Dr. Yang CAO (曹洋) Associate Professor Laboratory for Algorithmics Division of Computer Science and Information Technology Graduate School of Information Science and Technology Hokkaido University I am looking for Postdoctoral Fellows, PhD students, and Research Assistants. Please see Recruitment for more details. Research Interests Differential Privacy, Federated Learning, Data Economy, Trustworthy AI. Email: yang@ist.hokudai.ac.jp Short Bio Yang Cao is an Associate Professor at the Graduate School of Information Science and Technology, Hokkaido University. After earning a Ph.D. in Informatics from Kyoto University in 2017, he spent one year as a postdoctoral fellow at Emory hosted by Prof. Li Xiong. He then returned to Kyoto University in 2018 as a program-specific faculty member working with Prof. Masatoshi Yoshikawa until September 2022. Currently, he is an Associate Professor (tenured) at Hokkaido University and co-directing Laboratory for Algorithmics with Prof. Atsuyoshi Nakamura. He is passionate about studying and teaching on algorithmic trustworthiness in data science and AI. Two of his papers on data privacy were selected as best paper finalists in top-tier conferences IEEE ICDE 2017 and ICME 2020. He was a recipient of the IEEE Computer Society Japan Chapter Young Author Award 2019, Database Society of Japan Kambayashi Young Researcher Award 2021. His research projects were/are supported by JSPS, JST, MSRA, KDDI, LINE, WeBank, etc. Selected Publications (Google scholar, DBLP, Research Map) Secure Shapley Value for Cross-Silo Federated Learning. Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa. VLDB 2023 [arXiv] [Code] HDPView: Differentially Private Materialized View for Exploring High Dimensional Relational Data. Fumiyuki Kato, Tsubasa Takahashi, Shun Takagi, Yang Cao, Seng Pei Liew, Masatoshi Yoshikawa. VLDB 2022 [arXiv] [Code] Network Shuffling: Privacy Amplification via Random Walks. Seng Pei Liew, Tsubasa Takahashi, Shun Takagi, Fumiyuki Kato, Yang Cao, Masatoshi Yoshikawa. SIGMOD 2022 [arXiv] PCT-TEE: Trajectory-based Private Contact Tracing System with Trusted Execution Environment. (COVID-19 Response Efforts) Fumiyuki Kato, Yang Cao, Masatoshi Yoshikawa. ACM Transactions on Spatial Algorithms and Systems 2021 [ACM] [arXiv] [Code] [Slides] Preventing Manipulation Attack in Local Differential Privacy using Verifiable Randomization Mechanism. Fumiyuki Kato, Yang Cao, Masatoshi Yoshikawa. DBSec 2021 [arXiv] [Code] FLAME: Differentially Private Federated Learning in the Shuffle Model. Ruixuan Liu, Yang Cao, Hong Chen, Ruoyang Guo, Masatoshi Yoshikawa. AAAI 2021 [arXiv] [Slides] [Code] P3GM: Private High-Dimensional Data Release via Privacy Preserving Phased Generative Model. Shun Takagi, Tsubasa Takahashi, Yang Cao, Masatoshi Yoshikawa. IEEE ICDE 2020 [arXiv] Voice-Indistinguishability: Protecting Voiceprint with Differential Privacy under an Untrusted Server. Yaowei Han, Yang Cao, Sheng Li, Qiang Ma, Masatoshi Yoshikawa. ACM CCS 2020 Demo [PDF] [Code] [Slides] PGLP: Customizable and Rigorous Location Privacy through Policy Graph. Yang Cao, Yonghui Xiao, Shun Takagi, Li Xiong, Masatoshi Yoshikawa, Yilin Shen, Jinfei Liu, Hongxia Jin, Xiaofeng Xu. ESORICS 2020 [arXiv] [Code] [Slides] PCKV: Locally Differentially Private Correlated Key-Value Data Collection with Optimized Utility. Xiaolan Gu, Ming Li, Yueqiang Cheng, Li Xiong and Yang Cao. USENIX Security 2020 [arXiv] [Slides] [Youtube] FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection. Ruixuan Liu, Yang Cao, Masatoshi Yoshikawa, Hong Chen. DASFAA 2020 [arXiv] [Slides] [PDF] PANDA: Policy-aware Location Privacy for Epidemic Surveillance. (COVID-19 Response Efforts) Yang Cao, Shun Takagi, Yonghui Xiao, Li Xiong, Masatoshi Yoshikawa. VLDB 2020 Demo [arXiv] [Code] [Slides] Voice-Indistinguishability: Protecting Voiceprint in Privacy Preserving Speech Data Release. Yaowei Han, Sheng Li, Yang Cao, Qiang Ma, Masatoshi Yoshikawa. IEEE ICME 2020 Best Paper Finalist [arXiv] [Slides] [Code] Money Cannot Buy Everything: Trading Mobile Data with Controllable Privacy Loss. Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa. IEEE MDM 2020 [Paper] [Slides] Providing Input-Discriminative Protection for Local Differential Privacy. Xiaolan Gu, Ming Li, Li Xiong and Yang Cao. IEEE ICDE 2020 [arXiv] [Slides] Protecting Spatiotemporal Event Privacy in Continuous Location-Based Services. Yang Cao, Yonghui Xiao, Li Xiong, Liquan Bai and Masatoshi Yoshikawa. IEEE TKDE 2019 [arXiv] [IEEE] Efficient logging and querying for Blockchain-based cross-site genomic dataset access audit. Shuaicheng Ma, Yang Cao and Li Xiong. BMC Medical Genomics 2019 [arXiv] Geo-Graph-Indistinguishability: Protecting Location Privacy for LBS over Road Networks. Shun Takagi, Yang Cao, Yasuhito Asano, Masatoshi Yoshikawa. DBSec 2019 [Paper] PriSTE: From Location Privacy to Spatiotemporal Event Privacy. Yang Cao, Yonghui Xiao, Li Xiong, Liquan Bai. IEEE ICDE 2019, short paper. [Paper] [Poster] Supporting both Range Queries and Frequency Estimation with Local Differential Privacy. Xiaolan Gu, Ming Li, Yang Cao, Li Xiong. IEEE CNS 2019 [Paper] Quantifying Differential Privacy in Continuous Data Release under Temporal Correlations. Yang Cao, Masatoshi Yoshikawa, Yonghui Xiao, Li Xiong. IEEE TKDE 2018, the special issue on Best of ICDE 2017. [Paper] [Code] [Slides] [Poster] Research Grants Co-PI: JST CREST (PI: Prof. Kenjiro Taura at UTokyo), Privacy-Preserving Data Analysis and Secure Data Infrastructure for Real Applications, 2021-2027. Co-PI: JST/NSF SICORP (Japan PI: Prof. Masatoshi Yoshikawa at KyotoU, US PI: Prof. Li Xiong at Emory), Hyperlocal Risk Monitoring and Pandemic Preparedness through Privacy-Enhanced Mobility and Social Interactions Analysis, 2021-2024. PI: JSPS Grant-in-Aid for Scientific Research (B), A Principled Framework for Explaining, Choosing and Negotiating Privacy Parameters of Differential Privacy, 2022-2025. Co-PI: JSPS Grant-in-Aid for Scientific Research (A) (PI: Dr. Takao Murakami at AIST), 分散型ソーシャルグラフに向けた差分プライバシー技術, 2022-2027. Co-PI: JSPS Grant-in-Aid for Exploratory Research (PI: Prof. Masatoshi Yoshikawa at KyotoU), 個人の選好と報酬配分を考慮したパーソナルデータの健全で頑健な流通系構築に向けて, 2021-2024. PI: Kayamori Foundation of Informational Science Advancement, Privacy-Preserving Face Image Sharing, 2022-2023. PI: KDDI Foundation, Privacy-Preserving Spatiotemporal Data Collection and Analysis for Epidemic Surveillance, 2021-2023. PI: CCF-Tencent Rhino-Bird Young Faculty Open Research Fund, Privacy Protection and Incentivization in Federated Learning, 2020-2021. PI (Collaborator: Prof. Junichi Yamagishi at NII): NII Open Collaborative Research Funds, Speaker De-identification with Provable Privacy in Speech Data Release, 2020-2021. PI: Microsoft Research Asia Collaborative Research Grant 2020 (CORE16), Towards a Unified, Customizable and Rigorous Spatiotemporal Event Privacy Protection Framework, 2020. PI: JSPS Grant-in-Aid for Early-Career Scientists, Achieving Differential Privacy under Spatiotemporal Correlations, 2019-2021. Professional Service I am/was a program committee member for the following conferences/workshops: International Conference on Very Large Data Bases (VLDB) 2023, 2024. ACM SIGMOD International Conference on Management of Data (SIGMOD) 2022, 2024. ACM SIGKDDD Conference on Knowledge Discovery and Data Mining (KDD) 2022, 2023. IEEE International Conference on Data Engineering (ICDE) 2020, 2021, 2022, 2023. The AAAI Conference on Artificial Intelligence (AAAI) 2021, 2022 (Senior PC) 2023. ACM International Conference on Web Search and Data Mining (WSDM), 2022. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2022. IEEE International Conference on Big Data (IEEE BigData) 2020, 2022. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL) 2019, 2020, 2021. 2022. International Conference on Extending Database Technology (EDBT) 2022, 2023, 2024. International Conference on Database Systems for Advanced Applications (DASFAA) 2019, 2020, 2021, 2022, 2023. The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2023. IEEE International Conference on Multimedia and Expo (ICME) 2020, 2021, 2022. International Conference on Acoustics, Speech, & Signal Processing (ICASSP) 2023. Workshop on Privacy in the Electronic Society (WPES) 2022. Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy (DBSec) 2022. International Workshop on Blockchain and Distributed Ledger (BCDL) in conjunction with VLDB 2019. IEEE International Workshop on Blockchain and Data Management (BlockDM) 2019, 2020, 2021. International Workshop on Software Foundations for Data Interoperability (SFDI) 2019, 2020, 2021. International Workshop on Data Management and Analytics for Medicine and Healthcare (DMAH) in conjunction with VLDB 2020, 2021. International Workshop on Data Science for Data Marketplaces (DSDM) In conjunction with the International Conference on Very Large Data Bases 2022. I am/was invited reviewers for the following journals: Very Large Data Base (VLDB) Journal IEEE Transactions on Knowledge and Data Engineering (TKDE) IEEE Transactions on Information Forensics and Security (TIFS) IEEE Transactions on Dependable and Secure Computing (TDSC) Distributed and Parallel Databases (DAPD), Springer Information Sciences, Elsevier Computer Networks, Elsevier Computers & Security, Elsevier Future Generation Computer Systems (FGCS), Elsevier IET Information Security International Journal of Information Security (IJIS) IEEE Transactions on Big Data IEEE Transactions on Signal Processing IEEE Access Teaching Distributed Information Systems, Fall 2020/2021. Practice of Information Systems, Spring 2021/2022. PBL/FBL Privacy-enhancing Techniques for Combating COVID-19, Spring 2020 PBL/FBL Personal Data Market, Fall 2018.