Hui Wang

Associate Professor

School: School of Engineering and Science

Department: Computer Science

Building: Gateway Center

Room: S352

Phone: (201) 216-8736

Fax: (201) 216-8249

Email: hwang4@stevens.edu

Website

Research

Data security and privacy
Fairness and privacy in machine learning

Institutional Service
  • Faculty senate Member
  • Department promotion & Tenure committee Member
  • PhD coordinator Chair
  • SES Faculty Advisory Council (FAC) Member
  • Data Science PhD program Member
  • CS Faculty mentoring program committee Chair
  • CS Chair Search Committee Chair
  • Faculty Ambassadors for Undergraduate CS students Member
  • Director of Data Science PhD Program Chair
  • Lead undergraduate advisors Member
Professional Service
  • ACSAC'22 conference Program committee member
  • PVLDB Program committee member
  • SIGMOD'22 conference Program committee member
  • EDBT'22 conference Program committee
  • NSF Panlist
  • ACM SIGKDD'21 conference Program committee member
  • NSF Panelist
  • NSF Panelist
  • Department of Energy (DOE) Panelist
  • SDM'21 conference Program committee member
  • ACM SIGMOD conference Web Chair
  • The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) 2020 Program committee member
  • International Conference on Very Large Data Bases (VLDB) 2020 Program committee member
  • 34th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy (DBSec) 2020 Program committee member
  • International Joint Conferences on Artificial Intelligence (IJCAI) 2020 Program committee member
  • Cyber Women workshop affiliated with CODASPY conference Panelist
  • NSF Panelist
  • The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) Program committee member
  • 11th ACM Conference on Data and Application Security and Privacy (CODASPY)'20 conference Program committee member
  • NSF Panelist
  • SIAM International Conference on Data Mining (SDM20) conference Program committee member
  • The 23rd International Conference on Extending Database Technology (EDBT) 2020 Program committee member
  • National science foundation NSF panels
  • Department of Energy DOE panalist
  • National science foundation NSF panels
  • Information systems Journal reviewer
  • ACM Transactions on Knowledge Discovery from Data (TKDD) Journal reviewer
  • IEEE Transactions on Knowledge and Data Engineering (TKDE) Journal reviewer
  • SIAM International Conference on Data Mining (SDM19) conference committee member
  • ACM Conference on Data and Applications Security and Privacy (ACM CODASPY) conference committee member
  • IEEE ACCESS Journal reviewer
  • Distributed and Parallel Databases Journal reviewer
  • PLOS One Journal reviewer
Appointments

09/2016 - present, Associate professor, Stevens Institute of Technology
01/2008- 08/2016, Assistant Professor, Stevens Institute of Technology

Honors and Awards

NSF CAREER award, 2014.

Professional Societies
  • ACM – Association for Computing Machinery Member
  • IEEE – Institute of Electrical and Electronics Engineers Member
Selected Publications
Book Chapter
  1. Dong, B.; Wang, H. (2019). Efficient Authentication of Approximate Record Matching for Outsourced Databases. Advances in Intelligent Systems and Computing (pp. 119-168). Springer International Publishing.
    http://dx.doi.org/10.1007/978-3-319-98056-0_6.
  2. Li, Y.; Wang, W. H. (2016). Similarity Recoverable, Format-Preserving String Encryption. Web Technologies and Applications (pp. 439-443). Springer International Publishing.
    http://dx.doi.org/10.1007/978-3-319-45817-5_42.
Conference Proceeding
  1. Dong, B.; Zhang, B.; Wang, W. H. (2021). VeriDL: Integrity Verification of Outsourced Deep Learning Services. Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD).
  2. Chen, H.; Shi, X.; Wang, H. (2021). PAR-GAN: Improving the Generalization of Generative Adversarial Networks Against Membership Inference Attacks. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD.
  3. Sun, H.; Yang, Y.; Li, Y.; liu, H.; Wang, X.; Wang, W. (2021). Automating Fairness Configurations for Machine Learning. Proceedings of WWW conference.
  4. Wang, W. H.; Chen, J.; Shi, X. (2021). Differential Privacy Protection Against Membership Inference Attack on Machine Learning for Genomic Data. Pacific Symposium on Biocomputing (PSB).
  5. Li , Y.; Sun, H.; Wang, H. (2020). Towards Fair Truth Discovery from Biased Crowdsourced Answers. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Hoboken: ACM.
    http://dx.doi.org/10.1145/3394486.3403102.
  6. Hui, W.; Li , Y.; Ning, Y.; Liu, R.; Wu, Y. (2020). Fairness of Classification Using Users' Social Relationships in Online Peer-To-Peer Lending. (pp. 733-742). Hoboken: Proceeding of WWW conference, 2020.
  7. Wang, H.; Liu, R.; Ning, Y.; Wu, Y. (2020). Fairness of Classification Using Users’ Social Relationships in Online Peer-To-Peer Lending, FATES (Fairness, Accountability, Transparency, Ethics and Society) on the Web, joint with the Web Conference 2020 proceeding, 733-742. FATES (Fairness, Accountability, Transparency, Ethics and Society) on the Web, joint with the Web Conference 2020 proceeding.
  8. Zhang, B.; Dong, B.; Sun, H.; Wang, W. H. (2020). AuthPDB: Authentication of Probabilistic Queries on Outsourced Uncertain Data. Proceedings of the Tenth ACM Conference on Data and Application Security and Privacy. ACM.
    http://dx.doi.org/10.1145/3374664.3375731.
  9. Wang, H.; Sun, H.; Xiao, X.; Yin, Y.; Yu, T. (2019). Analyzing Subgraph Statistics from Extended Local Views with Decentralized Differential Privacy. No. 26th ACM Conference on Computer and Communications Security (CCS).
  10. Li, Y.; Sun, H.; Dong, B.; Wang, H. (2019). Cost-efficient Data Acquisition on Online Data Marketplaces for Correlation Analysis. Proceedings of International Conference on Very Large Data Bases (VLDB). Proceedings of International Conference on Very Large Data Bases (VLDB).
  11. Wang, H.; Li, Y.; Dong, B.; Sun, H. (2018). Cost-efficient Data Acquisition on Online Data Marketplaces for Correlation Analysis.. No. Yanying Li (4 ed., vol. 12, pp. 362 - 375). Proceedings of the VLDB Endowment .
  12. Wang, H.; Sun, H.; Dong, B.; Yu, T.; Qin, Z. (2018). Truth Inference on Sparse Crowdsourcing Data with Local Differential Privacy.. No. Proceedings of BigData Conference 2018 (pp. 488-497). IEEE Proceedings of BigData Conference 2018.
  13. Zhang, B.; Dong, B.; Wang, W. H. (2018). AssureMR: Verifiable SQL Execution on MapReduce. 2018 IEEE 34th International Conference on Data Engineering (ICDE). IEEE.
    http://dx.doi.org/10.1109/icde.2018.00117.
  14. Dong, B.; Wang, W. (2017). Frequency-Hiding Dependency-Preserving Encryption for Outsourced Databases. 2017 IEEE 33rd International Conference on Data Engineering (ICDE). IEEE.
    http://dx.doi.org/10.1109/icde.2017.124.
  15. Dong, B.; Wang, W. (2016). ARM: Authenticated Approximate Record Matching for Outsourced Databases. 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI). IEEE.
    http://dx.doi.org/10.1109/iri.2016.86.
  16. Monreale, A.; Wang, W. H. (2016). Privacy-Preserving Outsourcing of Data Mining. 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC). IEEE.
    http://dx.doi.org/10.1109/compsac.2016.169.
Journal Article
  1. Zhang, B.; Dong, B.; Wang, W. H. (2019). Integrity Authentication for SQL Query Evaluation on Outsourced Databases: A Survey. IEEE Transactions on Knowledge and Data Engineering (pp. 1-1). Institute of Electrical and Electronics Engineers (IEEE).
    http://dx.doi.org/10.1109/tkde.2019.2947061.
  2. Dong, B.; Wang, H. (2018). Secure partial encryption with adversarial functional dependency constraints in the database-as-a-service model. Data & Knowledge Engineering (vol. 116, pp. 1-20). Elsevier BV.
    http://dx.doi.org/10.1016/j.datak.2018.01.001.
  3. Wang, K.; Wang, H.; Tao, Y. (2017). Combining Ideas in Crowdsourced Idea Generation. Foundations of Management (1 ed., vol. 9, pp. 203-212).
    https://sciendo.com/article/10.1515/fman-2017-0016.
  4. WANG, W. H.; Tao, Y.; WANG, K.; JEDRUSZCZAK, D.; KNUTSON, B. (2016). Leveraging Crowd for Collecting and Maintaining Educational Resources for Privacy Learning. DEStech Transactions on Computer Science and Engineering (ameit ed.). DEStech Publications.
    http://dx.doi.org/10.12783/dtcse/ameit2017/12295.
  5. Dong, B.; Liu, R.; Wang, H. (2016). Trust-but-Verify: Verifying Result Correctness of Outsourced Frequent Itemset Mining in Data-Mining-As-a-Service Paradigm. IEEE Transactions on Services Computing (1 ed., vol. 9, pp. 18-32). Institute of Electrical and Electronics Engineers (IEEE).
    http://dx.doi.org/10.1109/tsc.2015.2436387.
  6. Wang, H.; Liu, R. (2015). Hiding outliers into crowd: Privacy-preserving data publishing with outliers. Data & Knowledge Engineering (vol. 100, pp. 94-115). Elsevier BV.
    http://dx.doi.org/10.1016/j.datak.2015.06.012.