Yue Zhang

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This project entails utilizing signal processing and statistical machine learning techniques to analyze asthma data extracted from electronic health records. The aim is to gain insights for assessing, ensuring adherence, and facilitating longitudinal monitoring. Additionally, active collaboration with clinical partners will be maintained to translate research findings into practical applications within clinical practice.

About me

I completed my PhD in Electronic and Electrical Engineering from the University of Leeds. My doctoral research centred on the development of an accurate and reliable Brain-Computer Interface system utilizing EEG signals. Currently, I am a research fellow at the University of Edinburgh, specializing in Asthma subtypes clustering and predicting clinical outcomes using electronic health records through machine learning techniques.

Publications

• Zhang Y, Qian K, Xie SQ, Shi C, Li J, Zhang ZQ. SSVEP-Based Brain-Computer Interface Controlled Robotic Platform With Velocity Modulation. IEEE Trans Neural Syst Rehabil Eng. 2023;31:3448-3458. doi:10.1109/TNSRE.2023.3308778
• Zhang Y, Xie SQ, Wang H, Shi C and Zhang ZQ, Bayesian-Based Classification Confidence Estimation for Enhancing SSVEP Detection in IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-12, 2023, Art no. 6503612, doi: 10.1109/TIM.2023.3284952.
• Zhang Y, Xie SQ, Shi C, Li J and Zhang ZQ, Cross-Subject Transfer Learning for Boosting Recognition Performance in SSVEP-Based BCIs, in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, pp. 1574-1583, 2023, doi: 10.1109/TNSRE.2023.3250953.
• Zhang Y, Li Z, Xie SQ, Wang H, Yu Z and Zhang ZQ, Multi-Objective Optimization-Based High-Pass Spatial Filtering for SSVEP-Based Brain–Computer Interfaces, in IEEE Transactions on Instrumentation and Measurement, vol. 71, pp. 1-9, 2022, Art no. 4000509, doi: 10.1109/TIM.2022.3146950.
• Zhang Y, Xie SQ, Wang H and Zhang Z, Data Analytics in Steady-State Visual Evoked Potential-Based Brain–Computer Interface: A Review, in IEEE Sensors Journal, vol. 21, no. 2, pp. 1124-1138, 15 Jan.15, 2021, doi: 10.1109/JSEN.2020.3017491.
• Zhang Y, Xie SQ, Li Z, Zhao Y, Qian K and Zhang ZQ, CCA-based Spatio-temporal Filtering for Enhancing SSVEP Detection, 2022 IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks (BSN), Ioannina, Greece, 2022, pp. 1-4, doi: 10.1109/BSN56160.2022.9928502.
• Zhang Y, Zhang Z and Xie S, Multi-Objective Optimisation for SSVEP Detection, 2021 IEEE 17th International Conference on Wearable and Implantable Body Sensor Networks (BSN), Athens, Greece, 2021, pp. 1-4, doi: 10.1109/BSN51625.2021.9507041.