Chuanyi Ji received a B.S. degree from Tsinghua University in Beijing, China in 1983, an M.S. degree from the University of Pennsylvania in 1986, and a Ph.D. degree from the California Institute of Technology in 1992, all in Electrical Engineering. She joined the faculty at Rensselaer Polytechnic Institute in 1991. She spent a sabbatical year at Bell-Labs Lucent in 1999, and was a visiting faculty at MIT in the fall of 2000. She joined the ECE faculty as an associate professor in the fall of 2001.
Chuanyi Ji's research lies in both basic and applied areas of networking and machine learning. Her research interests include investigating fundamental properties and deriving engineering solutions for modeling and managing heterogeneous large networks, developing learning algorithms and their applications in networks, and seeking knowledge and insights from large-scale network data.
Research she has been involved with includes resilience of the energy grid and communication networks, proactive anomaly detection, scalability of measurement-based network monitoring, and performance and efficiency issues of learning algorithms.
Modeling and managing heterogeneous and large networks
Learning algorithms, statistics and large-scale data
- Early Career Award, RPI 2000
- NSF Career Award, 1995
- Ming Li Scholarship, Caltech 1989
- Honor graduate, Tsinghua University, 1983
Chuanyi Ji, Yun Wei, and H. Vincent Poor, “Resilience of Energy Infrastructure and Services: Modeling, Data Analytics and Metrics.” Proceedings of the IEEE - Special Issue of Power Grid Resilience. 105 (7), 1354-1366, July 2017.
Chuanyi Ji, Yun Wei, Henry Mei, Jorge Calzada, Matthew Carey, Steve Church, Timothy Hayes, Brian Nugent, Gregory Stella, Matthew Wallace, Joe White, & Robert Wilcox. "Large-Scale Data Analysis of Power Grid Resilience across Multiple US Service Regions". Nature Energy, May 2016. DOI: http://dx.doi.org/10.1038/nenergy.2016.52
Y. Wei, C. Ji, F. Galvan, S. Couvillon, G. Orellana, & J. Momoh, “Learning Geo-Temporal Non-Stationary Failure and Recovery of Power Distribution,” Special issue on Learning in Non-stationary and Evolving Environments, IEEE Trans. on Neural Networks, Vol. 25, No.1, 229-240. Jan., 2014
G. Liu & C. Ji, “Scalability of Network-Failure Resilience: Analysis Using Multi-Layer Probabilistic Graphical Models,” IEEE/ACM Trans. Networking, Vol. 17, No. 1, pp. 319-331, Feb. 2009
M. Thottan & C. Ji, “Anomaly Detection in IP Networks,” Special Issue of Signal Processing in Networking, IEEE Trans. Signal Processing, vol. 51, No. 8, pp. 2191-2204, Aug. 2003
C. Ji & A. Elwalid, “Measurement-Based Network Monitoring: Achievable Performance and Scalability,” Special Issue on Recent Advances in Fundamentals of Network Management, IEEE Journal of Selected Areas of Communications (JSAC), Vol. 20, No. 4, pp. 714-725, May 2002
S. Ma and C. Ji, ``Performance and Efficiency: Recent Advances in Supervised Learning'', Proceedings of the IEEE, Volume: 87 Issue: 9, Sept. 1999, Page(s): 1519 -1535
C. Ji and S. Ma, ``Combinations of Weak Classifiers,'' IEEE Trans. Neural Networks, Special Issue on Neural Networks and Pattern Recognition, Volume 8, Jan. 1999, Page(s): 32-42
Last revised September 13, 2018