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Arshad Jhumka

Arshad Jhumka is an Honorary Professor at the University of Warwick and a Professor of Distributed Systems at the University of Leeds, UK. His main research interests currently lie in dependability design for large scale systems such as Internet of Things (IoT) and supercomputers. He has published extensively in these areas, with over 110 papers. He is also interested in the application of novel AI techniques (such as NLP) to dependability design.

Job Title
Associate Professor Reader
Computer Science
024 7657 3780
Web Link
Research Interests

I pursue research in all aspects of dependable systems. A system is dependable if trust can be justifiably placed in its correct operation even in exceptional circumstances. Exceptional circumstances can be due to hardware faults (e.g., bit corruptions) or to software faults (e.g., bugs, configuration errors). These can lead to benign fault at a node level (e.g., crash fault) or malicious fault (e.g., Byzantine behaviours). Either way, systems must be designed to be fault-tolerant. I am interested in the design of such systems, from their specification to their verification and validation. Specifically, my group has interests in the following areas: 1. Design of (variants) of fault tolerance (formal methods). 2. Dependability in networked embedded systems, e.g., Wireless sensor networks, Internet of Things, cyber-physical systems. 3. Failure log analysis of High Performance Computing systems (e.g., clusters). 4. Computer security/Digital forensics. 5. Distributed systems including cloud computing, mobile Computing, edge/fog computing. An increasing interest in our research group is the use of artificial intelligence techniques to solve dependability problems.


I am an Associate Professor in the Department of Computer Science at the University of Warwick. I am a member of the Artificial Intelligence theme and I lead the Reliability and Fault Tolerance group.

Title Funder Award start Award end
Evaluating Trustworthiness of Edge-Based Multi-Tenanted IoT Devices EPSRC 02 Mar 2020 30 Jun 2022
Bayesian predictive models of violent extremist threat: the intelligent combination of expert judgements and observational data Turing innovations Ltd 01 Oct 2018 31 Mar 2019
Testbed Development for Secure Cyber-Physical Systems and Internet of Things Research and Teaching Secretary of State for Foreign and Commonwealth Affairs 30 Nov 2017 29 May 2018