Biography


Sha ZHAO  (赵 莎)  

Research Professor (February 2021~present)
College of Computer Science and Technology, Zhejiang University
szhao@zju.edu.cn
Research Interests: Ubiquitous Computing, Smartphone Sensing,
Data Mining, Machine Learning.
Google Scholar Research Gate

I am currently a Research Professor of the Coolege of Computer Science and Technology, Zhejiang University. I received the Ph.D. degree in computer science from Zhejiang University in 2017, under the supervision of Prof. Gang Pan. I visited the Human-Computer Interaction Institute at Carnegie Mellon University as a visiting PhD student from September 2015 to September 2016, working with Prof. Anind K. Dey. I was a Postdoctoral Research Fellow of the College of Computer Science and Technology, Zhejiang University, from June 2017 to January 2021, working with Prof. Gang Pan. I won the Best Paper Award of ACM UbiComp’16.

News

2021/02: Our paper "User Profiling from Their Smartphone Applications (利用智能手机Apps的用户画像)" is published by Communications of the CCF (中国计算机学会通讯).

2021/01: Our paper "Player Behavior Modeling for Enhancing Role-Playing Game Engagement" is accepted by IEEE Transactions on Computational Social Systems.

2020/01: Our paper "Understanding Smartphone Users from Installed App Lists Using Boolean Matrix Factorization" is accepted by IEEE Transactions on Cybernetics.

2019/11: 第二届中国计算机学会网络空间用户画像与社群智能前沿论坛将于11月30日在杭州浙江大学邵逸夫科学馆117会议室举行,欢迎参加. 邀请函下载

2019/08: Our paper "Gender Profiling from a Single Snapshot of Apps Installed on a Smartphone: An Empirical Study" is accepted by IEEE Transactions on Industrial Informatics.

2019/08: Our paper "Forecasting Price Trend of Bulk Commodities Leveraging Cross-domain Open Data Fusion" is accepted by ACM Transactions on Intelligent Systems and Technology.

2019/07: Our paper "Investigating Smartphone User Differences in Their Application Usage Behaviors: An Empirical Study" is accepted by CCF Transactions on Pervasive Computing and Interaction.

2019/07: Our survey paper "User Profiling from Their Use of Smartphone Applications: A Survey" is accepted by Pervasive and Mobile Computing.

2016/09: Our paper "Discovering Different Kinds of Smartphone Users Through Their Application Usage Behaviors" wins the ACM UbiComp 2016 Best Paper Award.

Publications

1. Sha Zhao, Julian Ramos, Jianrong Tao, Ziwen Jiang, Shijian Li, Zhaohui Wu, Gang Pan, and Anind Dey. Discovering Different Kinds of Smartphone Users Through Their Application Usage Behaviors. The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016) [Best Paper Award] (CCF Rank: A) Full paper


2. Sha Zhao, Zhiling Luo, Ziwen Jiang, Haiyan Wang, Feng Xu, Shijian Li, Jianwei Yin, and Gang Pan. AppUsage2Vec: Modeling Smartphone App Usage for Prediction. The 35th IEEE International Conference on Data Engineering (ICDE2019) (CCF Rank: A) Full paper


3. Sha Zhao, Gang Pan, Jianrong Tao, Zhiling Luo, Shijian Li, and Zhaohui Wu. Understanding Smartphone Users from Installed App Lists Using Boolean Matrix Factorization. IEEE Transactions on Cybernetics (IF = 11.079) (JCR Section I) (ZJU Top)


4. Sha Zhao, Yizhi Xu, Xiaojuan Ma, Ziwen Jiang, Zhiling Luo, Shijian Li, Laurence T. Yang, Anind Dey, and Gang Pan. Gender Profiling from a Single Snapshot of Apps Installed on a Smartphone: An Empirical Study. IEEE Transactions on Industrial Informatics, 2019 (IF = 9.112) (JCR Section I) Full paper


5. Zhiling Luo, Yinghua Cui, Sha Zhao*, and Jianwei Yin*. g-Inspector: Recurrent Attention Model on Graph, IEEE Transactions on Knowledge and Data Engineering Computing (TKDE), 2020 (CCF Rank: A) (IF=4.935)


6. Sha Zhao, Shijian Li, Julian Ramos, Zhiling Luo, Ziwen Jiang, Anind Dey, and Gang Pan. User Profiling from Their Use of Smartphone Applications: A Survey. Pervasive and Mobile Computing, 2019 (IF = 2.725) Full paper


7. Sha Zhao, Gang Pan, Yifan Zhao, Jianrong Tao, Jinlai Chen, Shijian Li, and Zhaohui Wu. Player Behavior Modeling for Enhancing Role-Playing Game Engagement. IEEE Transactions on Computational Social Systems, 2021


8. Sha Zhao, Yizhi Xu, Zhiling Luo, Jianrong Tao, Shijian Li, Changjie Fan, and Gang Pan. Mining User Attributes Using Large-scale APP lists of Smartphones. IEEE SYSTEMS JOURNAL, 2017 (IF = 3.987) (JCR Section II) Full paper


9. 赵莎, 李石坚, 潘纲. 利用智能手机Apps的用户画像. 中国计算机学会, 2021, 17 (2).


10. Sha Zhao, Julian Ramos, Jianrong Tao, Ziwen Jiang, Shijian Li, Zhaohui Wu, Gang Pan, and Anind Dey. Who Are the Smartphone Users? -- Identifying User Groups with Apps Usage Behaviors. ACM SIGMOBILE Mobile Computing and Communications Review, 2017 Full paper


11. Sha Zhao, Zhe Zhao, Runhe Huang, Zhiling Luo, Shijian Li, Jianrong Tao, Shiwei Cheng, Jing Fan, and Gang Pan. Discovering Individual Life Style from Anonymized WiFi Scan Lists on Smartphones. IEEE Access, 2019 (IF = 3.745) (JCR Section II) Full paper


12. Sha Zhao, Feng Xu, Yizhi Xu, Xiaojuan Ma, Zhiling Luo, Shijian Li, Anind Dey, and Gang Pan. Investigating Smartphone User Differences in Their Application Usage Behaviors: An Empirical Study. CCF Transactions on Pervasive Computing and Interaction, 2019 Full paper


13. Binbin Zhou, Sha Zhao, Longbiao Chen, Shijian Li, Zhaohui Wu, Gang Pan. Forecasting Price Trend of Bulk Commodities Leveraging Cross-domain Open Data Fusion. ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2019 (IF = 2.672) (JCR Section II) Full paper


14. Sha Zhao, Zhe Zhao, Yifan Zhao, Runhe Huang, Shijian Li, and Gang Pan. Discovering People's Life Patterns from Anonymized WiFi Scanlists. The 11th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2014) (CCF Rank: C) Full paper


15. Sha Zhao, Yifan Zhao, Zhiling Luo, Runhe Huang, Shijian Li, and Gang Pan. Characterizing a User from Large-scale Smartphone-sensed Data. ACM Workshop on The 2017 International Joint Conference on Pervasive and Ubiquitous Computing (UbiMI 2017) Full paper


16. Sha Zhao, Feng Xu, Zhiling Luo, Shijian Li, and Gang Pan. Demographic Attributes Prediction Through App Usage Behaviors on Smartphones. ACM Workshop on The 2018 International Joint Conference on Pervasive and Ubiquitous Computing (AppLens 2018) Full paper


17. Gang Pan, Zhiwen Yu, Sha Zhao *, Anind K. Dey. Proposal for Workshop on AppLens: Mining and Learning from Smartphone Apps for Users. Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers.


18. Sha Zhao, Yong Li, Sasu Tarkoma, Zhiwen Yu, Anind K. Dey, Gang Pan. AppLens 2019: The 2nd International Workshop on Mining and Learning from Smartphone Apps for Users. Proceedings of the 2019 ACM International Joint Conference and 2019 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers.


19. Jianrong Tao, Jianshi Lin, Shize Zhang, Sha Zhao, Runze Wu, Changjie Fan, and Peng Cui. MVAN: Multi-view Attention Networks for Real Money Trading Detection in Online Games. (ACM SIGKDD 2019) (CCF Rank: A)


20. Pengfei Li, Hua Lu, Nattiya Kanhabua, Sha Zhao, and Gang Pan. Location Inference for Non-geotagged Tweets in User Timelines. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019 (CCF Rank: A) (IF=4.935)


21. Binbin Zhou, Longbiao Chen, Fangxun Zhou, Shijian Li, Sha Zhao, Sajal K. Das, and Gang Pan. ESCORT: Fine-grained Urban Crime Risk Inference Leveraging Heterogeneous Open Data with Application to Risk-aware Route Recommendation. IEEE Systems Journal, 2020 (IF=3.987)


22. Binbin Zhou, Longbiao Chen, Sha Zhao, Fangxun Zhou, Shijian Li, and Gang Pan. Spatio-temporal Analysis of Urban Crime Leveraging Multisource Crowdsensed Data. Personal and Ubiquitous Computing (PUC), 2020 (IF=2)


23. Zengwei Zheng, Mingxuan Zhou, Yuanyi Chen, Meimei Huo, Lin Sun, Sha Zhao, and Dan Chen. A Fused Method of Machine Learning and Dynamic Time Warping for Road Anomalies Detection. IEEE Transactions on Intelligent Transportation Systems (TITS), 2020 (IF=6.319)


24. Jianrong Tao, Linxia Gong, Changjie Fan, Longbiao Chen, Dezhi Ye and Sha Zhao. GMTL: A GART Based Multi-task Learning Model for Multi-Social-Temporal Prediction in Online Games. The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019) (CCF Rank: B)


25. Yu Chen, Zhiling Luo, Sha Zhao, Ying Li, and Jianwei Yin. Adversarial Attacks on Graphs by Adding Fake Nodes. AAAI Workshop on Deep Learning on Graphs: Methodologies and Applications (DLGMA'20)


26. Sha Zhao, Longbiao Chen, Shijian Li, and Gang Pan. iCPS-Car: An Intelligent Cyber-Physical System for Smart Automobiles. 2013 IEEE International Conference on Cyber, Physical and Social Computing (CPSCom 2013), 818-825. Full paper


27. Sha Zhao, Shijian Li, Gang Pan, and Hong Li. Design and Implementation of a driving simulation environment. 2011 Chinese Conference on Pervasive Computing (PCC 2011) [in Chinese]


28. Yang Xu, Shijian Li, Sha Zhao, and Gang Pan. A Novel Telematics Framework Based on Driving Behavior. 2013 Chinese Conference on Pervasive Computing (PCC 2013) [in Chinese]


29. Longbiao Chen, Yaochun Li, Zeming Zhegn, Li Zhang, Dan He, Xiaolong Li, Sha Zhao, Shijian Li, and Gang Pan. WaterLady: A Case Study for Connecting Physical Devices into Social Networks. The 9th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2012) (CCF Rank: C) Full paper

Projects

1. National Key R&D Program of China, 2018-2021

2. National Natural Science Foundation of China (NSFC), Young Scientist Fund, 2019-2021

3. China Postdoctoral Science Foundation (Special), 2018-2020

4. China Postdoctoral Science Foundation (First class), 2017-2020

Activities

ACM UbiComp 2019 Tutorial: Smartphone App Usage, Understanding, Modelling, And Prediction(September, 9, 2019, London, UK)

ACM UbiComp 2019 Workshop: AppLens 2019 (September, 9, 2019, London, UK) (Two datasets openning)

ACM UbiComp 2018 Workshop: AppLens 2018 (October 8, 2018, Singapore)

We organized a workshop "AppLens-Mining and Learning from Smartphones Apps for Users", in conjunction with the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing. More details can be seen at the AppLens2018 website.

Smartphone applications (abbr. apps) are ubiquitous in our daily life. Abundant apps provide useful services in almost every aspect of modern life. Easy to download and often free, apps can be fun and convenient for playing games, getting turn-by-turn directions, and accessing news, books, weather, and more. Apps on smartphones can be considered as the entry point to access everyday life services such as communication, shopping, navigation, and entertainment. Since a smartphone is linked to an individual user, apps in smartphones can sense users' behavior and activities.

Researchers can use smartphone apps to record users' personal history data, and use the data to analyze apps and understand users. In this workshop (AppLens 2018), we bring researchers together with an interest in understanding users from their use of smartphone apps (e.g., interests, personality, and life routines), discovering cultural and social phenomenon (e.g., social event detection) through analyzing app usage, recognizing app usage behaviors (e.g., app overuse detection), and studying smartphone apps (e.g., app categorization and app popularity prediction). We want researchers to share their experiences, success and frustrations on conducting research in such topics so as to capture a state-of-art on theories, models, and methodologies that cope with these challenges. This workshop will include paper sessions, invited talks, a panel session, and Best paper award.


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