Wei (Lisa) Li
Associate Professor, Associate Director of Graduate Studies Computer Science- Education
B.S., Mathematics & Applied Mathematics, China Agricultural University, 2008
M.S., Computer Science & Technology, Beijing University of Posts and Telecommunications, 2011
Ph.D., Computer Science, George Washington University, 2016
- Specializations
Secure and privacy-aware computing, secure and truthful auctions in dynamic spectrum access, game theory, algorithm design and analysis, resource management in cognitive radio networks and WiFi-based wireless access networks
- Biography
I received my Ph.D. degree in Computer Science from The George Washington University in 2016, my M.S. degree in Computer Science & Technology from Beijing University of Posts and Telecommunications in 2011, and my B.S. degree in Mathematics & Applied Mathematics from China Agricultural University in 2008.
My research mainly spans the areas of security and privacy for the Internet of Things and cyber-physical systems, secure and privacy-aware computing, big data, game theory, and algorithm design and analysis. I have obtained more than $1 million in grants from the U.S. National Science Foundation (NSF) and industry to support my research projects.
I have more than 45 publications, most of which were published in premier journals and conferences, including IEEE Internet of Things Journal, IEEE Transactions on Mobile Computing (TMC), IEEE/ACM Transactions on Networking (ToN), IEEE Journal on Selected Areas in Communications (JSAC), IEEE Transactions on Industrial Informatics (TII), IEEE Transactions on Wireless Communications (TWC), IEEE Transactions on Parallel and Distributed Systems (TPDS), ACM MobiHoc, IEEE INFOCOM, IEEE ICDM, and IEEE ICDCS.
- Publications
Saide Zhu, Zhipeng Cai, Huafu Hu, Yingshu Li, and Wei Li, “zkCrowd: a hybrid blockchain-based crowdsourcing platform,” IEEE Transactions on Industrial Informatics, vol. 16, no. 6, pp. 4196–4205, June 2020. (IF: 7.377)
Zhipeng Cai, Zhuojun Duan, and Wei Li, “Exploiting multi-dimensional task diversity in distributed auctions for mobile crowdsensing,” IEEE Transactions on Mobile Computing (early access), Apr. 2020. (IF: 4.474)
Zuobin Xiong, Wei Li, Qilong Han, and Zhipeng Cai, “Privacy-preserving auto-driving: a GAN-based approach to protect vehicular camera data,” IEEE International Conference on Data Mining (ICDM), Beijing, China, Nov. 2019, pp. 668–677. (Acceptance Ratio: 95 / 1046 = 9.08%)
Ling Tian, Jiaxin Li, Wei Li, Balasubramaniam Ramesh, and Zhipeng Cai, “Optimal contract-based mechanisms for online data trading markets,” IEEE Internet of Things Journal, vol. 6, no. 5, pp. 7800–7810, Oct. 2019. (IF: 9.515)
Zhuojun Duan, Wei Li, Xu Zheng, and Zhipeng Cai, “Mutual-preference driven truthful auction mechanism in mobile crowdsensing,” IEEE ICDCS 2019, Dallas, USA, July 2019, pp. 1233–1242. (Acceptance Ratio: 19.6%)
Saide Zhu, Wei Li, Hong Li, Ling Tian, Guangchun Luo, and Zhipeng Cai, “Coin hopping attack in blockchain-based IoT,” IEEE Internet of Things Journal, vol. 6, no. 4, pp. 4614–4626, June 2019. (IF: 9.515)
Chunqiang Hu, Wei Li, Xiuzhen Cheng, and Jiguo Yu, “A secure and verifiable secret sharing scheme for big data storage,” IEEE Transactions on Big Data, vol. 4, no. 3, pp. 341–355, Sept. 2018. The paper has been the 8th (2/2017), the 11th (3/2017), the 17th (4/2017), the 34th (5/2017), the 40th (6/2017), the 47th (7/2017) most frequently accessed document on IEEE Xplore for IEEE Transactions on Big Data.
Wei Li, Shengling Wang, Yong Cui, Xiuzhen Cheng, Ran Xin, Mznah A. Al-Rodhaan, and Abdullah Al-Dhelaan, “AP association for proportional fairness in multi-rate WLANs,” IEEE/ACM Transactions on Networking, vol. 22, no. 1, pp. 191–202, Feb. 2014. (IF: 3.597)
Wei Li, Xiuzhen Cheng, Tao Jing, Yong Cui, Kai Xing, and Wendong Wang, “Spectrum assignment and sharing for delay minimization in multi-hop multi-flow CRNs,” IEEE Journal on Selected Areas in Communications, vol. 31, no. 11, pp. 2483–2493, Nov. 2013. (IF: 9.302)
Wei Li, Xiuzhen Cheng, Tao Jing, and Xiaoshuang Xing, “Cooperative multi-hop relaying via network formation games in cognitive radio networks,” IEEE INFOCOM, Turin, Italy, Apr. 2013, pp. 971–979. (Acceptance Ratio: 280 / 1613 = 17.3%)