Jun Qi

Profile

Dr.Qi received the B.Sc. and M.Sc. degrees in computer science and technology from Changzhou University, Changzhou, China, in 2010 and 2013, respectively, and Ph.D. degree in computer science with the Department of Computing Sciences from Liverpool John Moores University, U.K., in 2019. She is currently a lecturer with the Department of Computer Science and Software Engineering at Xi’an JiaoTong-Liverpool University, Suzhou, China. She was a Postdoc Researcher with Oxford University, Oxford, U.K. Following her studies in 2019-2020, and a Research Associate with the Department of Computing and Mathematics, University of Ulster, Ulster, U.K., in 2013-2014. She has won the 2018 Chinese National Outstanding Self-funded International Student Scholarship.
Dr.Qi has successfully hosted a Key category of Chinese Returned Scholars Program funded by Ministry of Human Resources and Social Security (MOHRSS) and a sub-project of the National Key Research and Development Program funded by Ministry of Science and Technology (MOST). She also participated and managed a number of EPSRC and FP7 projects in the UK and the EU, including the assessment of brain deterioration in Patients with Alzheimer's disease, rehabilitation of patients with ankylosing spondylitis and the long-term human activity in healthy adults.
Her research focused on sensor-based data analysis for patients and healthy adults, using machine learning and expert systems. Special emphases of her work have been “lifelogging” physical activity patterns, and the analysis of time-series data from wearable sensors. Her research interests include predictive models for clinical applications, and investigating the effects of activity on Alzheimer's disease, Parkinson's disease, Stroke and other neurodegenerative conditions. She has published over 30 papers in the past five years including 4 Q1 journal papers and 1 ESI highly cited paper.
  • Qualifications

    • 2015-2019, PhD, Liverpool John Moores Unviersity, U.K.
  • Experience

    • 2020-present, Lecturer, Xi’an JiaoTong-Liverpool University, China
    • 2019-2020, Post-doctoral researcher, University of Oxford, U.K.
    • 2013-2014, Research Associate, University of Ulster, U.K.
  • Research interests

    • Healthcare informatics
    • AI clinical application
    • Wearable sensing
  • Articles

    • Qi, J., Yang, P., Newcombe, L., Peng, X., Yang, Y. and Zhao, Z., 2020. An overview of data fusion techniques for Internet of Things enabled physical activity recognition and measure. Information Fusion, 55, pp.269-280.
    • Qi, J., Yang, P., Hanneghan, M., Tang, S. and Zhou, B., 2018. A hybrid hierarchical framework for gym physical activity recognition and measurement using wearable sensors. IEEE Internet of Things Journal, 6(2), pp.1384-1393.
    • Qi, J., Yang, P., Hanneghan, M. and Tang, S., 2017. Multiple density maps information fusion for effectively assessing intensity pattern of lifelogging physical activity. Neurocomputing, 220, pp.199-209.
    • Qi, J., Yang, P., Min, G., Amft, O., Dong, F. and Xu, L., 2017. Advanced internet of things for personalised healthcare systems: A survey. Pervasive and Mobile Computing, 41, pp.132-149.
    • Qi, J., Yang, P., Waraich, A., Deng, Z., Zhao, Y. and Yang, Y., 2018. Examining sensor-based physical activity recognition and monitoring for healthcare using Internet of Things: A systematic review. Journal of biomedical informatics, 87, pp.138-153.
    • Yang, P., Antonacopoulos, A., Clausner, C., Pletschacher, S. and Qi, J., 2017. Effective geometric restoration of distorted historical document for large-scale digitisation. IET Image Processing, 11(10), pp.841-853.
    • Kong, X., Li, N., Lin, L., Xiong, P. and Qi, J., 2018. Relationship of stress changes and anomalies in OLR data of the Wenchuan and Lushan earthquakes. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(8), pp.2966-2976.
    • Shi, L., Lin, F., Yang, T., Qi, J., Ma, W. and Xu, S., 2014. Context-based ontology-driven recommendation strategies for tourism in ubiquitous computing. Wireless personal communications, 76(4), pp.731-745.
    • Zhou, B., Maines, C., Tang, S., Shi, Q., Yang, P., Yang, Q. and Qi, J., 2018. A 3-D security modeling platform for social IoT environments. IEEE Transactions on Computational Social Systems, 5(4), pp.1174-1188.
    • Cao, B., Zhao, J., Yang, P., Yang, P., Liu, X., Qi, J., Simpson, A., Elhoseny, M., Mehmood, I. and Muhammad, K., 2019. Multiobjective feature selection for microarray data via distributed parallel algorithms. Future Generation Computer Systems, 100, pp.952-981.
    • Yang, P., Liu, J., Qi, J., Yang, Y., Wang, X. and Lv, Z., 2019. Comparison and Modelling of Country-level Microblog User and Activity in Cyber-physical-social Systems Using Weibo and Twitter Data. ACM Transactions on Intelligent Systems and Technology (TIST), 10(6), pp.1-24.
    • Qi, J., Yang, P., Hanneghan, M., Fan, D., Deng, Z. and Dong, F., 2016. Ellipse fitting model for improving the effectiveness of life-logging physical activity measures in an Internet of Things environment. Iet Networks, 5(5), pp.107-113.
    • Yang, P., Qi, J., Zhang, S., Wang, X., Bi, G., Yang, Y., Sheng, B. and Yang, G., 2020. Feasibility study of mitigation and suppression strategies for controlling COVID-19 outbreaks in London and Wuhan. PloS one, 15(8), p.e0236857.
    • Fan, D., Yang, J., Zhang, J., Lv, Z., Huang, H., Qi, J. and Yang, P., 2018. Effectively measuring respiratory flow with portable pressure data using back propagation neural network. IEEE journal of translational engineering in health and medicine, 6, pp.1-12.
    • Yang, P., Yang, G., Liu, J., Qi, J., Yang, Y., Wang, X. and Wang, T., 2019. DUAPM: An Effective Dynamic Micro-Blogging User Activity Prediction Model Towards Cyber-Physical-Social Systems. IEEE Transactions on Industrial Informatics, 16(8), pp.5317-5326.
  • Proceedings

    • Yang, P., Qi, J., Yang, Y., Zhang, S. Rolling interventions for controlling COVID-19 outbreaks in the UK to reduce healthcare demand. International Conference on Knowledge Discovery and Data Mining : KDD 2020
    • Yang, P., Hanneghan, M., Qi, J., Deng, Z., Dong, F. and Fan, D., 2015, October. Improving the validity of lifelogging physical activity measures in an internet of things environment. In 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (pp. 2309-2314). IEEE.
    • Qi, J., Yang, P., Fan, D. and Deng, Z., 2015, October. A survey of physical activity monitoring and assessment using internet of things technology. In 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (pp. 2353-2358). IEEE.
    • Qi, J., Yang, P., Hanneghan, M., Latham, K. and Tang, S., 2017, June. Uncertainty Investigation for Personalised Lifelogging Physical Activity Intensity Pattern Assessment with Mobile Devices. In 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) (pp. 871-876). IEEE.
    • Qi, J., Yang, P., Hanneghan, M., Waraich, A. and Tang, S., 2018, July. A hybrid hierarchical framework for free weight exercise recognition and intensity measurement with accelerometer and ECG data fusion. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 3800-3804). IEEE.
    • Wang, X., Qi, J., Yang, Y. and Yang, P., 2019, July. A Survey of Disease Progression Modeling Techniques for Alzheimer's Diseases. In 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) (Vol. 1, pp. 1237-1242). IEEE.
    • Qi, J., Yang, Y., Peng, X., Newcombe, L., Simpson, A. and Yang, P., 2019, July. Experimental Analysis of Artificial Neural Networks Performance for Physical Activity Recognition Using Belt and Wristband Devices. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 2492-2495). IEEE.
  • Teaching activities

    • CPT103, Introduction to Database
  • Courses taught

    • CPT103, Introduction to Database
  • Awards and honours

    • 2018 Chinese government award for outstanding self-finance students abroad
    • ESI Highly Cited Paper Award in 2018
    • Best Student Paper Award, The 2017 International Workshop on Internet of Things and Big Data for Healthcare (IoTBDH), Exeter, UK, 2017
  • 电话

    +86 (0)512 81888766
  • 电子邮件

    Jun.Qi@xjtlu.edu.cn
  • 地址

    SD461(Science Building)
    Suzhou Dushu Lake Science and Education Innovation District
    Suzhou Industrial Park
    Suzhou
    P.R.China
    215123