Administrative Title:
Assistant Professor, Young Talents
Professional Title:
None
Office:
Room 1002, Mingde Main Building
Email:
xinyue.wang@ruc.edu.cn
Education
2018.09-2024.05，Ph.D. in Management Science and Information System，Rutgers University
2016.09-2018.02，M.S. in Economics，Rutgers University
2012.09-2016.06，B.S in Statistics，Chongqing University
Work Experience
2024.08- Present，Assistant Professor, School of Statistics, Renmin University of China
Research Interests
Data security and privacy, generative models, federated learning, privacy-preserving genomics
Honors and Awards
1. Best Reviewer Award, AMIA Informatics Summit, AMIA, 2024
2. Financial Crime Track 1st place (Team Scarlet-Pets), US-UK Privacy Enhancing Technologies Challenge, 2023
Funding
1. The Start-up Fund for New Teachers of RUC, P.I., 2025.5 - 2028.4
Publications
1. Wang, X., Asif, H., and Vaidya, J. (2025), “Data Synthesis Reinvented: Preserving Missing Patterns for Enhanced Analysis”, IEEE Transactions on Knowledge and Data Engineering,
2. Min, S., Asif, H., Wang, X., and Vaidya, J. (2025), “Cafe: Improved Federated Data Imputation by Leveraging Missing Data Heterogeneity”, IEEE Transactions on Knowledge and Data Engineering, vol. 37,pp. 2266-2281, 2025
3. Wang, X., Min, S., and Vaidya, J. (2025), “Descriptor: Synthetic Genomic Dataset with Diverse Ancestry (SynGen6)”, IEEE Data Descriptions, vol. 2, pp. 1-7, 2025.
4. Wang, X., Min, S., and Vaidya, J. (2024), “Exploring the use of Artificial Genomes for Genome-wide Association Studies through the lens of Utility and Privacy”, In AMIA Annual Symposium Proceedings, Vol. 2024
5. Asif, H., Min, S., Wang, X., and Vaidya, J. (2024) “U.S.-U.K. PETs Prize Challenge: Anomaly Detection via Privacy-Enhanced Federated Learning”, IEEE Transactions on Privacy, vol. 1, pp. 3-18, 2024.
6. Wang, X., Dervishi, L., Li, W., Ayday, E., Jiang, X., and Vaidya, J.(2023), “Privacy-Preserving Federated Genome-wide Association Studies via Dynamic Sampling”, Bioinformatics, 39(10), btad639.
7. Wang, X., Asif, H., and Vaidya, J. (2023), “Preserving Missing Data Distribution in Synthetic Data”, In Proceedings of the ACM Web Conference 2023 (WWW ’23). pp. 2110-2121.
8. Wang, X., Dervishi, L., Li, W., Jiang, X., Ayday, E., and Vaidya, J.(2023) “Efficient Federated Kinship Relationship Identification”. AMIA Joint Summits on Translational Science proceedings, 2023, 534.
9. Dervishi, L., Wang, X., Li, W., Halimi, A., Vaidya, J., Jiang, X., Ayday, E. (2022), “Facilitating Federated Genomic Data Analysis by Identifying Record Correlations while Ensuring Privacy”, In AMIA Annual Symposium Proceedings, Vol. 2022, p. 395.
10. Wang X, Jiang X, Vaidya J. (2021), “Efficient verification for outsourced genomewide association studies”, Journal of biomedical informatics, 117, p.103714.
Teaching
1. Graduate：Big Data Distributed Computing
2. Undergraduate: Big Data Parallel Computing