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Raksha Ramakrishna
Raksha Ramakrishna
Postdoctoral Researcher, KTH Royal Institute of Technology
Verified email at kth.se - Homepage
Title
Cited by
Cited by
Year
Grid-graph signal processing (grid-GSP): A graph signal processing framework for the power grid
R Ramakrishna, A Scaglione
IEEE Transactions on Signal Processing 69, 2725-2739, 2021
662021
A user guide to low-pass graph signal processing and its applications: Tools and applications
R Ramakrishna, HT Wai, A Scaglione
IEEE Signal Processing Magazine 37 (6), 74-85, 2020
472020
Phasor measurement units optimal placement and performance limits for fault localization
M Jamei, R Ramakrishna, T Tesfay, R Gentz, C Roberts, A Scaglione, ...
IEEE Journal on Selected Areas in Communications 38 (1), 180-192, 2019
392019
Detection of False Data Injection Attack using Graph Signal Processing for the Power Grid
R Ramakrishna, A Scaglione
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2019
322019
A model for joint probabilistic forecast of solar photovoltaic power and outdoor temperature
R Ramakrishna, A Scaglione, V Vittal, E Dall’Anese, A Bernstein
IEEE Transactions on Signal Processing 67 (24), 6368-6383, 2019
282019
Distributed bayesian estimation with low-rank data: Application to solar array processing
R Ramakrishna, A Scaglione, A Spanias, C Tepedelenlioglu
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
182019
Detection and localization of PMU time synchronization attacks via graph signal processing
E Shereen, R Ramakrishna, G Dán
IEEE Transactions on Smart Grid 13 (4), 3241-3254, 2022
162022
ON MODELING VOLTAGE PHASOR MEASUREMENTS AS GRAPH SIGNALS
R Ramakrishna, A Scaglione
IEEE Data Science Workshop 2019, 2019
142019
A compressive sensing framework for the analysis of solar photo-voltaic power
R Ramakrishna, A Scaglione
2016 50th Asilomar Conference on Signals, Systems and Computers, 308-312, 2016
132016
Distribution systems ac state estimation via sparse ami data using graph signal processing
SS Saha, A Scaglione, R Ramakrishna, NG Johnson
IEEE Transactions on Smart Grid 13 (5), 3636-3649, 2022
72022
SODA: An Irradiance-Based Tool to Generate Sub-Minute Solar Power Stochastic Time Series
I Losada Carreńo, R Ramakrishna, A Scaglione, D Arnold, C Roberts, ...
7*2020
A Stochastic Model for Short-Term Probabilistic Forecast of Solar Photo-Voltaic Power
R Ramakrishna, A Scaglione, V Vittal
arXiv preprint arXiv:1706.05445, 2017
62017
Inferring Class-Label Distribution in Federated Learning
R Ramakrishna, G Dán
Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security …, 2022
32022
A Bayesian lower bound for parameters with bounded support priors
R Ramakrishna, A Scaglione
2020 54th annual conference on information sciences and systems (ciss), 1-6, 2020
32020
JOINT PROBABILISTIC FORECASTS OF TEMPERATURE AND SOLAR IRRADIANCE
R Ramakrishna, A Bernstein, E Dall’Anese, A Scaglione
ICASSP 2018, 2018
32018
Model-based interference cartography and visualization
PN Karthik, R Ramakrishna, G Joseph, CR Murthy, J Sebastian, ...
2016 Twenty Second National Conference on Communication (NCC), 1-6, 2016
32016
Sequential Experiment Design for Parameter Estimation of Nonlinear Systems using a Neural Network Approximator
R Ramakrishna, Y Shao, G Dán, N Kringos
European Journal of Control 74, 100859, 2023
12023
Differential Privacy for Class-based Data: A Practical Gaussian Mechanism
R Ramakrishna, A Scaglione, T Wu, N Ravi, S Peisert
IEEE Transactions on Information Forensics and Security, 2023
12023
TECoSA–Trends, Drivers, and Strategic Directions for Trustworthy Edge Computing in Industrial Applications
J Gross, M Törngren, G Dán, D Broman, E Herzog, I Leite, R Ramakrishna, ...
INSIGHT 25 (4), 29-34, 2022
12022
Inferring class label distribution of training data from classifiers: An accuracy-augmented meta-classifier attack
R Ramakrishna, G Dán
arXiv preprint arXiv:2211.04157, 2022
12022
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