School of Computer Science
Shanghai, 201203, P.R.China
jiayunzhang15 AT outlook DOT com
I am an undergraduate student at the School of Computer Science at Fudan University. I have been a research assistant in the Mobile Systems and Networking (MSN) group since 2018, advised by Prof. Yang Chen. In 2019 summer, I visited Aalto University as a research intern in the Mobile Cloud Computing (mc2) group, advised by Prof. Yu Xiao. In 2020 winter, I visited the SAND Lab at University of Chicago, co-advised by Prof. Ben Y. Zhao and Prof. Heather Zheng. I am especially interested in data mining, social networks, machine learning and deep learning.Here is my full CV.
Fawkes: Protecting Personal Privacy against Unauthorized Deep Learning Models. [ pdf ]
Shawn Shan, Emily Wenger, Jiayun Zhang, Huiying Li, Haitao Zheng, Ben Y. Zhao.
arXiv preprint arXiv:2002.08327 (2020).
Understanding the Working Time of Developers in IT Companies in China and the United States.
Jiayun Zhang, Yang Chen, Qingyuan Gong, Aaron Yi Ding, Yu Xiao, Xin Wang, Pan Hui.
Accepted by IEEE Software.
Detecting Malicious Accounts in Online Developer Communities Using Deep Learning [ pdf ]
Qingyuan Gong, Jiayun Zhang, Yang Chen, Qi Li, Yu Xiao, Xin Wang, Pan Hui.
Proc. of ACM International Conference on Information and Knowledge Management (CIKM'19)
Identifying Structural Hole Spanners in Online Social Networks Using Machine Learning [ pdf ]
Qingyuan Gong, Jiayun Zhang, Xin Wang, Yang Chen
Proc. of the ACM SIGCOMM 2019 Conference Posters and Demos
DeepLoc: A Location Preference Prediction System for Online Lodging Platforms [ pdf ]
Yihan Ma, Hua Sun, Yang Chen, Jiayun Zhang, Yang Xu, Xin Wang, Pan Hui.
Proc. of the 14th CCF Conference on Computer Supported Cooperative Work and Social Computing (ChineseCSCW'19)
Understanding Work Rhythms in Software Development and Their Effects on Technical Performance.
Jiayun Zhang, Qingyuan Gong, Yang Chen, Yu Xiao, Xin Wang, Aaron Yi Ding.
Submitted to International Conference on Mining Software Repositories (MSR’20).
A video dataset of a wooden box assembly process.
Jiayun Zhang, Petr Byvshev, Yu Xiao.
Submitted to Scientific Data Journal.
Protecting Personal Privacy against Unauthorized Deep Learning Models
co-advised by Prof. Ben Y. Zhao and Prof. Heather Zheng, University of Chicago.   Jan 2020 – Feb 2020
We propose Fawkes, a system that allow individuals to inoculate themselves against unauthorized facial recognition models by adding imperceptible pixel-level changes to their photos.
Identifying Structural Hole Spanners in Online Social Networks
advised by Prof. Yang Chen, Fudan University.   Mar 2019 – Present
We propose a machine learning-based model for identifying structural hole spanners, which leverages the ego networks and the cross-site linking function to enhance the identification. This work has been published in SIGCOMM Posters and Demos'19.
Malicious User Identification on Version Control Systems
advised by Prof. Yang Chen, Fudan University.   Jun 2018 – Jun 2019
We propose GitSec, a system with Phased LSTM and attention mechanism to detect malicious accounts on VCS. This work has been published in CIKM'19.
Understanding Work Rhythms in Software Development and Their Effects on Technical Performance
advised by Prof. Yang Chen, Fudan University.   Jan 2019 – Sep 2019
We identify representative work rhythms of developers by performing clustering analysis on commit behaviors. We analyze the relationship between work rhythms and demographics and technical performance. A user survey is conducted to understand the situation of working overtime from developers’ perspectives. This work has been accepted by IEEE Software.
A Video and Sensor Dataset of a Wooden Box Assembly Process
advised by Prof. Yu Xiao, Aalto University.   Jun 2019 – Sep 2019
We collect a video and sensor dataset of the wooden box assembly process with multiple cameras and a sensor glove. This work has been submitted to Scientific Data.
Data Mining on Health-Seeking Behavior
advised by Prof. Yun Xiong, Fudan University.   May 2017 – Apr 2018
We devise a model with SVM for pneumonia detection based on medication records, and a model with Time-Aware LSTM to predict one’s stage of diabetes based on previous diagnoses. We also developed a web-based interactive system for diabetes prediction.
University of Chicago.   Chicago, IL, U.S.A
Research Intern at the SAND Lab   Jan 2020 – Mar 2020
Aalto University.   Espoo, Finland
Research Intern at the Mobile Cloud Computing (mc2) group.   Jun 2019 – Sep 2019
VMware, Inc.   Shanghai, China
MTS (Member of Technical Staff) Intern.   Apr 2018 – Oct 2018
Fudan University.   Shanghai, China
Research Assistant at the Mobile Systems and Networking (MSN) group.   May 2018 – Present
B.S. in Computer Science   Sep 2015 – Jul 2020 (Expected)
Raindrop Removal From a Single Image, advised by Prof. Junping Zhang, Fudan Univeristy. [ code ]   Jun 2019
A deep-learning-based model with ResNet, Dilated CNN and ConvLSTM was devised for raindrop removal. The model could identify the location and intensity of raindrops and eliminate the raindrops. Gaussian filtering was incorporated to remove the background interference and improve the network capability.
3D Parkour Game. [ code ]   Dec 2017
Developed a full-featured parkour game; built 3D game scenes in Unity, designed animation effects and user interactions; implemented the game logic with Unity Game scripts written in C#.
- The First Prize of Shanghai Open Data Innovation Research Competition (Top 1 among 65 teams)   2019
- Best Student Award, Mobile Systems and Networking Group in Fudan University (1 out of 32)   2019
- Second Class Scholarship for Outstanding Students, Fudan University (Top 10%)   2019
- Chun-Tsung Program, Endowment funded by Nobel Laureate Dr. Tsung-Dao Lee   2019
- Xiyuan Scholar, Undergraduate Research Program in Fudan University   2018
- Third Class Scholarship for Outstanding Students, Fudan University   2016 & 2018