Xu Jing

Xu Jing

Name: Xu Jing

Sex: Female

Department: Institute of Machine Intelligence 

Administrative duties: Vice Dean, Director

Title: Professor

Education: PhD

Major: Computer application

Office Phone: 23500350

Email: xujing@nankai.edu.cn

Research direction: Artificial intelligence, big data analysis, software engineering



Personal profile
Achievements
Writing papers
Lecture course
Social Appointments

[Education and Work Experience]

Received her Bachelor's degree in Computer Science from Nankai University in 1989, Master's degree in computer science from Beihang University in 1992, and Doctor's degree from Nankai University in 2003. From July 2002 to March 2003, she visited Microsoft Research Asia. From 1992 to 1998, she was engaged in software development in a research Institute in Tianjin. Since September 1998, she has been working in Institute of Machine Intelligence of Nankai University, mainly engaged in teaching and scientific research of artificial intelligence, big data analysis, software engineering, software testing and so on.




[Projects,Award and Patent]

In recent years, she has completed a number of national, provincial, international and domestic cooperation projects. She has published more than 100 papers and 1 textbook. She has applied for 15 software patents (5 of which have been authorized) and obtained 14 software Copyrights.

She won the Second Prize of Science and Technology Progress of Tianjin in 2017 (the first accomplisher), and won the second Prize of Tianjin Science and Technology Progress in 2018.


[Publications and Books]

Major papers published recently

[1] Early Prediction for Mode Anomaly in Generative Adversarial Network Training: An Empirical Study,Information Science, 534(2020) 117-138

[2] Review Sharing via Deep Semi-supervised Code Clone Detection[J]. IEEE Access 8(2020): 24948-24965.( Date of Publication: 2020-1-14)

[3] A Simple Saliency Detection Approach via Automatic Top-down Feature Fusion. Neurocomputing 388: 124–34.( Available online: 2020-1-13)

[4] Deep Attentive Factorization Machine for App Recommendation Service. ICWS 2019

[5] AutoPer: Automatic Recommender for Runtime-Permission in Android Applications. Compsac 2019. July15-19,USA.

[6] Bi-dimensional Representation of Patients for Diagnosis Prediction,Compsac2019,July5-19,USA.

[7] Deep Review Sharing,SANER 2019.

[8] Systematic Comprehension for Developer Reply in Mobile System Forum,SANER 2019.

[9] Android application Activity launch ring research. Chinese journal of computers, 2019,42 (39) : 1-19.

[10] Automatic Feature Exploration and an Application in Defect Prediction. IEEE Access 7 (2019): 112097-112112.

[11] A Projection-based Approach for Memory Leak Detection,Compsac2018,July 22-27,Japan.

[12] TRAC: A Therapeutic Regimen-oriented Access Control Model in Healthcare,Compsac2018,July 22-27,Japan.

[13] App Genome: Callback Sequencing in Android,Poster Track in ICSE 2017

[14] An Inferential Metamorphic Testing Approach to Reducing False Positives in SQLIV Penetration Test;CompSac2017

[15] Application of Markov Model in SQL Injection Detection;Compsac2017

[16] GEMS: An Extract Method Refactoring Recommender,ISSRE2017

[17] Test Case Generation method for Access Control Vulnerability Based on Policy Inference, Chinese Journal of Computer Science, December 2017

[18] Research on Model Detection of Mobile Application Information Leakage, Chinese Journal of Computer science, 2016, 39

[19] Toward Exploiting Access Control Vulnerabilities within MongoDB BackendWeb Applications,CompSac2016

[20] An Effective Penetration Test Approach based on Feature Matrix for Exposing SQL Injection Vulnerability,CompSac2016

[21] Toward Discovering Logic Flaws within MongoDB-Based Web Applications,International Journal of Automation and Computing, 2017.14

[22] Automatic Construction of Callback Model for Android Application,ICECCS 2016

[23] research on semi-supervised learning based on implicit information, Chinese journal of communications,2015,36(10)

[24] Neural Network Breathing Voice Recognition Algorithm based on SVM method, Communications Journal, October 25, 2014

[25] A trusted Entity Model of Network Software and Its Trust Model based on evaluation, Science and Information Science of China, 2013, 43 (1) : 108-125

[26] Detection of dead loops based on Recursive chain Algebra and Convergence and Divergence of iterative sequences, Journal of Computer Science and Technology,2013, 11 (2)

[27] A Dynamic SQL Injection Vulnerability Test Case Generation Model Based on the Multiple Phases Detection Approach,Compsac 2013,July 2013

[28] Enhancing Query Performance by Avoiding Negative Interactions , In HPCC2013

[29] An Evaluation Model for Dependability of Internet-scale Software on Basis of Bayesian Networks and Trustworthiness,Journal of Systems and Software,Sept.17,2013

[30] Reliability Evaluation Model of Network Software Based on Bayesian Networks, Computer Research and Development, May 2012


[Courses]

Intelligent Software Testing (Postgraduate)

Advanced Language Programming (Undergraduate)


[Memberships]

Member of Software Engineering Committee, China Computer Society

               

Standing director of Tianjin Graphics and Image Association

               

Deputy Director (Concurrently) of Tianjin Software Evaluation Center