Bio

• I received my Ph.D. degree in the Department of Computer Science and Engineering, Shanghai Jiao Tong University, in 2021. I received my B.S. degree from the IEEE Honor Class, Shanghai Jiao Tong University, in 2017. I was quite fortunate to be advised by Prof. Fan Wu and Prof. Guihai Chen. I also felt very happy to work closely with Prof. Shaojie Tang and Prof. Zhenzhe Zheng. I was very lucky to ever mentor (learn and grow up together with) 20+ well-motivated undergraduate students, and they were somewhat naughty but highly enthusiastic.
• My research interests include data sharing (e.g., cross-device federated learning and data trading), deep learning (e.g., recommender systems and distributed optimization), as well as security and privacy (e.g., privacy preservation and verifiable computation). My long-term research goal is to facilitate ultra-scale data shared in an intelligent, secure, and economically-robust way.
• I held internships in Alibaba Group from Nov. 2018 up till now and in Intel Asia-Pacific R&D Ltd. from Nov. 2016 to Aug. 2017.

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News

• [Feb. 2021]I received Alibaba Group's Outstanding Research Intern in 2020!
• [Dec. 2020]I won the 5th Academic Star in Shanghai Jiao Tong University (10 recipients out of all the graduate students) and was ranked 5th! An interview by the university's graduate association is available from its WeChat's official account.
• [Dec. 2020]The work on client-level influence measurement in federated learning was accepted by AAAI 2021! The preprint is available from arXiv: 2012.10936.
• [Oct. 2020]The work on verifiable and privacy preserving prediction was accepted by IEEE TDSC!
• [Sept. 2020]The literature review on the trend from server-based to client-based machine learning was accepted by ACM CSUR!
• [Aug. 2020]The work on the federated submodel learning framework and its privacy issues was accepted by ACM MobiCom 2020!
• [June 2020]I received Yang Yuanqing Ph.D. Fellowship!
• [Feb. 2020]Two optimization-related work on the intermittent client availability and data cyclicity in federated learning are available from arXiv: 2002.07399 and arXiv: 2002.07454, respectively.

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Publications

Conferences

• Yihao Xue, Chaoyue Niu, Zhenzhe Zheng, Shaojie Tang, Chengfei Lv, Fan Wu, and Guihai Chen, Toward Understanding the Influence of Individual Clients in Federated Learning, in Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), Online, Feb. 2 - 9, 2021. [Slides]
• Chaoyue Niu, Fan Wu, Shaojie Tang, Lifeng Hua, Rongfei Jia, Chengfei Lv, Zhihua Wu, and Guihai Chen, Billion-Scale Federated Learning on Mobile Clients: A Submodel Design with Tunable Privacy, in Proceedings of the 26th Annual International Conference on Mobile Computing and Networking (MobiCom), Pages 405 - 418, London, UK, Sept. 21 - 25, 2020. DOI: 10.1145/3372224.3419188 [Slides]
• Chaoyue Niu, Zhenzhe Zheng, Fan Wu, Shaojie Tang, and Guihai Chen, Online Pricing with Reserve Price Constraint for Personal Data Markets, in Proceedings of the 36th IEEE International Conference on Data Engineering (ICDE), Pages 1978 - 1981, Dallas, Texas, USA, Apr. 20th - 24th, 2020. DOI: 10.1109/ICDE48307.2020.00218 [Slides]
• Chaoyue Niu, Zhenzhe Zheng, Shaojie Tang, Xiaofeng Gao, and Fan Wu, Making Big Money from Small Sensors: Trading Time-Series Data under Pufferfish Privacy, in Proceedings of IEEE International Conference on Computer Communications (INFOCOM), Pages 568 - 576, Paris, France, Apr. 29 - May 2, 2019. DOI: 10.1109/INFOCOM.2019.8737579 [Slides]
• Chaoyue Niu, Zhenzhe Zheng, Fan Wu, Shaojie Tang, Xiaofeng Gao, and Guihai Chen, Unlocking the Value of Privacy: Trading Aggregate Statistics over Private Correlated Data, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Pages 2031 - 2040, London, UK, Aug. 19 - 23, 2018. DOI: 10.1145/3219819.3220013 [Slides, Poster]
• Chaoyue Niu, Zhenzhe Zheng, Fan Wu, Xiaofeng Gao, and Guihai Chen, Trading Data in Good Faith: Integrating Truthfulness and Privacy Preservation in Data Markets, in Proceedings of the 33rd IEEE International Conference on Data Engineering (ICDE), Pages 223 - 226, San Diego, CA, USA, Apr. 19 - 22, 2017. DOI: 10.1109/ICDE.2017.80 [Slides, Poster]
• Minping Zhou, Chaoyue Niu, Zhenzhe Zheng, Fan Wu, and Guihai Chen, An Efficient, Privacy-Preserving, and Verifiable Online Auction Mechanism for Ad Exchanges, in Proceedings of IEEE Global Communications Conference (GLOBECOM), Pages 1 - 6, San Diego, CA, USA, Dec. 6 - 10, 2015. DOI: 10.1109/GLOCOM.2015.7417743

Journals

• Chaoyue Niu, Fan Wu, Shaojie Tang, Shuai Ma, and Guihai Chen, Toward Verifiable and Privacy Preserving Machine Learning Prediction, in IEEE Transactions on Dependable and Secure Computing (TDSC), Nov. 3, 2020. DOI: 10.1109/TDSC.2020.3035591
• Renjie Gu, Chaoyue Niu, Fan Wu, Guihai Chen, Chun Hu, Chengfei Lv, and Zhihua Wu, From Server-Based to Client-Based Machine Learning: A Comprehensive Survey, in ACM Computing Surveys (CSUR), Volume 54, Issue 1, Pages 6:1 - 6:36, Jan., 2021. DOI: 10.1145/3424660
• Chaoyue Niu, Zhenzhe Zheng, Fan Wu, Shaojie Tang, and Guihai Chen, Online Pricing with Reserve Price Constraint for Personal Data Markets, in IEEE Transactions on Knowledge and Data Engineering (TKDE), June 5, 2020. DOI: 10.1109/TKDE.2020.3000262
• Chaoyue Niu, Zhenzhe Zheng, Fan Wu, Shaojie Tang, Xiaofeng Gao, and Guihai Chen, ERATO: Trading Noisy Aggregate Statistics over Private Correlated Data, in IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 33, Issue 3, Pages 975 - 990, Mar. 1, 2021. DOI: 10.1109/TKDE.2019.2934100
• Chaoyue Niu, Zhenzhe Zheng, Fan Wu, and Guihai Chen, Personal Data Trading: From Protection to Pricing (Feature Article in Chinese), in Communications of the China Computer Federation (CCCF), Volume 15, Issue 2, Pages 39 - 45, Feb., 2019.
• Chaoyue Niu, Zhenzhe Zheng, Fan Wu, Xiaofeng Gao, and Guihai Chen, Achieving Data Truthfulness and Privacy Preservation in Data Markets, in IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 31, Issue 1, Pages 105 - 119, Jan. 1, 2019. DOI: 10.1109/TKDE.2018.2822727
• Chaoyue Niu, Minping Zhou, Zhenzhe Zheng, Fan Wu, and Guihai Chen, ERA: Towards Privacy Preservation and Verifiability for Online Ad Exchanges, in Elsevier Journal of Network and Computer Applications (JNCA), Volume 98, Pages 1 - 10, Nov. 15, 2017. DOI: 10.1016/j.jnca.2017.08.012

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Awards & Honors

• Outstanding Ph.D. Graduate, Shanghai Jiao Tong University, 2021
• NRIEE Ph.D. Fellowship, 2021
• Outstanding Research Intern in Alibaba Group, 2020
• Academic Star in Shanghai Jiao Tong University, Ranked 5th (University-Level), 2020
• Yang Yuanqing Ph.D. Fellowship, Ranked 1st (Department-Level), 2020
• National Scholarship, Top 1%, 2019
• National Scholarship, Top 1%, 2018
• ACM KDD 2018 Student Travel Grant Award, 2018
• Outstanding Reviewer of Elsevier Journal of Network and Computer Applications (JNCA), 2018
• Excellent Bachelor Thesis, Ranked 3rd (Department-Level), 2017
• China Undergraduate Mathematical Contest in Modeling, National 2nd Prize, 2016
• China Undergraduate Mathematical Contest in Modeling, 1st Prize in Shanghai Division, 2016

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Professional Services

I mainly served as a reviewer of the following conferences and journals:

• IEEE International Conference on Computer Communications (INFOCOM)
• ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc)
• IEEE/ACM International Symposium on Quality of Service (IWQoS)
• IEEE Transactions on Dependable and Secure Computing (TDSC)
• IEEE Journal on Selected Areas in Communications (JSAC)
• IEEE Transactions on Mobile Computing (TMC)
• IEEE/ACM Transactions on Networking (TON)
• INFORMS Journal on Computing (JOC)
• Journal of Network and Computer Applications (JNCA)

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Hobbies

I love diverse ball games, among which football comes first. My favorite player is Luka Modrić. As a midfielder, Modrić won the Golden Foot award in 2019, for his outstanding career results and intriguing personality.