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Di Wang

Assistant Professor, Computer Science

Computer, Electrical and Mathematical Science and Engineering Division

di.wang@kaust.edu.sa


Affiliations

Education Profile

  • 2020 Ph.D State University of New York at Buffalo
  • 2015 M.S. Western University, 2014 B.S. Shandong University

Research Interests

Professor Wang's interests are differential privacy, privacy-preserving machine learning, privacy-preserving data mining, privacy attack in machine learning, trustworthy machine learning, statistical learning theory. He is also interested in trustworthy issues in digital healthcare, biomedical imaging and bioinformatics.​

Selected Publications

  • Di Wang, Hanshen Xiao, Srini Devadas, and Jinhui Xu. "On Differentially Private Stochatsic Optimization with Heavy-tailed Data" In International Conference on Machine Learning. 2020.
  • Di Wang, Changyou Chen, and Jinhui Xu. "Differentially private empirical risk minimization with non-convex loss functions." In International Conference on Machine Learning, pp. 6526-6535. 2019.
  • Di Wang, and Jinhui Xu. "On sparse linear regression in the local differential privacy model." In International Conference on Machine Learning, pp. 6628-6637. 2019.
  • Di Wang, Marco Gaboardi, and Jinhui Xu. "Empirical risk minimization in non-interactive local differential privacy revisited." In Advances in Neural Information Processing Systems, pp. 965-974. 2018.
  • Di Wang, Minwei Ye, and Jinhui Xu. "Differentially private empirical risk minimization revisited: Faster and more general." In Advances in Neural Information Processing Systems, pp. 2722-2731. 2017.