Teaching
Teaching Experience
TDT4200: Parallel Computing
Head Teaching Assistant (2019 - 2023)
Designed and implemented C++ and CUDA parallel computing problem sets and supplementary lectures. The problem sets focused on the latest optimization research in C++ and CUDA parallel programs and were consistently voted the best part of the class three years in a row.
Invited Talks & Presentations
Scalable Solvers Group
UC Berkeley • Invited Talk
March 15, 2023
Shared data and interfaces in Autotuning.
Stanford Compilers and Languages Lab
Stanford University • Invited Talk
June 20, 2022
The past, the present, and the future of Autotuning.
Cultural Psychology Lab
Stanford University • Invited Talk
September 10, 2021
Multimodal Large Language Models for Cultural Psychology.
iWAPT 2023
IPDPS • Paper Presentation
May 5, 2023
Towards a Benchmarking Suite for Kernel Tuners.
iWAPT 2022
IPDPS • Paper Presentation
May 3, 2022
Analyzing Search Techniques for Autotuning Image-based GPU Kernels: The Impact of Sample Sizes.
iWAPT 2021
IPDPS • Paper Presentation
May 4, 2021
Autotuning Benchmarking Techniques: A Roofline Model Case Study.
KAIST SE-Lab
KAIST • Invited Talk
November 18, 2022
Using a Statistical Evaluation Metric for Statistical Slicing.