职位

副教授

个人经历

2012年于芬兰赫尔辛基大学获得计算机科学博士学位。2013-2014年在英国诺丁汉大学宁波分校工作。2015年至2018年在美国天普大学从事博士后研究，并于2018年12月加入华东师范大学。

研究兴趣

研究兴趣主要包括：

·数据挖掘、大规模图分析；

·机器学习、时间序列数据分析、结构回归；

·以及在金融数据、社交媒体数据、电子病历数据中的应用。

详细信息请见个人主页：https://sites.google.com/view/fangzhou

学术研究

主持过国家自然科学基金青年项目、上海自然科学基金项目，参与过国家重点研发项目。主要工作已经发表在IJCAI, SIGKDD, ECML-PKDD, ICDM, Machine Learning等国际顶级会议及期刊上。

Selected publications:

• Fang Zhou, Ave Gillespie, Djordje Gligorijevic, Jelena Gligorijevic, Zoran Obradovic. (2020) “Use of Disease Embedding Technique to Predict the Risk of Progression to End-Stage Renal Disease,” Journal of Biomedical Informatics, vol. 105, 103409, 2020.

• Shoumik Roychoudhury*, Fang Zhou*, Zoran Obradovic.  Leveraging Subsequence-orders for Univariate and Multivariate Time-series Classification, Proc. 19th SIAM Int’l Conf. Data Mining(SDM), Calgary, Canada, May 2019.

• Martin Pavlovski, Fang Zhou, Nino Arsov, Ljupco Kocarev, Zoran Obradovic, “Generalization-Aware Structured Regression towards Balancing Bias and Variance”, Proc. 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018, pp. 2616-2622.

• Fang Zhou, Qiang Qu, Hannu Toivonen, “Summarisation of Weighted Networks”, Journal of Experimental & Theoretical Artificial Intelligence, 2017, 29(5): 1023-1054.

• Martin Pavlovski, Fang Zhou, Ivan Stojkovic, Ljupco Kocarev, Zoran Obradovic, “Adaptive Skip-Train Structured Regression for Temporal Networks”, ECML-PKDD 2017, pp 305-321.

• Tijana Vujicic, Jesse Glass, Fang Zhou, Zoran Obradovic, “Gaussian Conditional Random Fields Extended for Directed Graphs”, Machine Learning, 2017, 106(9-10): 1271-1288.

• Fang Zhou, Mohamed Ghalwash, Zoran Obradovic, “A Fast Structured regression for Large Networks”, Proc. 2016 IEEE International Conference on Big Data, Washington, DC, Dec. 2016, pp106-115.

• Tom Mirowski, Shoumik Roychoudhury, Fang Zhou, Zoran Obradovic, “Predicting Poll Trends using Twitter and Multivariate Time-series Classification”, Proc. 8th Int'l Conf. Social Informatics (SocInfo), Seattle, WA, Nov. 2016, pp273-289.

• Fang Zhou, Claire Q, Ross D. King, “Predicting the Geographical Origin of Music”, The 14th IEEE International Conference on Data Mining (ICDM), 1115-1120, 2014.

• Hannu Toivonen, Fang Zhou, Aleksi Hartikainen and Atte Hinkka, “Compression of Weighted Graphs”, The 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 965-973, 2011.

• Fang Zhou, Sebastien Mahler, and Hannu Toivonen, “Network Simplification with Minimal Loss of Connectivity”, The 10th IEEE International Conference on Data Mining (ICDM), 659-668, 2010.

学术活动：

Program Committee Member, 审稿人: CIKM, AAAI, IEEE BigData

We are seeking highly motivated, positive, and enthusiastic students to join our team.

If you are interested in our research topics, please contact me through email.