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Personal profile

Area of academic expertise - outline

Professor Keshav Dahal a chair in Intelligent Systems and the Leader of Artificial Intelligence, Visual Communication and Networks (AVCN) research centre. He has also been appointed as a visiting professor at Nanjing University of Information Science and Technology China and Chiang Mai University Thailand. He has an extensive experience in terms of research supervision and management of funded projects. He has been principal/co-investigator of 15 EU/UK/Industry funded projects worth over £4 million in last ten years. He has successfully supervised the completions of 4 Post-Doctoral and 13 PhD studies. Prof. Dahal has published over 110 peer-reviewed journals/conferences papers and 4 edited books, and has sat on organising/programme committees of over 50 reputed international conferences; including as the General Chair and the Programme Chair. His research expertise includes:

  • Artificial Intelligence (AI) applied to Data Mining/Big Data, Scheduling and Logistics Problems
  • Smart Decision Support Techniques and Intelligent Systems
  • Trust/Security Modelling in Networks, Cloud and Distributed Systems
  • Data Security and Privacy

Current research activities

Professor Dahal’s current research activities lie in the areas of applications of computational intelligent/machine learning approaches for modelling, analysis and solving challenging real-world problems.  The application domains of his current work are in the Disaster Management, Remote Healthcare Systems, Communication Networks and Electrical Power Systems. Currently, he is coordinating a consortium of 20 partners for EU Erasmus Mundus Action 2 ‘SmartLink’ project (2014-2018), which focuses on the applications of smart technologies to a wide range of application domains. He is the local coordinator of EU ‘gLINK’ project (2014-2018) focusing on the applications of smart technologies. He is also a co-investigator of the EU H2020-ICT-2014-2 “SELFNET – Framework for Self-organized network management in virtualized and software defended networks” project (2015-2018). Currently, 6 PhDs and 2 Post-Doctoral fellows are working under his supervision. 

Desired research direction

Professor Dahal’s research direction is to develop hybrid frameworks to bring together inter-disciplinary Machine learning, Decision making and Data mining algorithms for solving complex problems in wider application domains. This includes Big Data Analytics for processing and learning from overwhelming amount of data generated by web, IoTs and sensors for useful information for problems, such as service delivery, cyber physical systems security, personalised health treatment, fraud detection, national intelligence etc.  

Target collaborative organisations

Professor Dahal enjoys working across disciplines and with industrial collaborators, to solve important real-world problems. He is open to collaboration with organisations that are interested in Logistics/scheduling/event management, Big data analytics, Decision support and Data modelling. They include:

  • Government and private sector companies
  • UK and International HE institutions/research centres
  • Consortium for research and innovation funding applications

Fingerprint Dive into the research topics where Keshav Dahal is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2008 2020

94 Downloads (Pure)
Open Access
Computational fluid dynamics
Computer aided engineering
88 Downloads (Pure)

A hybrid intelligence-based cognitive engine

Olaleye, M., Dahal, K. & Pervez, Z., 29 Jul 2019, Proceedings of the 9th International Conference On Cloud Computing, Data Science and Engineering Confluence 2019. IEEE, p. 258-262 5 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access
Cognitive radio
Radio systems
Artificial intelligence
15 Downloads (Pure)

A multi-node energy prediction approach combined with optimum prediction interval for RF powered WSNs

Koirala, B., Dahal, K., Keir, P. & Chen, W., 16 Dec 2019, In : SENSORS. 19, 24, 14 p., 5551.

Research output: Contribution to journalArticle

Open Access
Wireless sensor networks

An efficient feature selection based Bayesian and rough set approach for intrusion detection

Prasad, M., Tripathi, S. & Dahal, K., 2 Dec 2019, In : Applied Soft Computing. 87, 14 p., 105980.

Research output: Contribution to journalArticle

Rough set theory
Intrusion detection
Feature extraction
Intelligent systems
1 Citation (Scopus)
121 Downloads (Pure)

DNS-IdM: a blockchain identity management system to secure personal data sharing in a network

Kassem, J. A., Sayeed, S., Marco Gisbert, H., Pervez, Z. & Dahal, K., 24 Jul 2019, In : Applied Sciences. 9, 15, 19 p., 2953.

Research output: Contribution to journalSpecial issue

Open Access
Data privacy
management systems

Activities 2014 2017

  • 2 Invited talk
  • 1 Editorial activity


Learning systems
Resource allocation
Electric power utilization
Routing protocols
Traffic congestion