Gal Morgenstern
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Gal Morgenstern |
I am a Ph.D student in the school of electrical and computer engeneering in Ben-Gurion University of the Negev.
I am part of Prof. Tirza Routtenberg's lab that specializes in signal processing and optimization with applications in power systems.
In my M.Sc. studies, I focused on anomaly detection in power systems.
Previously, in my BS.c. I majored in signal processing and communications.
Since 2018, I am posing as a teaching assistant in the signal processing introductory course.
Current Research Interests
Statistical graph signal processing with applications in smart grid:
Monitoring power system, state estimation, event detection
Power system cyber-security
Estimation after selection for graphical models
Sparse recovery for graphical models
Awards
Israeli Ministry of Science and Technology scholarship for excellent Ph.D. students (Jan 2020-Dec 2023)
Negev scholarship for excellent Ph.D. students (Sep 2019-Oct 2023)
M.Sc. graduation as part of the "Master degree direct track" program for excellent students which combines the undergraduate degree last year with the second-degree first year
B.Sc. graduation Cum Laude
Publications
G.Morgenstern and T. Routtenberg, "Structural-constrained Methods for the Identification of False Data Injection Attacks in Power Systems", IEEE Access 10 (2022): 94169-94185
G. Morgenstern, J. Kim, J. Anderson, G. Zussman, and T. Routtenberg, “Protection Against Graph Based False Data Injection Attacks on Power Systems”, in preparation, to be submitted to IEEE Trans. on Control of Network Systems.
G. Morgenstern and T. Routtenberg, "Sparse Recovery of Graph Signals",in preparation, to be submitted to IEEE Trans. Signal Processing
Conferences
G. Morgenstern and T. Routtenberg, "Network Constraints Against Cyber-attacks in Power Systems", 2019 Graph Signal Processing Workshop, University of Minnesota during June 5-7th, 2019 (Extended abstract)
G. Morgenstern, L. Dabush, and T. Routtenberg, “Graph Signal Processing for Electrical Networks”, Israeli Networking Day 2021, Ben-Gurion University. October 2021. Hybrid conference (presentation).
G. Morgenstern and T. Routtenberg, "Structural-constrained Methods for the Identification of Unobservable False Data Injection Attacks in Power Systems,” SPS/Eurasip Summer School, Data and Graph learning for Communications and Signal Processing, September 2022, Banja Luka.