Associate Researcher

Email: emma002@sjtu.edu.cn


Research Interests:Electric health record mining, Clinical AI


  • Dr Yang graduated with a DPhil degree in Signal Processing of Mechanical Engineering at Shanghai Jiao Tong University in 2013, jointly supervised by Professor Guang Meng and Zhike Peng. From 2007 to 2008, she studied at the Center for Intelligent Maintenance Systems, the University of Cincinnati in America, supervised by Professor Jay Lee. After Dphil, Dr Yang worked as a postdoctoral fellow and a lecturer at Shanghai Jiao Tong University.

  • Followed by a two-year K.C. Wong Fellow at the Computational Health Informatics Lab, the University of Oxford, Dr Yang was appointed as Senior Research Associate at the University of Oxford in 2018, meanwhile, she was also in charge of the Digital Health research group at Oxford Suzhou Centre for Advanced Research, supervised by Professor David Clifton.

  • In 2021, Dr Yang was appointed as Associate Professor in the School of Public Health, Shanghai Jiao Tong University. She has received early-career funding from the National Science Foundation of China, Postdoctoral Funding of China, and the K.C. Wang Fellowship, and selected as a candidate of Shanghai high-level overseas talents. Her research focuses on the development of multi-modal data analysis for healthcare.

Research Areas

  • Sequencing data mining and representation learning

  • Multimodal healthcare data mining and knowledge discovery

  • Time series modelling methods


  • Mertes, Gert, Yuan Long, Zhangdaihong Liu, Yuhui Li, Yang, Yang, and David, A. Clifton. "A Deep Learning Approach for the Assessment of Signal Quality of Non-Invasive Foetal Electrocardiography." Sensors 22, no. 9 (2022): 3303.

  • Walker, Timothy M., Paolo Miotto, Claudio U. Köser, Philip W. Fowler, Jeff Knaggs, Zamin Iqbal, Martin Hunt, CRyPTIC Consortium. "The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: A genotypic analysis." The Lancet Microbe 3, no. 4 (2022): e265-e273.

  • Yang, Yang, Timothy M. Walker, A. Sarah, Walker, Daniel J. Wilson, Timothy EA Peto, Derrick W. Crook, Farah Shamout, Tingting Zhu, and David A. Clifton. "DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis." Bioinformatics 35, no. 18 (2019): 3240-3249.

  • Kouchaki, Samaneh, Yang, Yang, Timothy, M. Walker, A. Sarah Walker, Daniel J. Wilson, Timothy EA Peto, Derrick W. Crook, CRyPTIC Consortium, and David A. Clifton. "Application of machine learning techniques to tuberculosis drug resistance analysis." Bioinformatics 35, no. 13 (2019): 2276-2282.

  • Yang, Yang, Katherine E. Niehaus, Timothy, M. Walker, Zamin, Iqbal, A. Sarah, Walker, Daniel J. Wilson, Tim EA Peto et al. "Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data." Bioinformatics 34, no. 10 (2018): 1666-1671.

  • CRyPTIC Consortium and the 100,000 Genomes Project. "Prediction of susceptibility to first-line tuberculosis drugs by DNA sequencing." New England Journal of Medicine 379, no. 15 (2018): 1403-1415.

  • Kouchaki, Samaneh, Yang, Yang, Alexander, Lachapelle, Timothy, M. Walker, A. Sarah Walker, CRyPTIC Consortium, Timothy EA Peto, Derrick W. Crook, and David A. Clifton. "Multi-label random forest model for tuberculosis drug resistance classification and mutation ranking." Frontiers in microbiology 11 (2020): 667.

  • Yang, Yang, Zhike, Peng, Xingjian, Dong, Wenming, Zhang, and David, A. Clifton. "Component isolation for multi-component signal analysis using a non-parametric gaussian latent feature model." Mechanical Systems and Signal Processing 103 (2018): 368-380.

  • Yang, Yang, Zhike, Peng, Wenming, Zhang, and Guang, Meng. "Parameterised time-frequency analysis methods and their engineering applications: A review of recent advances." Mechanical Systems and Signal Processing 119 (2019): 182-221.

  • Yang, Yang, Zhike, Peng, Xingjian, Dong, Wenming, Zhang, and Guang, Meng. "Nonlinear time-varying vibration system identification using parametric time–frequency transform with spline kernel." Nonlinear dynamics 85, no. 3 (2016): 1679-1694.

  • Yang, Yang, Zhike, Peng, Wenming, Zhang, Guang Meng, and Ziqing, Lang. "Dispersion analysis for broadband guided wave using generalized warblet transform." Journal of Sound and Vibration 367 (2016): 22-36.

  • Yang, Yang, Xinjian Dong, Zhike Peng, Wenming Zhang, and Guang Meng. "Vibration signal analysis using parameterized time–frequency method for features extraction of varying-speed rotary machinery." Journal of Sound and Vibration 335 (2015): 350-366.

  • Yang, Yang, Xingjian Dong, Zhike Peng, Wenming Zhang, and Guang Meng. "Component extraction for non-stationary multi-component signal using parameterized de-chirping and band-pass filter." IEEE Signal Processing Letters 22, no. 9 (2014): 1373-1377.

  • Yang, Yang, Z. K. Peng, X. J. Dong, W. M. Zhang, and G. Meng. "General parameterized time-frequency transform." IEEE Transactions on Signal Processing 62, no. 11 (2014): 2751-2764.

  • Yang, Yang, Zhike, Peng, Xingjian Dong, Wenming, Zhang, and Guang Meng. "Application of parameterized time-frequency analysis on multicomponent frequency modulated signals." IEEE Transactions on Instrumentation and Measurement 63, no. 12 (2014): 3169-3180.

  • Yang, Yang, Wenming, Zhang, Zhike, Peng, and Guang Meng. "Multicomponent signal analysis based on polynomial chirplet transform." IEEE transactions on Industrial Electronics 60, no. 9 (2012): 3948-3956.

  • Yang, Yang, Z. K. Peng, G. Meng, and W. M. Zhang. "Spline-kernelled chirplet transform for the analysis of signals with time-varying frequency and its application." IEEE Transactions on Industrial Electronics 59, no. 3 (2011): 1612-1621.

  • Yang, Yang, Zhike, Peng, Wenming, Zhang, and Guang Meng. "Frequency-varying group delay estimation using frequency domain polynomial chirplet transform." Mechanical Systems and Signal Processing 46, no. 1 (2014): 146-162.

  • Zhu, Tingting, Alistair EW Johnson, Yang, Yang, Gari D. Clifford, and David A. Clifton. "Bayesian fusion of physiological measurements using a signal quality extension." Physiological measurement 39, no. 6 (2018): 065008.

  • Zhu, Tingting, Glen Wright Colopy, Clare Macewen, Katherine Niehaus, Yang, Yang, Chris W. Pugh, and David A. Clifton. "Patient-specific physiological monitoring and prediction using structured Gaussian processes." IEEE Access 7 (2019): 58094-58103.

  • Yang, Jenny, Andrew AS Soltan, Yang, Yang, and David A. Clifton. "Algorithmic Fairness and Bias Mitigation for Clinical Machine Learning: Insights from Rapid COVID-19 Diagnosis by Adversarial Learning." medRxiv (2022).

  • Rohanian, Omid, Samaneh Kouchaki, Andrew, Soltan, Jenny, Yang, Morteza Rohanian, Yang, Yang, and David Clifton. "Privacy-aware Early Detection of COVID-19 through Adversarial Training." arXiv preprint arXiv:2201.03004 (2022).

  • Soltan, Andrew AS, Jenny Yang, Ravi, Pattanshetty, Alex Novak, Yang, Yang, Omid, Rohanian, Sally Beer, Marina A. Soltan et al. "Real-world evaluation of AI driven COVID-19 triage for emergency admissions: External validation & operational assessment of lab-free and high-throughput screening solutions." medRxiv (2021).