Kexin Rong

I am an Assistant Professor in the School of Computer Science at Georgia Tech. My lab studies systems and algorithms to improve the computational and human efficiency of large-scale data analytics and is part of the Georgia Tech database group. I also spend time at VMware Research Group as an affiliated researcher.

I am broadly interested in building systems and tools to help democratize data science, i.e., making it easy for non-experts to make sense and leverage the increasing large volumes of data by making the process more efficient and more accessible.

Previously, I completed my Ph.D. in CS from Stanford (advised by Peter Bailis and Philip Levis) and my B.S. in CS from Caltech.

I am actively looking for master and PhD students. If you are a GT student who is interested in working with me, please check out this page.

Email  /  Google Scholar  /  CV  /  Github  /  Lab Website

  • [Aug 2023] Congrats to Peng Li for winning the best research paper award at VLDB'23!!
  • [Aug 2023] Recognized as a distinguished reviewer for PVLDB Vol16.
  • [June 2023] EECS Rising Stars 2023 Workshop will be hosted at Georgia Tech. Apply by July 10!
  • [May 2023] Invited talk at UCSD Database Seminar.
  • [Oct 2022] Thanks Bosch Research for supporting our work!
  • [Aug 2022] I am honored to have received the Catherine M. and James E. Allchin Early Career Professorship in the College of Computing.
  • [Jun 2022] After Datadog, TimescaleDB has also published a blog post about using our work ASAP for smoothing their time series visualizations.
  • [Jun 2022] I honored to have received an Honorable Mention for the 2022 SIGMOD Jim Gray Doctoral Dissertation Award.
PhD Students
Publications and Preprints
Recent Talks
  • Towards a Human-Centric Approach to Machine Learning Lifecycle Management
    UCSD Database Seminar, May 2023, Virtual
  • Learned Indexing and Sampling for Improving Query Performance in Big-Data Analytics
    Stanford MLSys Seminar, April 2022, Virtual

Template Source.