GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments. - Michael Wang 003; Tingjun Yang; Maria Acosta Flechas; Philip C. Harris; Benjamin Hawks; Burt Holzman; Kyle Knoepfel; Jeffrey D. Krupa; Kevin Pedro; Nhan Tran (Frontiers Big Data, 2020)

A machine learning approach to the detection of ghosting and scattered light artifacts in dark energy survey images. - Chihway L. Chang; Alex Drlica-Wagner; S. M. Kent; Brian Nord; Donah Michelle Wang; Michael H. L. S. Wang (Astron. Comput., 2021)

In-network fractional calculations using P4 for scientific computing workloads. - Shivam Patel; Rigden Atsatsang; Kenneth M. Tichauer; Michael H. L. S. Wang; James B. Kowalkowski; Nik Sultana (EuroP4@CoNEXT, 2022)

DeepGhostBusters: Using Mask R-CNN to detect and mask ghosting and scattered-light artifacts from optical survey images. - Dimitrios Tanoglidis; Aleksandra Ciprijanovic; Alex Drlica-Wagner; Brian Nord; Michael H. L. S. Wang; A. Jacob Amsellem; K. Downey; S. Jenkins; Diana Kafkes; Z. Zhang (Astron. Comput., 2022)

Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing. - Tejin Cai; Kenneth Herner; Tingjun Yang; Michael Wang 003; Maria Acosta Flechas; Philip C. Harris; Burt Holzman; Kevin Pedro; Nhan Tran (Comput. Softw. Big Sci., 2023)

Shape-shifting Elephants: Multi-modal Transport for Integrated Research Infrastructure. - Nik Sultana; Yatish Kumar; Chin Guok; James B. Kowalkowski; Michael H. L. S. Wang (HotNets, 2024)