CV

Education

• B.S. in University of Science and Technology of China, June 2011
• Ph.D in Computer Science, University of North Carolina at Charlotte, Charlotte, NC, USA, May 2015

Work experience

• Software Engineer and Research Scientist               AcuSys, Inc
                                                                                  Aug 2015 - now
  • Design and implement data analysis and reporting solutions for different government systems such as National Data Bank, Automated Grants Closeout, Digital Accountability and Transparency Act Supporting Systems and so on, for United States Department of Agriculture.
  • Evaluate network-related applications to identify root cause of issues; analyze network data and leverage statistical models to determine network usage and provide technical support.
• Software Engineer Intern                               Samsung Research America
                                                                                      Spring 2014
  • Conduct analysis of the information demand of the hardware security team with Amazon Web Service to conduct efficient analysis of large scale of data.
  • Design and implement a security supporting component enabling daily OLAP and other mining tasks on the access logs generated from millions of Samsung mobile devices every day.

Research Experience

• Research Assistant                                                                                             University of North Carolina, Charlotte
  • Privacy Preserving Data Mining of Social Network and HealthCare Data                         Oct 2012-May 2015
    • Conducted interdisciplinary research in the design and implementation of the SMASH system to help understanding the influence of various factors on sustained weight loss, in collaboration with doctors, scientists and researchers from PeaceHealth Medical Group, SKT Americas, NIH and University of Oregon
    • Designed and implemented privacy preserving data analysis algorithms (eight publications). For my doctoral dissertation, I investigate how to protect privacy in analyzing sensitive data with various mining models. We develop privacy preserving mining techniques for analyzing sensitive data from social network, wearable devices, health record platforms, considering various potential attacking methods from adversaries. Our developed techniques can be applied to many commonly used data mining approaches such as general OLAP queries, regression analysis, spectral analysis, Bayesian inference, deep learning models and so on.
  • Privacy Threat in Human Genome Data Analysis(Java, Matlab; Best Overall Paper Award at BIBM 2013)                                                                                                                                                                 Jan-Sep 2013
    • Explored commonly used analyzing approaches for human genome data including chi-square tests, linear regression, logistic regression, Bayesian inferences and so on.
    • Evaluated potential risks in analyzing human genome data. Designed attack models that bring about potential risks to general population. Designed and proposed privacy protection mechanisms that can be employed to protect study participants and the general population. This work achieved Best Overall Paper Award at the 2013 IEEE International Conference on Bioinformatics and Biomedicine(BIBM).
  • Retweeting Behavior Prediction in Social Media (Java, Matlab, SPSS; Runner-up Award on WISE 2012 Challenge)                                                                                                                                         Jan-Oct 2012
    • Conducted user behavior analysis of data from Twitter and Sina focusing on semantic analysis, fraud detection and retweeting behavior prediction. This work achieved Runner-up Award on WISE 2012 Challenge at the 13th International Conference on Web Information System Engineering.
    • Designed and implemented analyzing algorithms including ARMA model for time series data analysis and spectral projection of graph topology for spectrum based methods to identify different behavior patterns.
• Junior Research Assistant                                                                 University of Science and Technology of China
  • Student Performance Prediction for KDD CUP 2010 Challenge(Java)
    • Explored and implemented data mining algorithms to predict student performance on mathematical problems from logs of student interaction with Intelligent Tutoring System. Our Team, consisting of several junior students, ranked 13th in the students teams and 25th in all teams (including some famous research institutes) in the competition in the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

Publications

Predicting Retweeting Behavior Based on Autoregressive Moving Average Model

Z. Luo, Y. Wang, and X. Wu. Proceedings of the 13th International Conference on Web Information System Engineering (WISE12), Paphos, Cyprus, Nov 28-30, 2012.

On Linear Refinement of Differential Privacy-Preserving Query Answering

X. Ying, X. Wu, and Y. Wang. Proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD13), Gold Coast, Australia, April 14-17, 2013. (Best Application Paper Award)

Differential Privacy Preserving Spectral Graph Analysis

Y. Wang, X. Wu, and L. Wu. Proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD13), Gold Coast, Australia, April 14-17, 2013.

On Learning Cluster Coefficient of Private Networks

Y. Wang, X. Wu, J. Zhu, and Y. Xiang. Journal of Social Network Analysis and Mining (SNAM), 3(4):925-938, 2013.

Preserving Differential Privacy in Degree-correlation based Graph Generation

Y. Wang and X. Wu. ransactions on Data Privacy, 6(2):127-145, 2013.

Using Aggregate Human Genome Data for Individual Identification

Y. Wang, X. Wu, and X. Shi. Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Shanghai, China, Dec 18-21, 2013, pp. 410-415. (Best Paper Award).

On Burst Detection and Prediction in Retweeting Sequence

Z. Luo, Y. Wang, X. Wu, W. Cai and T. Chen. Proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Ho Chi Minh, Vietnam, May 19-22, 2014.

Regression Model Fitting under Differential Privacy and Model Inversion Attack

Y. Wang, C. Si and X. Wu. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, July 25-31, 2015.

Differential Privacy Preservation for Deep Auto-Encoders: an Application of Human Behavior Prediction

N. Phan, Y. Wang, X. Wu and D. Dou. Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona, USA, Feb 12-17, 2016.

Using Randomized Response for Differential Privacy Preserving Data Collection

Y. Wang, X. Wu and D. Hu. Proceedings of the 9th International Workshop on Privacy and Anonymity in the Information Society (PAIS), Bordeaux, France, March 15, 2016.

Infringement of Individual Privacy via Mining Differentially Private GWAS Statistics

Y. Wang, J. Wei, X. Wu and X. Shi. Proceedings of the 2nd International Conference on Big Data Computing and Communications (BIGCOM), Shenyang, China, July 29-31, 2016.

Bayesian Network Construction and Genotype-Phenotype Inference Using GWAS Statistics

L. Zhang, Q. Pan, Y. Wang, X. Wu, and X. Shi. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 16(2):475-489, March-April 2019.

Service and leadership

• Served as Program Committee Member for top conferences in Computer Science such as AAAI, IJCAI, PAKDD, ICDM, CIKM, KDD and so on.
• Served as the Review Editor in the Editorial Board for top journals of Data Mining and Management such as Frontiers in Big Data, Social Network Analysis and Mining, Journal of Intelligent Information Systems, International Journal of Data Science and Analytics and so on.