Junqi Yin

Dr. Junqi Yin is a research staff member of the National Center for Computational Science at Oak Ridge National Laboratory. He obtained his Ph.D. in Computational Physics and M.S. in Statistics from the University of Georgia, and B.S. in Physics and Computer Science from Zhejiang University. His research interests range from AI foundation model, scalable machine learning/deep learning to materials science, statistical sampling algorithms especially Monte Carlo sampling.

FORGE: Pre-training Open Foundation Models for Science, SC’23, (2023) 

Accelerating Collective Communication in Data Parallel Training across Deep Learning Frameworks, USENIX NSDI’22, (2022)

Neural network-based order parameter for phase transitions and its applications in high-entropy alloys, Nature Computational Science 1, 686–693 (2021)