Arun Kumar

Associate Professor
Computer Science and Engineering
and Halicioglu Data Science Institute
and HDSI Faculty Fellow
University of California, San Diego
Email: akk018 [at] ucsd [dot] edu
Office: 3218 CSE (EBU3B) and 351 HDSI


Arun Kumar is an Associate Professor in the Department of Computer Science and Engineering and the Halicioglu Data Science Institute and an HDSI Faculty Fellow at the University of California, San Diego. He is a member of the Database Lab and Center for Networked Systems and an affiliate member of the AI Group. His primary research interests are in data management and systems for machine learning/artificial intelligence-based data analytics. Systems and ideas based on his research have been shipped as part of products from, or used internally by, multiple cloud, Web, and database systems companies, including Google, Facebook, Oracle, and VMware. He is a recipient of three SIGMOD research paper awards, six distinguished reviewer/metareviewer awards from SIGMOD/VLDB, the IEEE TCDE Rising Star Award, an NSF CAREER Award, a UCSD oSTEM Faculty of the Year Award, and research award gifts from Amazon, Google, Oracle, and VMware. His first PhD graduate received the ACM SIGMOD Jim Gray Doctoral Dissertation Award.

Curriculum Vitae | Research Blog | Youtube Channel | On Twitter | On Tumblr

Note: I am not currently looking for new advisees or mentees. Feel free to check out the research of other faculty at CSE or HDSI.

Recent News

  • New! 6/24: Congrats to my recent PhD graduate, Yuhao Zhang, on his ACM SIGMOD Distinguished PC Member award! I am also delighted to receive an ACM SIGMOD Distinguished Associate Editor award the same year.

  • New! 6/24: Gave a talk on my path to CS and career tips at the ForMIDABLE summer program for middle school students.

  • 1/24: Vraj's paper on studying and benchmarking the impact of categorical duplicates on ML is accepted to VLDB 2024!

  • 11/23: The Saturn paper on an optimized system to run finetuning / transfer learning of multiple large DL models / LLMs is accepted to VLDB 2024!


My current research focuses on the foundations of advanced data analytics systems that help make the process of building and deploying ML/AI-powered data analytics applications easier (improving the productivity of data scientists and ML/software engineers) and faster (improving runtime performance and introducing accuracy trade-offs). Thus, the key themes of my research are usability, developability, performance, and scalability. I enjoy working on problems that are motivated by real applications and are formally grounded. I also enjoy insightful conversations with practitioners on the frontlines of data analytics.

More details about my research are available on my research group webpage, including current projects, and all of our publications.

For a summary of my current research, you can also read this one-pager, listen to this podcast, or watch this talk video.




  • Kyle Luoma (PhD, CSE, UCSD); Co-advisor: Jingbo Shang

  • Xiuwen Zheng (PhD, CSE, USCD); Co-advisor: Amarnath Gupta

  • Animesh Kumar (MS, CSE, UCSD)


  • Kabir Nagrecha (PhD, CSE, UCSD; 2024); Co-advisor: Hao Zhang; First employment: Netflix

  • Yuhao Zhang (PhD, CSE, UCSD; 2023); First employment: Databricks

  • Pradyumna Sridhara (MS, CSE, UCSD, 2023); First employment: UCSD HDSI

  • Tanay Karve (MS, CSE, UCSD, 2022); First employment: Apple

  • Vignesh Nanda Kumar (MS, CSE, UCSD, 2022); First employment: ServiceNow

  • Supun Nakandala (PhD, CSE, UCSD, 2022); First employment: Databricks

  • Vraj Shah (PhD, CSE, UCSD, 2022); First employment: IBM Research Almaden

  • Liangde Li (MS, CSE, UCSD, 2022); First employment: TigerGraph

  • Tara Mirmira (MS, CSE, USCD, 2022); First employment: PhD at UCSD

  • Advitya Gemawat (BS, HDSI, UCSD, 2021); First employment: Microsoft NERD AI.

  • Kabir Nagrecha (BS, CSE, UCSD, 2021); First employment: PhD at UCSD.

  • Shaoqing Yi (BS, HDSI and Math, UCSD, 2021); First employment: PhD at UC Berkeley.

  • Side Li (MS, CSE, UCSD, 2021); First employment: Google.

  • Kevin Yang (BS, CSE, UCSD, 2020); First employment: MS at UPenn

  • David Justo (MS, CSE UCSD, 2019); Co-advisor: Nadia Polikarpova; First employment: Microsoft

  • Anthony Thomas (MS, CSE, UCSD, 2018); First employment: PhD at UCSD

  • Lingjiao Chen (MS, CS, UW-Madison, 2018); First employment: PhD at Stanford

  • Side Li (BS, CSE, UCSD, 2018); First employment: Amazon

  • Mingyang Wang (MS, CSE, UCSD, 2017); First employment: Amazon



  • Program Co-Chair (Research Track), ACM CODS-COMAD 2024

  • Associate Editor, ACM SIGMOD 2024

  • Associate Editor, Scalable Data Science Category, VLDB 2022, 2021 (Inaugural)

  • Co-Chair, Diversity and Inclusion, ACM SIGMOD 2021 (Inaugural)

  • Core Committee member, Diversity & Inclusion in DB Initiative, 2021 (Inaugural)

  • (Inaugural) Lead Organizer, SoCal DB Day 2018

  • Co-Chair, ACM SIGMOD Workshop on Data Management for End-to-End Machine Learning (DEEM) 2018

  • (Inaugural) Organizing Committee, ACM SIGKDD Workshop on Common Model Infrastructure (CMI) 2018

  • Organizing Committee, Extremely Large Databases (XLDB) 2018

Program Committee:

  • ACM SIGMOD: 2024, 2020, 2019, 2018, 2017

  • ACM CODS-COMAD: 2024

  • CIDR: 2023, 2022, 2021

  • IEEE ICDE 2023 Special Track Senior PC

  • ACM SIGMOD DEEM Workshop: 2023, 2022, 2021, 2020, 2019, 2017

  • VLDB: 2022, 2021, 2020, 2019, 2018

  • ACM SIGMOD HILDA Workshop: 2022

  • MLSys / SysML: 2020, 2019

  • ACM SIGMOD 2017 Demonstrations; Student Research Competition

  • IEEE ICDE 2017

  • USENIX HotCloud 2016

  • ACM SIGMOD 2016 Undergraduate Research Poster Competition

Reviewer / External:

  • ACM SIGMOD 2022

  • ACM Transactions on Database Systems (TODS) 2017, 2015

  • IEEE Transactions on Knowledge and Data Engineering (TKDE) 2014

Outreach Materials

Blog Posts and Talks:

Interviews and Panels:

News and Other Resources: