Prof Yan Li
Name | Prof Yan Li |
---|---|
Email Address | yan.li@unisq.edu.au |
Job Title | Professor (Computing) |
Qualifications | BEng HUST, MEng HUST, PhD Flinders |
Department | School of Mathematics, Physics and Computing |
Affiliations | Centre for Health Research |
ORCID | https://orcid.org/0000-0002-4694-4926 |
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Biography
Prof Yan Li is a full Professor in Artificial Intelligence (AI) in Computer Science discipline, the Associate Head (Research) and the Chair of Research Committee in the School of Mathematics, Physics and Computing at the University of Southern Queensland (UniSQ), Australia.
Yan received her PhD degree from the Flinders University of South Australia, Australia. Her research interests lie in the areas of AI, Machine Learning, Big Data and Internet Technologies, Network Security, Signal/Image Processing and EEG Research, etc. She has published 250+ high quality publications, supervised dozens of PhD students to completion, and obtained more than $3.5 million research grants from Australia government, industry and through international collaborations.
Prof Yan Li is the leader of UniSQ AI Research and the recipient of many research and teaching excellence awards, including 2012 Australia prestigious National Learning and Teaching Citation Award, 2008 Queensland Government Smart State-Smart Women Award, 2009 UniSQ Teaching Excellence Award, 2009 UniSQ Research Excellence Award, 2015-2018 Research Publication Excellence Awards, and 2021 HES Faculty Research Excellence Award.
Yan has served as an elected academic leader in many high-level university committees, such as UniSQ Academic Board Executive Committee and UniSQ Research Committee etc. Prof Yan Li is a current member in Australian Research Council College of Experts.
Employment
Position | Organisation | From | To |
---|---|---|---|
Professor | University of Southern Queensland | 2018 |
Expertise
Artificial Intelligence, Machine Learning, Big Data and Internet Technologies, Network Security, Signal/Image Processing and EEG Research
Teaching
Machine Learning, Network Security
Fields of Research
- 400607. Signal processing
- 460306. Image processing
- 460501. Data engineering and data science
- 461103. Deep learning
- 461106. Semi- and unsupervised learning
Current Supervisions
Research Title | Supervisor Type | Level of Study | Commenced |
---|---|---|---|
GRAPH NEURAL NETWORKS FOR CAUSALITY | Associate Supervisor | Doctoral | 2024 |
Optimise innovative financial products for Climate Risk Management in Agribusiness | Associate Supervisor | Doctoral | 2024 |
Depth of Anaesthesia assessment and Anaesthesia state change early warning system based on EEG data. | Associate Supervisor | Doctoral | 2024 |
Using Capsule Neural Network to Diagnose Internet Network Traffic | Principal Supervisor | Doctoral | 2024 |
Investigating the trade-offs between privacy, accuracy, and model performance in federated learning for privacy-sensitive domains | Principal Supervisor | Masters | 2023 |
Alzheimer's Disease Prediction based on Federated Learning | Principal Supervisor | Doctoral | 2023 |
Investigate the methods for fast incremental learning of machine learning models for misuse and anomaly-based intrusion detection in the cyber-attack domain. | Associate Supervisor | Doctoral | 2023 |
Advanced Machine Learning Models for EEG Signal Analysis in Assessing Depth of Anaesthesia | Principal Supervisor | Doctoral | 2023 |
Developing Deep Learning Methods for Detection and Segmentation of Brain Tumor using 3D and 4D Images | Principal Supervisor | Doctoral | 2022 |
The Chance-setup on Data Mining Results | Principal Supervisor | Doctoral | 2022 |
Human-centered Artificial Intelligence (AI) for Quality Education | Associate Supervisor | Doctoral | 2021 |
Rigorous Security for Flexible Workflow by Coherence and Proof-checking | Associate Supervisor | Doctoral | 2021 |
Epileptic Seizure Prediction Based on Electroencephalography | Principal Supervisor | Doctoral | 2020 |
Logical Conditions on Policies in the Internet of Things and Cyber-Physical Systems | Associate Supervisor | Doctoral | 2019 |
Completed Supervisions
Research Title | Supervisor Type | Level of Study | Completed |
---|---|---|---|
Deep learning based sleep stage classification studies | Principal Supervisor | Doctoral | 2024 |
MODELLING AND NUMERICAL INVESTIGATIONS OF TRANSCRANIAL FOCUSED ULTRASOUND STIMULATION | Associate Supervisor | Doctoral | 2023 |
Multi-Method Approaches for Sleep EEG Analysis and Sleep Stage Classification. | Principal Supervisor | Doctoral | 2023 |
Sleep Stages Classification Based on Graph Convolutional Networks Using Multi-type Bio-signals | Principal Supervisor | Doctoral | 2023 |
Real-Time Epilepsy Seizure Detection and Brain Connectivity Analysis using Electroencephalogram | Associate Supervisor | Doctoral | 2023 |
Investigating the effects of interactions of environmental factors on grain quality using statistical techniques | Principal Supervisor | Doctoral | 2021 |
Sleep characteristics and stages detection and analysis using Electroencephalogram (EEG) | Principal Supervisor | Doctoral | 2021 |
A data based approach for diagnosis and management of yield variability attributed to soil constraints | Associate Supervisor | Doctoral | 2020 |
Developing new techniques to improve licence plate detection systems for complicated and low quality vehicle images | Principal Supervisor | Doctoral | 2020 |
Brain network, modelling and corresponding EEG patterns for health and disease states | Associate Supervisor | Doctoral | 2020 |
Development of data intelligent models for electricity demand forecasting: Case studies in the state of Queensland, Australia | Associate Supervisor | Doctoral | 2020 |
Stakeholder security analysis - a new approach to security design with example application | Associate Supervisor | Doctoral | 2020 |
Development of Electroencephalogram (EEG) signals classification techniques | Principal Supervisor | Doctoral | 2019 |
Streamflow and soil moisture forecasting with hybrid data intelligent machine learning approaches: Case studies in the Australian Murray-Darling Basin | Associate Supervisor | Doctoral | 2018 |
Securing clouds using cryptography and traffic classification | Associate Supervisor | Doctoral | 2018 |
An intelligent recommender system based on short-term disease risk prediction for patients with chronic diseases in a telehealth environment | Associate Supervisor | Doctoral | 2018 |
EEG signals analysis and classification based on graph theory and statistical features | Principal Supervisor | Doctoral | 2017 |
Human head temperature and electric field investigations under ECT | Associate Supervisor | Doctoral | 2017 |
Numerical human head modelling and investigation for precise tDCS applications | Principal Supervisor | Doctoral | 2016 |
Project title | Details | Year |
---|---|---|
Australian Research Council (ARC) Discovery Project | This project aims to generate new knowledge and tools in global brain network modelling and deep learning technology. It addresses the significant issues in higher brain function state assessment using brain signal EEG. The project applies global brain networks to model brain dynamical activities as a whole, and assesses higher brain functions such as consciousness, fatigue, sleep, stress and depression, and their step by step evolution in real-time using innovative deep learning approaches. The expected outcomes are optimised brain network models and a platform technology. The intended results can be applied to greatly improve the sleep quality and productivity of general community, and the safety of workplace and transportation. $533,377 | 2024 |
Australian Research Council (ARC) Discovery Project | This project aims to develop a secured cybersecurity system for workflows and business processes, which enable organizations to provide flexible and more secure web-based services and business communication. The project expects to generate new knowledge, theoretic advancement and result in new technologies in the areas of internet of things and cybersecurity. $420,000 | 2023 |
Australian Department of Health Funded Project | The project is to develop an AI-assisted interactive and privacy-preserving system to reduce STI testing related barriers and facilitate linkage to care. $500,000 | 2022 |
Global Connection Program from Australian Academy of Technology and Engineering | Bridging Grant with Industry Partner Scheme. $120,000 | 2020 |
Industry Collaboration Research Investment Fund | Collaboration Research Fund from Shenzhen Delica Medical Equipment Co. Ltd. $543,227 | 2017 |