Kui Ren is affiliated with Zhejiang University in China and has an extensive publication record in computer science, with a particular focus on security, privacy, and machine learning. Their research spans several subfields, including artificial intelligence, information systems, computer networks and communications, signal processing, and computer vision and pattern recognition.
Their work covers a variety of major topics such as adversarial robustness in machine learning, cryptography and data security, privacy-preserving technologies in data, advanced malware detection techniques, anomaly detection techniques and applications, internet traffic analysis and secure e-voting, as well as blockchain technology applications and security.
Kui Ren has published research in leading venues, frequently contributing to:
The scientist often collaborates with several coauthors, frequently working with Feng Lin, Zhongjie Ba, Zhibo Wang, Zhan Qin, and Li Lü.
Among Kui Ren's recent papers are:
Kui Ren's contributions to the fields of wireless system security and cloud data security have been formally recognized. The scientist was named an ACM Fellow in 2020 and an IEEE Fellow in 2016 for their work in security and privacy in cloud computing and wireless networks. Additionally, they received the ACM Distinguished Member designation in 2017.
Ning Cao;Cong Wang;Ming Li;Kui Ren
Cong Wang;Qian Wang;Kui Ren;Wenjing Lou
Shucheng Yu;Cong Wang;Kui Ren;Wenjing Lou
Cong Wang;Qian Wang;Kui Ren;Wenjing Lou
Cong Wang;S. S. M. Chow;Qian Wang;Kui Ren
Qian Wang;Cong Wang;Kui Ren;Wenjing Lou
Ming Li;Shucheng Yu;Yao Zheng;Kui Ren
Qian Wang;Cong Wang;Jin Li;Kui Ren
Jin Li;Qian Wang;Cong Wang;Ning Cao
Kui Ren;Cong Wang;Qian Wang
Cong Wang;Ning Cao;Jin Li;Kui Ren
Shucheng Yu;Cong Wang;Kui Ren;Wenjing Lou
Cong Wang;Qian Wang;Kui Ren;Ning Cao
Zhangjie Fu;Kui Ren;Jiangang Shu;Xingming Sun
Ming Li;Wenjing Lou;Kui Ren
Cong Wang;Ning Cao;Kui Ren;Wenjing Lou
Zhihua Xia;Xinhui Wang;Liangao Zhang;Zhan Qin
Ming Li;Shucheng Yu;Kui Ren;Wenjing Lou
Cong Wang;Kui Ren;Wenjing Lou;Jin Li
Kui Ren;Tianhang Zheng;Zhan Qin;Xue Liu
Jianfeng Wang;Hua Ma;Qiang Tang;Jin Li
If you think any of the details on this page are incorrect, let us know.
Exploring a career in computer science opens the door to a variety of flexible online learning opportunities. Many students choose to start with an associate degree, and earning your associate degree online can be a fast, practical way to get qualified for entry-level positions or lay the foundation for further study.
For those looking to advance their skills, pursuing one of the most useful masters degrees in computer science or related fields can significantly enhance job prospects and salary potential.
Affordability is another key concern. Fortunately, there are many most affordable online colleges offering flexible computer science programs without sacrificing quality.
If your academic record isn’t perfect, don’t be discouraged. There are excellent online colleges that accept 2.0 gpa, enabling more students from diverse backgrounds to pursue their computer science goals.
University of Sydney
Oak Ridge National Laboratory
University of Pittsburgh
Florida State University
University of Michigan–Ann Arbor
Florida State University
Beth Israel Deaconess Medical Center
Creighton University
Aarhus University
University of British Columbia
Aarhus University
Stanford University
The University of Texas Southwestern Medical Center
Kyoto University
Harvard University
University College London