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Umeå universitet
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Personalbild Monowar Bhuyan

Monowar Bhuyan

Assistant Professor (biträdande universitetslektor), WASP, one of the research group leaders in Autonomous Distributed Systems Lab, https://cloudresearch.org/.

Kontakt

E-post
monowar.bhuyan@umu.se
Telefon
090-786 67 05

Verksam vid

Anknytning
Biträdande universitetslektor vid Institutionen för datavetenskap
Plats
Naturvetarhuset, Umeå universitet, NAT.B2.208 Umeå universitet, 901 87 Umeå

Monowar received doctoral degree in Computer Science and Engineering from Tezpur University, India in 2014. He was a Visiting Researcher in the Laboratory for Cyber Resilience at NAIST, Japan funded by NICT, Japan, a Researcher, Department of Computing Science, Umeå University, Sweden, an Associate Professor (Senior Lecturer) and an Assistant Professor (Lecturer) in the Department of Computer Science and Engineering at Assam Kaziranga University, Jorhat, India, and a Researcher in the Department of Computer Science and Engineering, Tezpur University, India from January 2009 to December 2019. He primarily works in machine learning, anomaly detection, security and privacy, trustworthy AI, and distributed systems.

Read more on the personal page.

Identification and Classification of Cyberbullying Posts: A Recurrent Neural Network Approach Using Under-Sampling and Class Weighting
ICONIP 2020: Neural Information Processing: 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18–22, 2020, Proceedings, Part V, Thailand: Springer Berlin/Heidelberg 2020 : 113-120
Agarwal, Ayush; Chivukula, Aneesh Sreevallabh; Bhuyan, Monowar H.; et al.
End-to-End Analysis for Text Detection and Recognition in Natural Scene Images
2020 International Joint Conference on Neural Networks (IJCNN): Proceedings
Alnefaie, Ahlam; Gupta, Deepak; Bhuyan, Monowar H.; et al.
Hierarchical Load Balancing and Clustering Technique for Home Edge Computing
IEEE Access, IEEE 2020, Vol. 8 : 127593-127607
Babou, Cheikh Saliou Mbacke; Fall, Doudou; Kashihara, Shigeru; et al.
Multi-Diseases Classification From Chest-X-Ray: A Federated Deep Learning Approach
AI 2020: Advances in Artificial Intelligence: 33rd Australasian Joint Conference, AI 2020, Canberra, ACT, Australia, November 29–30, 2020, Proceedings, Springer 2020 : 3-15
Banerjee, Sourasekhar; Misra, Rajiv; Prasad, Mukesh; et al.
Boosted Ensemble Learning for Anomaly Detection in 5G RAN
Artificial Intelligence Applications and Innovations, AIAI 2020, Springer 2020 : 15-30
Sundqvist, Tobias; Bhuyan, Monowar H.; Forsman, Johan; et al.
SDN-Enabled IoT Anomaly Detection Using Ensemble Learning
Artificial Intelligence Applications and Innovations: 16th IFIP WG 12.5 International Conference, AIAI 2020, Neos Marmaras, Greece, June 5–7, 2020, Proceedings, Part II, Springer 2020 : 268-280
Tsogbaatar, Enkhtur; Bhuyan, Monowar H.; Taenaka, Yuzo; et al.
Information-theoretic Ensemble Learning for DDoS Detection with Adaptive Boosting
2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), IEEE Computer Society 2019 : 995-1002
Bhuyan, Monowar H.; Ma, Maode; Kadobayashi, Youki; et al.
Adversarial Impact on Anomaly Detectionin Cloud Datacenters
2019 IEEE 24th Pacific Rim International Symposium on Dependable Computing (PRDC), IEEE 2019 : 188-197
Deka, Pratyush Kr.; Bhuyan, Monowar H.; Kadobayashi, Youki; et al.
TVis: A Light-weight Traffic Visualization System for DDoS Detection
The Proceedings: 2019 14th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)
Kalwar, Abhishek; Bhuyan, Monowar H.; Bhattacharyya, Dhruba K.; et al.
SURE-H: A Secure IoT Enabled Smart Home System
2019 IEEE 5th World Forum on Internet of Things (WF-IoT), IEEE 2019 : 59-63
Sarmah, Roshmi; Bhuyan, Manasjyoti; Bhuyan, Monowar H.
Multi-Scale Low-Rate DDoS Attack Detection Using the Generalized Total Variation Metric
17th IEEE International Conference on Machine Learning and Applications, IEEE 2018 : 1040-1047
Bhuyan, Monowar H.; Elmroth, Erik
Visa publikationer i DiVA

Forskargrupper

Forskningsledare
Autonomous Distributed Systems Lab

Forskningsprojekt

1 januari 2020 till 31 december 2023
Anomaly Detection and Countermeasures for Edgeclouds
1 januari 2018 till 31 december 2022
Machine Learning-based Observability and Diagnostics in Future Networks and Mobile Edge Clouds