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.

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.

💼 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

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

Mrs. Sabatina Criscuolo | Signal Processing Awards | Young Scientist Award

Mrs. Sabatina Criscuolo, University of Naples Federico II, Italy

Sabatina Criscuolo is an Italian biomedical engineer currently pursuing a Ph.D. in Information and Communication Technology for Health at the University of Naples Federico II, where she is affiliated with the National Research Council’s Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA). Her research focuses on the development of advanced artificial intelligence techniques to support precision medicine, with specific applications in neurodegenerative diseases, type 1 diabetes, and colorectal surgery. Sabatina has also collaborated internationally, including a visiting PhD position at the Applied Intelligence Research Centre in Dublin, where she worked on EEG artifact removal using variational autoencoders. With a strong academic background, she holds a Master’s degree in Biomedical Engineering, specializing in Bionic and Biorobotics, and has been involved in various research projects and initiatives aimed at enhancing health monitoring and rehabilitation technologies. In addition to her research activities, Sabatina contributes to the scientific community as a reviewer for multiple journals and has organized significant conferences in her field.

Professional Profile:

ORCID

Research for Young Scientist Award Evaluation for Sabatina Criscuolo

Sabatina Criscuolo is a promising candidate for the Research for Young Scientist Award, given her strong academic background, ongoing research initiatives, and contributions to the field of biomedical engineering and artificial intelligence. Here are several key points that highlight her suitability for this award.

Academic Experience

Sabatina is currently engaged in research at the National Research Council – STIIMA in Lecco, Italy, focusing on advanced artificial intelligence techniques to support precision medicine. Her work involves developing AI algorithms for applications in electroencephalographic (EEG) analysis related to neurodegenerative diseases, type 1 diabetes, and colorectal surgery.

PhD Studies: Since January 2022, she has been pursuing her PhD, with her thesis submission planned for December 2024 and expected graduation in March 2025. She has also been a visiting PhD student at the Applied Intelligence Research Centre in Dublin, Ireland, where she worked on EEG artifact removal using variational autoencoders and explainable AI.

Education

Sabatina holds a Master’s degree in Biomedical Engineering with a focus on Bionic & Biorobotics, where she developed a wearable Brain-Computer Interface system for robot-assisted rehabilitation in children with ADHD. She also completed a Bachelor’s degree in Biomedical Engineering, focusing on innovative enzyme immobilization methods.

Research Collaborations

Her collaborative research spans several institutions, including the University of Salento, Temple University, and the Interdepartmental Research Centre on Management and Innovation in Healthcare at her home university.

Scientific Impact

As of July 2024, Sabatina has an H-index of 5 on Scopus, reflecting her contributions to topics such as EEG signal analysis and diabetes management.

Subspace learning based classification of ADHD patients