Prof. Xiaoying Song, Wuhan University of Science and Technology, China
Xiaoying Song is a prominent Professor and Doctoral Supervisor in the School of Information Science and Engineering at Wuhan University of Science and Technology, China. Selected by the Hubei Chutian Scholar Program, she has made significant contributions to the fields of microelectronics and solid-state electronics. Dr. Song obtained her PhD in Microelectronics and Solid State Electronics from Wuhan University in 2017, following her Bachelor’s degree in Electronic Science and Technology from the same institution. Since joining Wuhan University of Science and Technology, she has advanced through various academic roles, including Lecturer and Associate Professor, before becoming a full Professor in 2024. Dr. Song teaches courses such as Signal and System, Digital Signal Processing, and Machine Learning and Data Mining, sharing her expertise with both undergraduate and graduate students. Her research interests focus on graph signal processing, graph learning, compound QSAR/QSPR model learning, and brain network analysis, positioning her as a key figure in innovative research and education in her field.
Professional Profile:
SCOPUS
Suitability of Xiaoying Song for the Best Researcher Award
Overview: Xiaoying Song is a highly qualified candidate for the Best Researcher Award, currently serving as a Professor and Doctoral Supervisor at the School of Information Science and Engineering at Wuhan University of Science and Technology. Her extensive educational background, impressive work experience, and significant contributions to research make her an exemplary candidate for this recognition.
🎓 Education Experience
- PhD in Microelectronics and Solid State Electronics
Wuhan University
September 2012 – June 2017
- BS in Electronic Science and Technology
Wuhan University
September 2008 – June 2012
💼 Work Experience
- Professor
School of Information Science and Engineering, Wuhan University of Science and Technology
October 2024 – Present
- Associate Professor
School of Information Science and Engineering, Wuhan University of Science and Technology
December 2020 – October 2024
- Lecturer
School of Information Science and Engineering, Wuhan University of Science and Technology
July 2017 – December 2020
- Postdoctoral Researcher
School of Information Science and Engineering, Wuhan University of Science and Technology
July 2017 – July 2019
📚 Courses Taught
- Signal and System (Undergraduate)
- Digital Signal Processing (Undergraduate)
- Machine Learning and Data Mining (Graduate)
🔬 Research Interests
- Graph Signal Processing
- Graph Learning
- Compound QSAR/QSPR Model Learning
- Brain Network Analysis
🏆 Achievements and Honors
- Selected by the Hubei Chutian Scholar Program
- Published numerous research papers in reputable journals
- Contributed to significant advancements in the fields of graph signal processing and data mining
Publication Top Notes:
Graph signal processing based nonlinear QSAR/QSPR model learning for compounds
Fusion of Individual and Population Graphs in a GNN Brain Disease Network
Classification of Alzheimer’s Disease via Spatial-Temporal Graph Convolutional Networks
Compound Property Learning Based on Molecular Fingerprints and Complex Network Metrics
Subspace learning based classification of ADHD patients