Data Science
[PAST EVENT] CS Schmidt Distinguished Talk: Miryung Kim
Access & Features
- Open to the public
Title: Software Engineering for Big Data and Heterogeneous Computing
Abstract: The rise of big data, machine learning, and AI necessitates a re-evaluation of existing software engineering techniques to achieve desired developer productivity gains. Furthermore, specialized hardware accelerators like GPUs and FPGAs are now integral to the computing landscape. However, developing heterogeneous applications remains accessible to only a small subset of programmers with specialized hardware expertise. To enhance productivity and performance for both data-intensive and compute-intensive development, the software engineering community must design new waves of refactoring, testing, and debugging tools tailored for big data analytics and heterogeneous application development.
This talk overviews the software development challenges in this emerging domain of data-intensive, scalable, and heterogeneous computing. We present examples of automated software engineering techniques (debugging, testing, and refactoring) designed for this domain and share lessons learned from their development.
Bio: Miryung Kim is a Professor and Vice Chair of Graduate Studies in Computer Science at UCLA. Her research group focuses on software engineering for AI, big data, and hardware heterogeneity. She has mentored seven PhD students and postdocs who have gone on to become professors (at Columbia, Purdue, and two at Virginia Tech, among others). For her impact on nurturing the next generation of academics, she received the ACM SIGSOFT Influential Educator Award. She served as Program Co-Chair of the ACM International Conference on Foundations of Software Engineering (FSE 2022). She was a Keynote Speaker at ASE 2019 and ISSTA 2022 and has given Distinguished Lectures at CMU, UIUC, and other institutions.
Sponsored by: Computer Science