Arun Kumar Assistant Professor Computer Science and Engineering and Halicioglu Data Science Institute University of California, San Diego Email: arunkk [at] eng [dot] ucsd [dot] edu Office: 3218 EBU3B (CSE building)

Bio

Arun Kumar is an Assistant Professor in the Department of Computer Science and Engineering and the Halicioglu Data Science Institute at the University of California, San Diego. He is a member of the Database Lab and CNS 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 two SIGMOD research paper awards, three distinguished reviewer awards from SIGMOD/VLDB, the PhD dissertation award from UW-Madison CS, a Hellman Fellowship, two Google Faculty Research Awards, and an Oracle Labs Research Award.

Curriculum Vitae | Research Blog | On Twitter

Recent News

• New! 3/20: Both the Vista and SpeakQL papers are accepted to ACM SIGMOD 2020! Let our data systems open their eyes and ears to the era of "database perception."

• 2/20: The GDPRBench paper is accepted to VLDB 2020!

• 2/20: Interviewed by UCSD's Data Science Student Society on scalable analytics/ML systems and career options and on risks/benefits of AI and emerging tech.

• 2/20: Wrote a blog post on Inclusive CS Examples to help raise awareness of the importance of inclusion and avoiding exclusionary examples in CS concepts.

• 01/20: With help from my PhD students Supun, Vraj, and Yuhao, I have launched DSC 102: Systems for Scalable Analytics, the first course of its kind in the world aimed at data science juniors/seniors.

• 07/19: Gave a talk on data science careers to two groups of high school students, REHS summer workshop by SDSC and Big Data Summer Camp by QI at UCSD. PDF of slides

• Morgan & Claypool publishes a book I co-authored with Matthias Boehm and Jun Yang, Data Management in ML Systems, the first book on the emerging area of ML systems (PDF on M&C webpage; order hard copy).

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.

• CSE 132C (formerly CSE 190): Database System Implementation: Spring 2020, Spring 2019, Spring 2018, Spring 2017

• DSC 102: Systems for Scalable Analytics: Winter 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 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)

Current:

• Side Li (PhD, CSE, UCSD)

• Tara Mirmira (PhD, CSE, USCD)

• Supun Nakandala (PhD, CSE, UCSD)

• Vraj Shah (PhD, CSE, UCSD)

• Yuhao Zhang (PhD, CSE, UCSD)

• Advitya Gemawat (BS, HDSI, UCSD)

• Kabir Nagrecha (BS, CSE, UCSD)

• Kevin Yang (BS, CSE, UCSD)

Alumni:

• David Justo (BS, CSE UCSD, 2019); Co-advisor: Nadia Polikarpova

• Side Li (BS, CSE, UCSD, 2018)

• Anthony Thomas (MS, CSE, UCSD, 2018)

• Lingjiao Chen (MS, CS, UW-Madison, 2018)

• Mingyang Wang (MS, CSE, UCSD, 2017)

Research Service

Organization:

• Associate Editor, VLDB 2021

• Lead Organizer, SoCal DB Day 2018

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

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

• Organizing Committee, Extremely Large Databases (XLDB) 2018

Program Committee:

• ACM SIGMOD: 2020, 2019, 2018, 2017

• VLDB: 2021, 2020, 2019, 2018

• ACM SIGMOD DEEM Workshop: 2020, 2019, 2017

• 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:

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

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