journals

1. a. ahmed et al., “spatio-temporal deep graph network for event detection, localization and classification in cyber-physical electric distribution system,” in ieee transactions on industrial informatics, doi: 10.1109/tii.2023.3290942.
2. tushar, z. nie, a. srivastava and s. basumallik, “measuring and enabling transmission systems resiliency with renewable wind energy systems,” in ieee transactions on industry applications, doi: 10.1109/tia.2023.3328572.
3. foroutan a, basumallik s, srivastava a. estimating and calibrating der model parameters using levenberg–marquardt algorithm in renewable rich power grid. energies. 2023; 16(8):3512. https://doi.org/10.3390/en16083512
4. a. ahmed, s. k. sadanandan, s. pandey, s. basumallik, a. k. srivastava and y. wu, “event analysis in transmission systems using spatial temporal graph encoder decoder (stged),” in ieee transactions on power systems, doi: 10.1109/tpwrs.2022.3226209.
5. r. ma, s. basumallik and s. eftekharnejad, “controlled islanding resilience with high penetration of renewable energy resources,” in ieee transactions on sustainable energy, 2022.
6. c. lyu, s. eftekharnejad, s. basumallik and c. xu, “dynamic feature selection for solar irradiance forecasting based on deep reinforcement learning,” in ieee transactions on industry applications, 2022.
7. basumallik, sagnik, sara eftekharnejad, and makan fardad. 2022. “controlled islanding under complete and partial false data injection attack uncertainties against phasor measurement units” energies 15, no. 15: 5723.
8. ma, r., basumallik, s., eftekharnejad, s. and kong, f., 2021. a data-driven model predictive control for alleviating thermal overloads in the presence of possible false data. ieee transactions on industry applications, 57(2), pp.1872-1881.
9. basumallik, s., eftekharnejad, s. and johnson, b.k., 2020. the impact of false data injection attacks against remedial action schemes. international journal of electrical power & energy systems, 123, p.106225.
10. ma, r., basumallik, s. and eftekharnejad, s., 2020. a pmu-based data-driven approach for classifying power system events considering cyberattacks. ieee systems journal, 14(3), pp.3558-3569.
11. basumallik, s., ma, r. and eftekharnejad, s., 2019. packet-data anomaly detection in pmu-based state estimator using convolutional neural network. international journal of electrical power & energy systems, 107, pp.690-702.

conferences

1. basumallik sagnik, liu, ying, katramatos, dimitrios, yoo, shinjae, real-time distribution state estimation with massive μpmu streaming data, the 11th conference on innovative smart grid technologies (isgt 2020), february, washington dc.
2. basumallik sagnik, eftekharnejad, sara, dynamic islanding in power systems based on real-time operating conditions, 2019 north american power symposium (naps), wichita, kansas, october 2019.
3. basumallik sagnik, eftekharnejad, sara, davis, nathan and johnson, brian k, impact of false data injection attacks on pmu-based state estimation, in power symposium (naps), 2017 north american, ieee, 2017.
4. basumallik sagnik, eftekharnejad, sara, davis, nathan, nuthalapati, nagarjuna, and johnson, brian k, cyber security considerations on pmu-based state estimation, in proceedings of the fifth cybersecurity symposium, p.14.acm,2018.
5. basumallik sagnik, p. purkait, nimesh mohandas, and s. v. kulkarni, analysis of variations in measured recovery voltage peaks due to presence of moisture in insulation of power transformers, in condition assessment techniques in electrical systems (catcon), 2013 ieee 1st international conference on, ieee, 2013.
6. cheng lyu, basumallik sagnik, sara eftekharnejad, chongfang xu, a data-driven solar irradiance forecasting model with minimum data, 2021 ieee texas power and energy conference.
7. ma, rui, basumallik sagnik, eftekharnejad, sara, recovery-based model predictive control for cascade mitigation under cyber-physical attacks, texas power and energy conference, 2020
8. j. buckelew, s. basumallik, v. sivaramakrishnan, a. mukhopadhyay, a. k. srivastava and a. dubey, “synchrophasor data event detection using unsupervised wavelet convolutional autoencoders,” 2023 ieee international conference on smart computing (smartcomp), nashville, tn, usa, 2023, pp. 326-331, doi: 10.1109/smartcomp58114.2023.00080.

bulletin

1. basumallik, sagnik, anurag srivastava, arman ahmed, and yinghui wu. “synchrophasor data anomaly detection and classification considering data drift and contextual information.”, smart grid bulletin, january 2023

invited talks

1. islanding during data injection attacks, wecc jsis meeting, 2022