushukla/cudf
Nov 2019 - Jan 2021
cuDF - GPU DataFrame Library
Contributions:185 pushes, 32 branches in 1 year 2 months
cudadataframe-librarycudfgpu-accelerationmpi
kuhushukla/spark-rapids
Aug 2020 - Jan 2025
Spark RAPIDS plugin - accelerate Apache Spark with GPUs
Contributions:100 pushes, 29 branches in 4 years 5 months
gpu-accelerationtvmapachesparkapache-spark
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