电话：(0512)**
Email:hankai@ustc.edu.cn
主要研究方向：
大数据处理与数据挖掘、机器学习理论及应用、计算机网络与信息安全
韩恺，男，研究员，博士生导师。分别于1997年和2004年在中国科学技术大学少年班和计算机系获学士和博士学位；2008年于中国科学技术大学数学系计算数学专业博士后流动站出站；后曾在新加坡南洋理工大学计算机工程学院长期访问研究，于2015年以海外人才引进方式回国工作。主要研究兴趣包括大数据处理与机器学习、网络科学与数据挖掘、信息安全。近年来以第一作者身份在PVLDB、ICDE、MobiHoc、INFOCOM、TON、TKDE、TMC、TC等国际顶级会议和期刊发表论文多篇。 曾主持和参与国家自然科学基金项目、新加坡教育部MOE AcRF Tier 1、Tier 2项目、国家973项目等多项重大科研项目。曾担任TON、JSAC、TMC、TKDE、TPDS、TC、INFOCOM、MobiHoc等一系列国际顶级期刊和会议的审稿人。目前担任微软亚洲研究院(MSRA)合作导师，可招收博士后、博士生或硕士生联合指导和培养。



主要论著：
1.Kai Han*, Fei Gui, Xiaokui Xiao, Jing Tang, Yuntian He, Zongmai Cao, He Huang: Efficient and Effective Algorithms for Clustering Uncertain Graphs, PVLDB 12(6), 2019.

2.Kai Han*, etc: Organizing an influential social event under a budget constraint, IEEE Transactions on Knowledge and Data Engineering, in press.

3.Kai Han*, Huan Liu, Shaojie Tang, and Mingjun Xiao, Jun Luo: Differentially Private Mechanisms for Budget Limited Mobile Crowdsourcing, IEEE Transactions on Mobile Computing, in press

4.Kai Han*, Keke Huang, Xiaokui Xiao, Jing Tang, Aixin Sun, Xueyan Tang: Efficient Algorithms for Adaptive Influence Maximization, PVLDB 11(9): 1029-1040, 2018.

5.Kai Han*, He Huang, Jun Luo: Quality-Aware Pricing for Mobile Crowdsensing, IEEE/ACM Transactions on Networking, in press

6.Kai Han*, Chaoting Xu, Fei Gui, Shaojie Tang, He Huang, Jun Luo: Discount Allocation for Revenue Maximization in Online Social Networks. ACM MobiHoc 2018.

7.Kai Han*,Yuntian He,Xiaokui Xiao, Shaojie Tang, Fei Gui, Chaoting Xu,Jun Luo, Budget-Constrained Organization of Influential Social Events, IEEE ICDE 2018.

8.Kai Han*, Yuntian He, Haisheng Tan, Shaojie Tang, He Huang, Jun Luo: Online Pricing for Mobile Crowdsourcing with Multi-Minded Users. ACM MobiHoc 2017.

9.Kai Han*, He Huang, Jun Luo: Posted pricing for robust crowdsensing. ACM MobiHoc 2016.

10.Kai Han*, Z. Hu, J. Luo, and L. Xiang, “RUSH: RoUting and Scheduling for Hybrid Data Center Networks,” IEEE INFOCOM, 2015.

11.Kai Han*, C. Zhang, J. Luo, M. Hu and B. Veeravalli, “Truthful Scheduling Mechanisms for Powering Mobile Crowdsensing,” IEEE Transactions on Computers, Vol. 65, No. 1, pp 294-307, 2016

12.Kai Han*, C. Zhang, and J. Luo, “Taming the Uncertainty: Budget Limited Robust Crowdsensing through Online Learning,” IEEE/ACM Transactions on Networking，24(3): 1462-1475, 2016

13.Kai Han*, Jun Luo, Xiang Liu, Mingjun Xiao, and Liusheng Huang, "Achieving Energy Efficiency and Reliability for Data Dissemination in Duty-Cycled WSNs," IEEE/ACM Transactions on Networking, Vol. 23, No. 4, pp 1041-1052, August 2015.

14.Kai Han*, Yang Liu, and Jun Luo, "Duty-Cycle-Aware Minimum-Energy Multicasting in Wireless Sensor Networks," IEEE/ACM Transactions on Networking, vol. 21, no. 3, pp. 910-923, 2013.

15.Kai Han*, Jun Luo, Yang Liu, and A. Vasilakos, "Algorithm Design for Data Communications in Duty-Cycled Wireless Sensor Networks: A Survey," IEEE Communications Magazine, vol. 51, no. 7, pp. 107-113, 2013. (SCI一区)

16.Kai Han*, Liu Xiang, Jun Luo, and Yang Liu, "MEGCOM: Minimum-Energy Group COMmunication in Multi-hop Wireless Networks," IEEE Transactions on Vehicular Technology, vol. 63, no. 4, pp 1790-1801, 2014.

17.Kai Han*, Liu Xiang, Jun Luo, Ming-jun Xiao, and Liusheng Huang, "Energy-Efficient Reliable Data Dissemination in Duty-Cycled Wireless Sensor Networks," ACM MobiHoc, 2013.

18.Kai Han*, Liu Xiang, Jun Luo, and Yang Liu, "Minimum-Energy Connected Coverage in Wireless Sensor Networks with Omni-Directional and Directional Features," ACM MobiHoc, 2012.