Dr. Wenqian Dong is an assistant professor in the EECS department at Oregon State University. She earned her Ph.D. in EECS at the University of California, Merced, in Spring 2022. Recently, she is selected for the IEEE-CS Technical Community on High Performance Computing (TCHPC) Early Career Researchers Award for Excellence in High Performance Computing. Her research focuses on three main areas. She has contributed significantly to scientific machine learning, particularly in using machine learning to speed up HPC applications. Her work is showcased in conferences like SC'19 and SC'20. Wenqian has excelled in automatic machine learning, concentrating on creating machine learning models for HPC applications. Her papers in VLDB'21, HPDC'23, and ASPLOS'22 highlight her notable contributions. She's skilled in optimizing system performance, aiming to enhance HPC applications' quality and efficiency through system optimization. Her work presented at conferences like ICS'21, Eurosys'21, ICPP'18, and Parallel Computing'23 illustrates her dedication to this field. Her work has generated real impacts in the HPC community. For example, her work on power grid simulation using ML leads to 3.28 times performance improvement and highlighted Newswise as a DOE science innovation. Furthermore, Wenqian is committed to enrich the HPC community. Her commitment is apparent in her various roles as an organizer for ICPP'24, the MLBench'23 workshop, and as a member of the Technical Program Committee (TPC) for the SC'24, HPDC'24, CCGrid'24, IEEE Cloud 2023, IEEE Cluster 2023, AI4Science 2022 workshop, and the GPGPU 2023 workshop.