姓名：李松泽
职称：教授
电话：
办公室：
个人主页：https://s3ic-lab.github.io/
邮箱：songzeli@seu.edu.cn; songzeli8824@outlook.com
教育背景
博士，电子工程专业，南加利福尼亚大学 (2011年 9月 – 2018 年 8 月)
学士，电子工程专业，纽约大学 (2008年1月 – 2011年8月)
工作经历
教授，东南大学网络空间安全学院 (2023年9月至今)
助理教授，香港科技大学（广州）物联网学域、人工智能学域 (2020年12月 – 2023年8月)
委任助理教授，香港科技大学计算机科学与工程系 (2021年8月 – 2023年6月)
访问助理教授，香港科技大学电子与计算机工程系 (2020年12月 – 2021年11月)
研究员, 斯坦福大学 (2020年1月 – 2020年8月)
研究科学家，Applied Protocol Research (2019年1月 – 2019年12月)
博士后研究员, 通信科学研究院, 南加利福尼亚大学 (2018年9月 – 2018年12月)
学术兼职
期刊客座编辑：
o Journal of Surveillance, Security and Safety, special issue on AI Security and Privacy，2023
o Entropy，special issue on Information Theory for Distributed Systems，2023
技术委员会委员
o KDD 2023 Workshop on Federated Learning for Distributed Data Mining (FL4Data-Mining-23)
o ICML 2023 Workshop on Federated Learning and Analytics in Practice (FL-ICML-23)
o SIGIR 2023 1st Workshop on Federated Learning for Information Retrieval (FLIRT@SIGIR 2023)
o IJCAI International Workshop on Trustworthy Federated Learning (FL-IJCAI-23)
o NeurIPS 2022 International Workshop on Federated Learning: Recent Advances and New Challenges (FL-NeurIPS-22)
o International Conference on Wireless Communications and Signal Processing (WCSP-22)
o IEEE Region 10 Conference (TENCON-22)
o IEEE Journal on Selected Areas in Communications, Special Issue on Communication-Efficient Distributed Learning over Networks (JSAC-CEDL-22)
o IJCAI International Workshop on Trustworthy Federated Learning (FL-IJCAI-22)
o AAAI International Workshop on Trustable, Verifiable and Auditable Federated Learning (FL-AAAI-22)
o AAAI Conference on Artificial Intelligence (22, 24)
o ICML International Workshop on Federated Learning for User Privacy and Data Confidentiality (FL-ICML-21)
o MobiCom Technologies for the Wireless Edge Workshop (EdgeTech-MobiCom-18)
审稿人
o 期刊杂志：IEEE Transactions on Information Theory, IEEE Transactions on Information Forensics and Security, IEEE Journal on Selected Areas in Information Theory, IEEE Transactions on Signal Processing, IEEE Transactions on Communications, IEEE Journal on Selected Areas in Communications, IEEE Transactions on Wireless Communications, IEEE Transactions on Knowledge and Data Engineering
o 会议： NeurIPS, ICML, ICLR, AAAI, CVPR, ISIT
研究领域
大模型安全
隐私保护的机器学习
安全多方计算
区块链安全及隐私
课题组长年招收本科生、硕士及博士研究生、博士后、研究助理，特别欢迎对科研有热情、有野心的同学加入团队。请机器学习、密码学、网安、信息、数学等相关专业的同学与我联系。
招生要求：
1. 对机器学习安全与隐私、联邦学习、大模型安全、密码及安全多方计算、区块链理论及系统、信息编码理论（至少一项）具有研究热情及相关的研究经验。在机器学习、安全、信息论国际顶会或顶刊上一作发表过论文的同学会优先考虑；
2. 敢于挑战自己。愿意积极交流及合作；
3. 良好的英语表达能力和英文学术写作能力；
4. 具备以下一项或多项技术特长的同学会优先考虑：
扎实的理论基础
概率与随机过程
机器学习理论、优化理论
密码学、安全多方计算理论
区块链理论
信息论、编码理论
优秀的编程和系统搭建能力
常用编程语言（Python、C++、Golang、Rust）
常用机器学习软件框架（PyTorch、Tensorflow）
区块链项目经验（Bitcoin、Ethereum smart contract、Hyperledger Fabric）
联系方式：
请将个人简历、成绩单、学术论文发送至邮箱songzeli@seu.edu.cn 或 songzeli8824@outlook.com。标题注明相应职位申请。
研究概况
东南大学青年首席教授、博士生导师，香港科技大学（广州）兼职助理教授；区块链应用监管教育部工程研究中心执行主任；国家高层次青年人才，江苏特聘教授，华为紫金青年学者。博士毕业于美国南加州大学，曾任斯坦福大学研究员，香港科技大学助理教授。研究方向为人工智能安全与隐私，大模型安全，隐私保护的机器学习，区块链安全与可扩展性。在安全四大顶会（IEEE S&P、USENIX Security、ACM CCS、NDSS）、机器学习三大顶会（ICML、NeurIPS、ICLR）等旗舰会议期刊发表论文50余篇（17篇CCF-A）。获得NeurIPS 2020 联邦学习研讨会最佳论文奖，开源软件FedML（https://github.com/FedML-AI/FedML）在GitHub平台获4200颗星、779次分叉。开创性地提出使用信息论工具提升分布式学习安全及效率：单篇论文获536次引用，出版学术专著一部。担任3个国际期刊客座编辑，20个国际期刊及会议技术委员会成员。受邀在3个国际会议作主题报告。
最近动态
研究课题
国家自然科学基金委员会，青年科学基金项目，“信息论在加强联邦学习系统安全性方面的应用，”2022-01-01 至 2024-12-31，30万元，主持。
奖励与荣誉
国家高层次青年人才
江苏特聘教授
东南大学青年五四奖章
2021-2024连续4年入选斯坦福全球前2%顶尖科学家榜单
NeurIPS 2020 Workshopon Scalability, Privacy, and Security in Federated Learning最佳论文奖
课程信息
人工智能安全与隐私（全英）
学术成果
会议主题报告
“Coded Merkle Tree: Solving Data Availability Attacks in Blockchains,” The Third IEEE International Workshop on Blockchain and Mobile Applications (BlockApp 2021)
“DeepPrivate: Scalable Distributed DNN Training with Data and Model Privacy,” Sixth London Symposium on Information Theory (LSIT 2021)
“Nakamoto Meets Shannon: Scaling Blockchains Using Codes,” Iran Workshop on Communication and Information Theory (IWCIT 2021)
专题论文
1. S. Li, and A. S. Avestimehr, “Coded Computing: Mitigating Fundamental Bottlenecks in Large-scale Distributed Computing and Machine Learning”, Foundations and Trends in Communications and Information Theory,Vol. 17: No. 1, pp 1-148.
期刊发表论文 （标注谷歌学术被引用次数和中国计算机学会(CCF)分类）
1. H. Hu, Y. Wu, Y. Shi, S. Li, C. Jiang, and W. Zhang, “Communication-Efficient Coded Computing for Distributed Multi-Task Learning,” IEEE Transactions on Communications, Apr. 2023. （B类）
2. T. Jahani-Nezhad, M. A. Maddah-Ali, S. Li, and G. Caire, “Swiftagg+: Achieving asymptotically optimal communication loads in secure aggregation for federated learning,” IEEE Journal on Selected Areas in Communications, vol. 41, no. 4, pp. 977–989, Mar. 2023. （11次，A类）
3. J. Zhu, S. Li, and J. Li, “Information-Theoretically Private Matrix Multiplication From MDS-Coded Storage,” IEEE Transactions on Information Forensics and Security, vol. 18, pp. 1680-1695, 2023. （2次，A类）
4. J. Zhu, S. Li, “A Systematic Approach towards Efficient Private Matrix Multiplication,” IEEE Journal on Selected Areas in Information Theory, vol. 3, no. 2, pp. 257-274, June 2022. （8次）
5. J. Zhu, Q. Yan, X. Tang, and S. Li, “Symmetric Private Polynomial Computation From Lagrange Encoding,” IEEE Transactions on Information Theory, vol. 68, no. 4, pp. 2704-2718, Jan. 2022. （4次，A类）
6. S. Li, M. Yu, C. Yang, A. S. Avestimehr, S. Kannan, and P. Viswanath, “PolyShard: Coded Sharding Achieves Linearly Scaling Efficiency and Security Simultaneously,” IEEE Transactions on Information Forensics & Security, vol. 16, pp. 249-261, July 2020.（106次，A类）
7. S. Li, M. A. Maddah-Ali, and A. S. Avestimehr, “Coding for distributed Fog computing,” IEEE Communications Magazine, vol. 55, no. 4, pp. 34-40, Apr. 2017. （149次）
8. S. Li, Q. Yu, M. A. Maddah-Ali, and A. S. Avestimehr, “A Scalable Framework for Wireless Distributed Computing,” IEEE/ACM Transactions on Networking, vol. 25, no. 5, pp. 2643-2654, Oct. 2017. （111次，A类）
9. S. Li, Q. Yu, M. A. Maddah-Ali, and A. S. Avestimehr, “A Fundamental Tradeoff between Computation and Communication in Distributed Computing,” IEEE Transactions on Information Theory, vol. 64, no. 1, pp. 109-128, Jan. 2018. （430次，A类）
10.AR. Elkordy1, S. Li1, Q. Yu, M. A. Maddah-Ali, and A. S. Avestimehr, “Compressed Coded Distributed Computing,” IEEE Transactions on Communications, Jan. 2021. （6次，B类）
11.S. Li, D. Kao, and A. S. Avestimehr, “Rover-to-Orbiter Communication in Mars: Taking Advantage of the Varying Topology,” IEEE Transactions on Communications, Vol. 64, No. 2, Feb. 2016. （6次，B类）
会议发表论文（标注被引用次数和中国计算机学会(CCF)分类）
1. S. Li, D. Yao, and J. Liu, FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models, ICML, July 2023. （A类）
2. Y. Dai and S. Li, “Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning,” ICML, July 2023. （A类）
3. J. Tang, J. Zhu, S. Li, and L. Sun, “Secure Embedding Aggregation for Federated Representation Learning,” IEEE ISIT, June 2023.
4. Z. Huang, S. Li, K. Liang, and Y. Wu, “Secure Gradient Aggregation for Wireless Multi-Server Federated Learning,” IEEE ISIT, June 2023.
5. H. Hu, S. Li, M. Cheng, and Y. Wu, “Coded Distributed Computing for Hierarchical Multi-Task Learning,” IEEE ITW, Apr. 2023.
6. J. Shao, Y. Sun, S. Li, and J. Zhang, “DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing,” NeurIPS, Nov. 2022. （4次，A类）
7. J. Zhu and S. Li, “Generalized Lagrange Coded Computing: A Flexible Computation-Communication Tradeoff,” IEEE International Symposium on Information Theory (ISIT 2022), June 2022.
8. T. Jahani-Nezhad, M. A. Maddah-Ali, S. Li, and G. Caire, “SwiftAgg: Communication-Efficient and Dropout-Resistant Secure Aggregation for Federated Learning with Worst-Case Security Guarantees,” IEEE International Symposium on Information Theory (ISIT 2022), June 2022. （8次）
9. Y. Sun, J. Shao, S. Li, Y. Mao, and J. Zhang “Stochastic Coded Federated Learning with Convergence and Privacy Guarantees,” IEEE International Symposium on Information Theory (ISIT 2022), June 2022. （6次）
10.J. So, C. Yang, S. Li, Q. Yu, R. E. Ali, B. Guler, and S. Avestimehr. “LightSecAgg: A Lightweight and Versatile Design for Secure Aggregation in Federated Learning,” Proceedings of Machine Learning and Systems 4，2022. （44次）
11.C. He, S. Li, J. So, X. Zeng, M. Zhang, H. Wang, X. Wang, P. Vepakomma, A. Singh, H. Qiu, et al. “Fedml: A Research Library and Benchmark for Federated Machine Learning,” NeurIPS-20 Workshop on Scalability, Privacy, and Security in Federated Learning (NeurIPS-SpicyFL 20 Best Paper Award), 2020. （288次，A类）
12.J. Liang, W. Jiang, and S. Li , “OmniLytics: A Blockchain-based Secure Data Mark et for Decentralized Machine Learning, ” ICML International Workshop on Federated Learning for User Privacy and Data Confidentiality, July, 2021. （4次）
13.S. Li, M. Yu, C. Yang, A. S. Avestimehr, S. Kanna, and P. Viswanath, “PolyShard: Coded Sharding Achieves Linearly Scaling Efficiency and Security Simultaneously,” IEEE International Symposium on Information Theory (ISIT 2020), June 2020. （19次）
14.M. Yu, S. Sahraei, S. Li, A. S. Avestimehr, S. Kanna, and P. Viswanath, “Coded Merkle Tree: Solving Data Availability Attacks in Blockchains,” Financial Cryptography and Data Security, Feb. 2020. （62次，C类）
15.S. Li, S. Sahraei, M. Yu, A. S. Avestimehr, S. Kanna, and P. Viswanath, “Coded State Machine - Scaling State Machine Execution under Byzantine Faults,” ACM Symposium on Principles of Distributed Computing (PODC 2019), July 2019. （4次，B类）
16.Q. Yu, S. Li, N. Raviv, M. Mousavi Kalan, M. Soltanolkotabi, and A. S. Avestimehr, “Lagrange Coded Computing: Optimal Design for Resiliency, Security, and Privacy,” International Conference on Artificial Intelligence and Statistics (AISTATS 2019), Apr. 2019. （303次，C类）
17.Q. Yu, N. Raviv, S. Li, M. Mousavi Kalan, M. Soltanolkotabi, and A. S. Avestimehr, “Lagrange Coded Computing: Optimal Design for Resiliency, Security, and Privacy,” NeurIPS MLSys workshop, Dec. 2018. （A类）
18.Y. Li, M. Yu, S. Li, A. S. Avestimehr, NS Kim, and A. Schwing, “Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training,” Neural Information Processing Systems (NeurIPS 2018), Dec. 2018. （98次，A类）
19.M. Yu, Z. Lin, H. V. Narra, S. Li, Y. Li, NS Kim, A. Schwing, M. Annavaram, and A. S. Avestimehr, “GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training,” Neural Information Processing Systems (NeurIPS 2018), Dec. 2018. （66次，A类）
20.S. Li, M. A. Maddah-Ali, and A. S. Avestimehr, “Compressed Coded Distributed Computing,” IEEE International Symposium on Information Theory (ISIT 2018), June 2018. （30次）
21.S. Li, M. Mousavi Kalan, A. S. Avestimehr, and M. Soltanolkotabi, “Near- Optimal Straggler Mitigation for Distributed Gradient Methods,” the 7th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics, May 2018. (96次，B类)
22.S. Li, M. A. Maddah-Ali, and A. S. Avestimehr, “Architectures for Coded Mobile Edge Computing,” Fog World Congress, Oct. 2017. （6次)
23.S. Li, M. A. Maddah-Ali, and A. S. Avestimehr, “Communication-AwareComputing for Edge Processing,” IEEE International Symposium on Information Theory (ISIT 2017), June 2017. （26次）
24.S. Li, S. Supittayapornpong, M. A. Maddah-Ali, and A. S. Avestimehr, “Coded Terasort,” the 6th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics, May 2017. （62次，B类）
25.Q. Yu, S. Li, M. A. Maddah-Ali, and A. S. Avestimehr, “How to optimally allocate resources for coded distributed computing?,” IEEE ICC, May 2017. （52次，C类）
26.S. Li, M. A. Maddah-Ali, and A. S. Avestimehr, “A Unified Coding Framework for Distributed Computing with Straggling Servers,” IEEE NetCod, Dec. 2016. （182次，C类）
27.S. Li, Q. Yu, M. A. Maddah-Ali, and A. S. Avestimehr, “Edge-Facilitated Wireless Distributed Computing,” IEEE GLOBECOM, Dec. 2016. （30次，C类）
28.S. Li, Q. Yu, M. A. Maddah-Ali, and A. S. Avestimehr, “Coded Distributed Computing: Fundamental Limits and Practical Challenges,” IEEE Asilomar Conference on Signals, Systems, and Computers, Nov. 2016. （24次）
29.S. Li, Q. Yu, M. A. Maddah-Ali and A. S. Avestimehr, “A Scalable Coded Computing Framework for Edge-Facilitated Wireless Distributed Computing,” The First IEEE/ACM Symposium on Edge Computing, Oct. 2016. （8次）
30.S. Li, M. A. Maddah-Ali, and A. S. Avestimehr, “Coded Distributed Computing: Straggling Servers and Multistage Dataflows,” 54rd Annual Allerton Conference on Communication, Control, and Computing, Sept. 2016. （53次）
31.S. Li, M. A. Maddah-Ali, and A. S. Avestimehr, “Fundamental Tradeoff between Computation and Communication in Distributed Computing,” IEEE International Symposium on Information Theory (ISIT 2016), July 2016.
32.S. Li, M. A. Maddah-Ali, and A. S. Avestimehr, “Coded MapReduce,” 53rd Annual Allerton Conference on Communication, Control, and Computing, Sept. 2015. （177次）
33.S. Li, D. Kao, and A. S. Avestimehr, “Rover-to-Orbiter Communication in Mars: Taking Advantage of the Varying Topology,” IEEE International Symposium on Information Theory (ISIT 2015), June 2015.
34.S. Li, E. Akyol and U. Mitra, “Power Allocation for Gaussian Multiple Access Channel with Noisy Cooperative Links,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), May 2014. （6次，B类）
35.S. Li, U. Mitra and A. Pandharipande, “Cooperative Spectrum Sharing with Joint Receiver Decoding,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), May 2013. （1次，B类）
36.S. Li, U. Mitra, V. Ratnam and A. Pandharipande, “Jointly Cooperative Decode-and-Forward Relaying for Secondary Spectrum Access,” Conference on Information Sciences and Systems (CISS 2012), Mar. 2012. （5次）
新闻发表文章
1. S. Li, and A. S. Avestimehr, “Coding for Distributed Computing on the Edge: Enabling Robust and Resilient Edge Computing in a Service Oriented Net- work,” IEEE ComSoc Technology News (CTN) August Issue, 2018. Online at https://www.comsoc.org/ctn/coding-distributed-computation-edge- enabling-robust-and-resilient-edge-computing-service.
技术报告
1. P. Sakulkar, P. Ghosh, A. Knezevic, J. Wang, Q. Nguyen, J. Tran, H.V. K.
Giri Narra, Z. Lin, S. Li, M. Yu, B. Krishnamachari, S. Avestimehr, M. Annavaram, “WAVE: A Distributed Scheduling Framework for Dispersed Computing,” USC ANRG Technical Report, ANRG 2018-01, 2018.Online at http://anrg.usc.edu/www/papers/wave_dispersed_computing_ANRGTechReport.pdf.
海报
1. S. Li, Q. Yu, “Accelerating Cloud Computing via Coding,” Qualcomm Innovation Fellowship Finalists Poster, Apr. 2017.
2. S. Li, Q. Yu, M. A. Maddah-Ali and A. S. Avestimehr, “Coded Distributed Computing: Fundamental Limits and Practical Impacts,” Information Theory and Applications Workshop (ITA) Graduation Day Poster, Feb. 2017.
3. S. Li, M. A. Maddah-Ali and A. S. Avestimehr, “Coded MapReduce: Trading Computation for Bandwidth via Coding,” 2015 EE Research Festival, University of Southern California, Nov. 2015.
4. S. Li and U. Mitra, “A Jointly Cooperative Scheme for Secondary Spectrum Access,” 2013 EE Research Festival, University of Southern California, Feb. 2013.
5. S. Li and U. Mitra, “Cooperative Spectrum Sharing with joint receiver decoding,” CSI’s 30th Anniversary Conference and Celebration, USC Davidson Conference Center, Nov. 2012.
6. S. Li and U. Mitra, “Jointly cooperative decode-and-forward relaying for secondary spectrum access,” 2012 North American School of Information Theory, Cornell University, June 2012.
