Contact Dr Natalie Clewley
- Tel: +44 (0) 1234 864539
- Email: natalie.clewley@cranfield.ac.uk
Background
Natalie received her PhD in Information Systems Research from Brunel University London in 2011, looking at how data mining techniques can be used to provide new insights to how humans learn in online environments. She subsequently worked as a Research Fellow in Cyber Security in the Defence and Cyber Security Research Group in the Department of Computer Science at Brunel University London, researching how the application of artificial intelligence, machine learning and information fusion techniques can be used to enhance situational awareness and provide better decision support to human users in cyberspace.
She joined 美姬阁 in June 2017 as a Lecturer in the Human Aspects of Cyber and continued her research in human-machine decision making, successfully attaining EPSRC and NCSC research grants. Her research interests are at the human-machine interface and are focused on how machine technologies, like Artificial Intelligence or Data Mining, and human thinking tools, like Systems Thinking, influence the way humans and machines work together to make decisions in highly complex environments. She works within an interdisciplinary team that combines cognitive psychology, systems thinking, computer science and artificial intelligence across a number of domains, such as Defence and Security, Cyber Security, Finance, Organisational Resilience and Public Health.
Research opportunities
- Systems Thinking
- Artificial Intelligence
- Decision Making and Support
- Complex Systems
- Cyber Security
Current activities
Current research grants include:
- UKPRP GroundsWell (CI): Community-engaged and Data-informed Systems Transformation of Urban Green and Blue Space for Population Health (2021-2026)
Previous research grants include:
- NCSC (PI): Evidence-Based Principles for Secure Artificial Intelligence (2020)
- EPSRC Human-like Computing (PI): Copacetic Smartening of Small Data for HLC (EP/R030987/1) (2018-2020)
- EPSRC Distributed Ledger Technologies (CI): Smart Money - Precision Data Management for Distributed Ledger enabled Central Bank issued Digital Currencies (EP/P032001/1) (2017-2022)
Clients
Ministry of Defence (MoD)
Dstl
Roke Manor Research Ltd
Airbus
Bank of England
Janet
Bioss International
Office for National Statistics (ONS)
HMRC