| Deep ensemble learning-based approach to real-time power system state estimation N Bhusal, RM Shukla, M Gautam, M Benidris, S Sengupta International Journal of Electrical Power & Energy Systems 129, 106806, 2021 | 37 | 2021 |
| Anomaly detection using supervised learning and multiple statistical methods W Jia, RM Shukla, S Sengupta 2019 18th IEEE international conference on machine learning and applications …, 2019 | 37 | 2019 |
| Scalable and robust outlier detector using hierarchical clustering and long short-term memory (lstm) neural network for the internet of things RM Shukla, S Sengupta Internet of Things 9, 100167, 2020 | 31 | 2020 |
| Software-defined network and cloud-edge collaboration for smart and connected vehicles RM Shukla, S Sengupta, M Chatterjee Proceedings of the Workshop Program of the 19th International Conference on …, 2018 | 27 | 2018 |
| An efficient computation offloading architecture for the Internet of Things (IoT) devices RM Shukla, A Munir 2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC …, 2017 | 24 | 2017 |
| Smart plug-in electric vehicle charging to reduce electric load variation at a parking place RM Shukla, S Sengupta, AN Patra 2018 IEEE 8th Annual Computing and Communication Workshop and Conference …, 2018 | 19 | 2018 |
| Coordinated data falsification attack detection in the domain of distributed generation using deep learning N Bhusal, M Gautam, RM Shukla, M Benidris, S Sengupta International Journal of Electrical Power & Energy Systems 134, 107345, 2022 | 17 | 2022 |
| Cop: An integrated communication, optimization, and prediction unit for smart plug-in electric vehicle charging RM Shukla, S Sengupta Internet of Things 9, 100148, 2020 | 16 | 2020 |
| A computation offloading scheme leveraging parameter tuning for real-time IoT devices RM Shukla, A Munir 2016 IEEE International Symposium on Nanoelectronic and Information Systems …, 2016 | 15 | 2016 |
| A novel software-defined network based approach for charging station allocation to plugged-in electric vehicles RM Shukla, S Sengupta 2017 IEEE 16th International Symposium on Network Computing and Applications …, 2017 | 14 | 2017 |
| A neural network-based appliance scheduling methodology for smart homes and buildings with multiple power sources RM Shukla, P Kansakar, A Munir 2016 IEEE International Symposium on Nanoelectronic and Information Systems …, 2016 | 13 | 2016 |
| Software-defined network based resource allocation in distributed servers for unmanned aerial vehicles RM Shukla, S Sengupta, AN Patra 2018 IEEE 8th Annual Computing and Communication Workshop and Conference …, 2018 | 12 | 2018 |
| Unr-idd: Intrusion detection dataset using network port statistics T Das, OA Hamdan, RM Shukla, S Sengupta, E Arslan 2023 IEEE 20th Consumer Communications & Networking Conference (CCNC), 497-500, 2023 | 10 | 2023 |
| Analysis and detection of outliers due to data falsification attacks in vehicular traffic prediction application RM Shukla, S Sengupta 2018 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile …, 2018 | 9 | 2018 |
| The devil is in the details: Confident & explainable anomaly detector for software-defined networks T Das, RM Shukla, S Sengupta 2021 IEEE 20th International Symposium on Network Computing and Applications …, 2021 | 8 | 2021 |
| Give and take: Federated transfer learning for industrial iot network intrusion detection LT Rajesh, T Das, RM Shukla, S Sengupta arXiv preprint arXiv:2310.07354, 2023 | 4 | 2023 |
| AgileML: A machine learning project development pipeline incorporating active consumer engagement RM Shukla, J Cartlidge 2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering …, 2021 | 4 | 2021 |
| Analyzing the Impact of Adversarial Examples on Explainable Machine Learning P Devabhakthini, S Parida, RM Shukla, SC Nayak arXiv preprint arXiv:2307.08327, 2023 | 3 | 2023 |
| Transparency and privacy: the role of explainable ai and federated learning in financial fraud detection T Awosika, RM Shukla, B Pranggono IEEE Access, 2024 | 2 | 2024 |
| A novel machine learning pipeline to detect malicious anomalies for the Internet of Things RM Shukla, S Sengupta Internet of Things 20, 100603, 2022 | 2 | 2022 |
