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Arun Kumar
Associate Professor
Computer Science and Engineering
and Halicioglu Data Science Institute
and HDSI Faculty Fellow
University of California, San Diego
Email: arunkk [at] eng [dot] ucsd [dot] edu
Office: 3218 EBU3B (CSE building)
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Bio
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 released as part of the Apache MADlib open-source library,
shipped as part of products from Cloudera, IBM, Oracle, and Pivotal, and used internally by Facebook,
Google, LogicBlox, Microsoft, and other companies.
He is a recipient of three SIGMOD research paper awards,
four 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.
Curriculum Vitae |
Research Blog |
On Twitter |
On Tumblr
Recent News
New! Huge congrats to Kabir on receiving a highly competitive Meta PhD Fellowship, the first UCSD student to receive one in the program's 10-year history!
New! 12/21: The Nautilus paper on optimized execution of deep transfer learning at scale,
part of the Cerebro project, is accepted to SIGMOD 2022.
Round and round go the models that learn and relearn from past knowledge!
9/21: Awarded early tenure and promoted to Associate Professor by UC San Diego. Excited to keep powering ahead at this truly amazing academic home!
Research
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.
Teaching
CSE 132C (formerly CSE 190): Database System Implementation:
Spring 2022,
Spring 2021,
Spring 2020,
Spring 2019,
Spring 2018,
Spring 2017
DSC 102: Systems for Scalable Analytics:
Winter 2022, Winter 2021, Winter 2020
CSE 234: Data Systems for Machine Learning (regularized version of CSE 291):
Fall 2021,
Fall 2020
CSE 232A: Graduate Database Systems: Fall 2019, Fall 2018
CSE 291: Advanced Data Analytics and ML Systems:
Winter 2019,
Winter 2018,
Winter 2017
CSE 239: Database Seminar: Fall 2021, Fall 2020, Fall 2019
CSE 290: Seminar on Integrative AI Engineering: Fall 2018
CSE 290: Seminar on Advanced Data Science: Fall 2017, Spring 2017
CS 564: Database Management Systems: Design and Implementation (Fall 2015 at UW-Madison)
Advising
Current:
Kabir Nagrecha (PhD, CSE, UCSD)
Kyle Luoma (PhD, CSE, UCSD)
Supun Nakandala (PhD, CSE, UCSD)
Vraj Shah (PhD, CSE, UCSD)
Xiuwen Zheng (PhD, CSE, USCD); Co-advisor: Amarnath Gupta
Yuhao Zhang (PhD, CSE, UCSD)
Yutong Shao (PhD, CSE, UCSD); Primary advisor: Ndapa Nakashole
Liangde Li (MS, CSE, UCSD)
Pradyumna Sridhara (MS, CSE, UCSD)
Vignesh Nanda Kumar (MS, CSE, UCSD)
Alumni:
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
Service
Organization:
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:
CIDR: 2023, 2022, 2021
VLDB: 2022, 2021, 2020, 2019, 2018
ACM SIGMOD: 2020, 2019, 2018, 2017
ACM SIGMOD DEEM Workshop: 2022, 2021, 2020, 2019, 2017
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:
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