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Ju Ren
H指数:61
被引数:1.2万
浏览量:0
个人简介
An associate professor with the Department of Computer Science and Technology, Tsinghua University, Beijing, China. Prior to joining Tsinghua, the scholar was a professor with the School of Computer Science and Engineering, Central South University, Changsha, China, in 2016-2021. Research interests include Internet-of-Things, edge computing, distributed and embedded AI. The scholar is a senior member of the IEEE and a member of the ACM, and was recognized as a highly cited researcher by Clarivate in 2020-2022.
教育背景
暂无内容
工作经历
2016.01 – 2021.12
School of Computer Science and Engineering, Central South University
professor
荣誉奖项
- Highly Cited Researcher（2022）｜Clarivate Analytics
- Highly Cited Researcher（2021）｜Clarivate Analytics
- Highly Cited Researcher（2020）｜Clarivate Analytics
- Best Young Researcher Award（2021）｜IEEE ComSoc Asia-Pacific Region
- Early Career Researcher Award（2019）｜IEEE Technical Committee on Scalable Computing
- Best Paper Award（2019）｜IEEE ICC'19
- Outstanding Paper Award（2019）｜IEEE HPCC'19
- Best Paper Award（2018）｜IEEE IoP'18
非实时数字孪生在移动边缘计算中的节能任务卸载
<sc>MagGuard</sc>：基于对比学习，通过内置磁力计检测移动窃听
面向小规模和大规模语言模型之间通信高效且无数据的协同微调
LiBre：面向运动鲁棒性的基于移动LiDAR的非接触式呼吸监测
通过后门植入对生成式语言模型进行的微调数据恢复攻击
FOVA：基于混合质量数据的离线联邦强化学习
使用气相色谱/质谱法研究腺肌病患者的子宫内膜代谢特征
MUCVR：基于边缘计算的面向交互式MVR的高质量多用户协作
数据驱动的协同边缘智能方法：机遇与挑战
IEEE Network
IF6.3
单模态设备间的跨模态联邦学习
MobiFuse：一种基于多数据融合的高精度端侧深度感知系统
莫尔通信：基于莫尔密码学的安全屏幕-相机通信
MASA：通过模态感知和安全聚合的多模态联邦学习
面向隐私增强和鲁棒性聚类的联邦学习
Squeezer：通过跨模型调度实现边缘视频分析的高效多DNN推理
通过无偏特征聚合实现公平的联邦学习
