Ergute Bao (Bob) is a PhD candidate at the National University of Singapore (NUS), advised by Professor Xiaokui Xiao. Bob obtained his B.Sc with First Class Honors in Computer Science from the Chinese University of Hong Kong (CUHK) in 2018, and has previously interned at SEA AI Lab and Alibaba DAMO Academy. Link to my CV.

Research Interest

Differential privacy and its applications in federated learning.

Publications

1. Fei Wei, Ergute Bao, Xiaokui Xiao, Yin Yang, and Bolin Ding.
   AAA: an Adaptive Mechanism for Locally Differentially Private Mean Estimation.
   50th International Conference on Very Large Data Bases (VLDB), 2024, to appear.

2. Ergute Bao, Dawei Gao, Xiaokui Xiao, Yaliang Li.
   Communication Efficient and Differentially Private Logistic Regression under the Distributed Setting.
   29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023.

3. Jianxin Wei, Ergute Bao, Xiaokui Xiao, Yin Yang.
   DPIS: an Enhanced Mechanism for Differentially Private SGD with Importance Sampling.
   The 29th ACM Conference on Computer and Communications Security (CCS), 2022. Slides.

4. Ergute Bao, Yizheng Zhu, Xiaokui Xiao, Yin Yang, Beng Chin Ooi, B.H.M. Tan, K.M.M. Aung.
   Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy.
   48th International Conference on Very Large Data Bases (VLDB), 2022. Technical report. Slides.
   Preprint of the Skellam Mechanism.
   Google’s implementation of the Skellam Mechanism in TF_Privacy.

5. Ergute Bao, Yin Yang, Xiaokui Xiao, and Bolin Ding.
   CGM: An Enhanced Mechanism for Streaming Data Collection with Local Differential Privacy.
   47th International Conference on Very Large Data Bases (VLDB), 2021. Technical report.

6. Ergute Bao, Xiaokui Xiao, Jun Zhao, Dongping Zhang, Bolin Ding.
   Synthetic Data Generation with Differential Privacy via Bayesian Networks.
   Journal of Privacy and Confidentiality (JPC), 2021, Vol. 11 No. 3.
   Invited paper. Based on our solution for the 2018 NIST Differential Privacy Synthetic Data Challenge.

Services

Reviewer for ICML 2022, DASFAA 2023 (demo) 2024 (demo), TKDE.

Honors

Dean’s Graduate Research Excellence Award in 2023, by NUS School of Computing.

First place in the 2020 NIST Differential Privacy Temporal Map Challenge. News.

Third place in the 2018 NIST Differential Privacy Synthetic Data Challenge. News.
Invited to JPC 2021 on Privacy Challenges.

Research Achievement Award in 2021, 2022 by NUS School of Computing.

Second place in the 2021 NIST DeID2 - A Better Meter Stick for Differential Privacy

Research Scholarship 2018-2022 by NUS.