· 個(gè)人簡(jiǎn)介
楊揚(yáng)，副研究員,。長(zhǎng)期從事信號(hào)處理與人工智能在醫(yī)療健康衛(wèi)生領(lǐng)域的理論方法和應(yīng)用研究,。獲得國(guó)自然青年基金資助、中國(guó)博士后基金,、王寬誠(chéng)研究基金資助,、入選上海市海外高層次人才計(jì)劃、參與國(guó)家級(jí)和省部級(jí)多項(xiàng)課題研究,。研究成果發(fā)表在NEJM,、Lancet Digital Health、Lancet Microbiology ,、Briefing in Bioinformatics,、Bioinformatics、IEEE Transaction in Signal Processing等國(guó)際雜志,，累積發(fā)表SCI論文20余篇,，申請(qǐng)專利2項(xiàng)。為參與世界衛(wèi)生組織發(fā)布的第一份《結(jié)核分枝桿菌基因組突變及其與耐藥性關(guān)聯(lián)的目錄》,，參與編寫專著《Machine Learning for Healthcare Technologies》,。為擔(dān)任Breifing in Bioinformatics、Journal of Biomedical and Health Informatics,、Bioinformatics等雜志審稿人,。人才培養(yǎng)方面，2018至2021年擔(dān)任牛津大學(xué)Kellogge學(xué)院思政老師,；2021年指導(dǎo)牛津大學(xué)高等研究院(蘇州）電子健康課題組3名成員參加IEEE COVID-19生物信息藥物靶向挑戰(zhàn)賽并獲勝,；2020至2021共同指導(dǎo)培養(yǎng)兩位研究生申請(qǐng)到牛津大學(xué)Clarendon獎(jiǎng)學(xué)金攻讀博士學(xué)位
本科與博士均畢業(yè)于上海交通大學(xué)，2013年獲工學(xué)博士,；2007至2008年在美國(guó)辛辛那提大學(xué)智能維護(hù)系統(tǒng)中心交流學(xué)習(xí),；博士畢業(yè)后在上海交通大學(xué)機(jī)械系統(tǒng)和振動(dòng)國(guó)家重點(diǎn)實(shí)驗(yàn)室開展博士后工作，后就職于上海交通大學(xué)機(jī)械與動(dòng)力工程學(xué)院,；2015至2017年在牛津大學(xué)醫(yī)療健康計(jì)算研究中心擔(dān)任王寬誠(chéng)研究員,；2018至2021年在牛津大學(xué)工程系擔(dān)任Senior Research Associate，同時(shí)負(fù)責(zé)牛津大學(xué)高等研究院（蘇州）電子健康課題組,；2021年12月加入上海交通大學(xué)醫(yī)學(xué)院公共衛(wèi)生學(xué)院,。
· 研究領(lǐng)域
(1) 測(cè)序數(shù)據(jù)挖掘與表征學(xué)習(xí)
(2) 醫(yī)療健康多模態(tài)數(shù)據(jù)挖掘與融合
(3) 健康衛(wèi)生數(shù)據(jù)表征學(xué)習(xí)與知識(shí)發(fā)現(xiàn)
(4) 時(shí)間序列建模與方法研究
主要發(fā)表論文：
1. Yang, Y., Walker, T.M., Walker, A.S., et al, “DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis", Bioinformatics, 35(18), pp. 3240-3249, 2019.
2. Kouchaki, S., Yang, Y.*, Walker, T.M., Walker, S., Wilson, D.J., Peto, T.E.A., Crook, D.W., and Clifton, D.A., “Application of Machine Learning Techniques to Tuberculosis Drug Resistance Analysis”, Bioinformatics, 35(13), pp. 2276–2282, 2019.
3. Yang, Y., Niehaus, K.E., Walker, T.M., et al, “Machine Learning for Classifying Tuberculosis Drug-Resistance from DNA Sequencing Data", Bioinformatics, 34 (10), pp. 1666–1671, 2018.
4. Allix-Beguec, C., ..., Clifton, D.A., Yang, Y., ..., Zhu, B. “Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing”, New England Journal of Medicine 379(15), pp. 1403-1415, 2018. (Co-corresponding author）
5. Samaneh K., Yang, Y., Walker, T.M., Walker, A.S., CRyPTIC Consortium, Peto, T.E.A., Crook, D.W., and Clifton, D.A., “Multi-Label Random Forest Model for Tuberculosis Drug Resistance Classification and Mutation Ranking”, Frontiers in Microbiology, 22 April 2020, https://doi.org/10.3389/fmicb.2020.00667.
6. Yang, Y., Peng, Z., Dong, X., Zhang, W., and Clifton, D.A., “Component Isolation for Multicomponent Signal Analysis Using a Non-parametric Gaussian Latent Feature Model", Mechanical Systems and Signal Processing, 103, pp. 368-380, 2018.
7. Yang, Y., Peng, Z., Zhang, W., Meng G. “Parametric Time-frequency Analysis Methods and their Engineering Applications: A Review of Recent Advances", Mechanical Systems and Signal Processing, 119, pp. 182-221, 2019.
8. Yang, Y., Peng, Z. K., Dong, X. J., Zhang, W. M., Meng, G., “Nonlinear Time-varying Vibration System Identification Using Parametric Time-frequency Transform with Spline Kernel". Nonlinear Dynamics, 85(3), pp. 1679-1694, 2016.
9. Yang, Y., Peng, Z. K., Zhang, W. M., Meng, G., Lang, Z. Q. “Dispersion Analysis for Broadband Guided Wave Using Generalized Warblet Transform", Journal of Sound and Vibration, 367, pp. 22-36,2016.
10. Yang, Y., Dong, X. J., Peng, Z. K., Zhang, W. M., Meng, G., “Vibration Signal Analysis Using Parameterized Time-frequency Method for Feature Extraction of Varying-speed Rotary Machinery", Journal of Sound and Vibration, 332(20), pp. 350-366, 2015.
11. Yang, Y., Dong, X. J., Zhang, W. M., Peng, Z. K., Meng, G., “Component Extraction for Non-Stationary Multi-Component Signal Using Parametrized De-chirping and Band-pass Filter", IEEE Signal Processing Letters, 22(9), pp. 1373-1377, 2015.
12. Yang Y., Peng, Z. K., Dong, X. J., Zhang, W.M., “General Parameterized Time-frequency Transform", IEEE Transactions on Signal Processing, 62(11), pp. 2751-2764, 2014.
13. Yang Y., Peng, Z. K., Dong, X. J., Zhang, W.M., “Application of Parameterized Time-frequency Analysis on Multicomponent Frequency Modulated Signals", IEEE Transactions on Instrumentation and Measurement, 63(12), pp. 3169-3180, 2014.
14. Yang Y., Zhang, W. M., Peng, Z. K., Meng, G., “Multicomponent Signal Analysis based on Polynomial Chirplet Transform", IEEE Transactions on Industrial Electronics, 60(9), pp. 3948-3956, 2013.
15. Yang Y., Peng, Z. K., Zhang, W. M., Meng, G., “Spline-kernelled Chirplet Transform for the Analysis of Signals with Time-varying Frequency and Its Application", IEEE Transactions on Industrial Electronics, 59(3), pp. 1612-1621, 2012.
16. Yang, Y., Peng, Z. K., Zhang W. M., Meng, G., “Frequency-varying Group Delay Estimation Using Frequency Domain Polynomial Chirplet Transform", Mechanical Systems and Signal Processing, 46(1), pp. 146-162, 2014.
17. Yang Y., Peng Z. K., Zhang W. M., Meng G., “Characterize Highly Oscillating Frequency Modulation Using Generalized Warblet Transform", Mechanical Systems and Signal Processing, 26, pp. 128-140, 2012.
18. Zhu, T., Johnson, A.E., Yang, Y., Clifford, G.D. and Clifton, D.A., 2018. Bayesian fusion of physiological measurements using a signal quality extension. Physiological measurement, 39(6), p.065008.
19. Zhu, T., Colopy, G.W., Macewen, C., Niehaus, K., Yang, Y., Pugh, C.W. and Clifton, D.A., 2019. Patient-specific physiological monitoring and prediction using structured Gaussian processes. IEEE Access, 7, pp.58094-58103.
20. Wang C. Y. , Yang Y. *, Kouchaki S., Walker, A.S., Crook, D.W., Peto, T.E.A., Clifton, D.A., “MTB-HINE-BERT: a pre-trained model for predicting drug resistance of Mycobacterium tuberculosis”, Machine Learning for Health workshop at NeurIPS 2020.
21. 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). (co-last author)
22. 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).
23. 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).
