Updates on the campus response to coronavirus (COVID-19)
Photo file: 
photograph of Shuva Paul
Full name: 
Shuva Paul
Job title: 
Postdoctoral Fellow
Email address: 

Dr. Shuva Paul received his B.S. degree in electrical and electronics engineering from American International University-Bangladesh, Dhaka, Bangladesh, in 2013, and the M.S. degree from American International University-Bangladesh, Dhaka, Bangladesh, in 2015. He received his Ph.D. degree in electrical engineering and computer science from South Dakota State University, Brookings, South Dakota in 2019. He worked as a Graduate Intern at National Renewable Energy Laboratory (NREL) at Golden, Colorado from May 2019 to May 2020. He also worked as a Postdoctoral Research Associate at Washington State University, Pullman, Washington from June 2020 to January 2021. He is currently working as a Post-Doctoral Fellow at the Georgia Institute of Technology in the School of Electrical and Computer Engineering.

Research interests: 
  • Smart grid cybersecurity
  • Computational intelligence, machine learning (such as reinforcement learning, generative adversarial networks), game theory
  • Events and anomaly detection, vulnerability and resilience assessment, big data analytics
  • Collaborative autonomy
Distinctions: 
  • Guest editor, Journal of Sensors and Actuator Networks (JSAN) special issue on "Recent Trends in Innovation for Industry 4.0 Sensor Networks", 2021
  • Session chair, IEEE EIT, 2019
  • Session chair, IEEE EnergyTech, 2013
  • Conference reviewer, IEEE PES General Meeting, SSCI, IJCNN, PECI, ECCI
  • Journal reviewer, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Smart Grid, Neurocomputing, IEEE Access, IET The Journal of Engineering, IET Cyber-Physical Systems: Theory & Applications

S. Paul, F. Ding, U. Kumar, W. Liu and Z. Ni, "Q-Learning-Based Impact Assessment of Propagating Extreme Weather on Distribution Grids," 2020 IEEE Power & Energy Society General Meeting (PESGM), 2020, pp. 1-5, doi: 10.1109/PESGM41954.2020.9281506.

W. Liu, F. Ding, U. Kumar and S. Paul, "Post-Disturbance Dynamic Distribution System Restoration with DGs and Mobile Resources," 2020 IEEE Power & Energy Society General Meeting (PESGM), 2020, pp. 1-5, doi: 10.1109/PESGM41954.2020.9281387.

S. Paul and F. Ding, "Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-learning," 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2020, pp. 1-5, doi: 10.1109/ISGT45199.2020.9087654.

S. Paul and F. Ding, "Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-learning," 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2020, pp. 1-5, doi: 10.1109/ISGT45199.2020.9087654.

S. Paul, Z. Ni and C. Mu, "A Learning-Based Solution for an Adversarial Repeated Game in Cyber–Physical Power Systems," in IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 11, pp. 4512-4523, Nov. 2020, doi: 10.1109/TNNLS.2019.2955857.

S. Paul and F. Ding, "Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-learning," 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2020, pp. 1-5, doi: 10.1109/ISGT45199.2020.9087654.

Z. Ni and S. Paul, "A Multistage Game in Smart Grid Security: A Reinforcement Learning Solution," in IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 9, pp. 2684-2695, Sept. 2019, doi: 10.1109/TNNLS.2018.2885530.

S. Paul, M. R. Haq, A. Das and Z. Ni, "A Comparative Study of Smart Grid Security Based on Unsupervised Learning and Load Ranking," 2019 IEEE International Conference on Electro Information Technology (EIT), 2019, pp. 310-315, doi: 10.1109/EIT.2019.8834059.

S. Paul and Z. Ni, "Study of Learning of Power Grid Defense Strategy in Adversarial Stage Game," 2019 IEEE International Conference on Electro Information Technology (EIT), 2019, pp. 292-297, doi: 10.1109/EIT.2019.8834202.

S. Paul and Z. Ni, "A Strategic Analysis of Attacker-Defender Repeated Game in Smart Grid Security," 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2019, pp. 1-5, doi: 10.1109/ISGT.2019.8791629.

S. Paul and Z. Ni, "A Study of Linear Programming and Reinforcement Learning for One-Shot Game in Smart Grid Security," 2018 International Joint Conference on Neural Networks (IJCNN), 2018, pp. 1-8, doi: 10.1109/IJCNN.2018.8489202.

Z. Ni, S. Paul, X. Zhong and Q. Wei, "A reinforcement learning approach for sequential decision-making process of attacks in smart grid," 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017, pp. 1-8, doi: 10.1109/SSCI.2017.8285291.

Z. Ni, S. Paul, X. Zhong and Q. Wei, "A reinforcement learning approach for sequential decision-making process of attacks in smart grid," 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017, pp. 1-8, doi: 10.1109/SSCI.2017.8285291.

S. Paul, A. Parajuli, M. R. Barzegaran and A. Rahman, "Cyber physical renewable energy microgrid: A novel approach to make the power system reliable, resilient and secure," 2016 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), 2016, pp. 659-664, doi: 10.1109/ISGT-Asia.2016.7796463.

Last revised June 30, 2021