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Intelligent Systems

Dr Jun Chen


Reader in Intelligent Systems Engineering

Room Number: Engineering 310, Mile End


Dr Chen is a Reader in Intelligent Systems Engineering at QMUL. He has published more than 70 scientific papers in areas of multi-objective optimisation, interpretable fuzzy systems, data-driven modelling, and intelligent transportation systems. Dr Chen was among the first researchers to investigate the trade-off between taxi time and fuel consumption in airport ground movements (EP/H004424/2), and proposed the Active Routing (AR) concept. AR forms the cornerstone of a major ongoing EPSRC funded project (EP/N029496/1, EP/N029356/1 and EP/N029577/1, in total in excess of £1M) for which Dr Chen is the lead PI (with BAEs, AirFrance-KLM, Rolls Royce, Manchester and Zurich Airports, and Simio plc.). He has also been the PI on EPSRC-QMUL IAA projects, four industrial projects with Anglian Water, and was the CI on three Innovate UK projects (with IMS and Tesco plc, and Siemens). He serves as a full member of the EPSRC Peer Review College. He is also a Turing Fellow at Alan Turing Institute.

Dr Chen is working closely with industries and regulatory bodies to produce guidance on safe, secure and successful adoption of AI technologies in Aeronautical systems, in particular for ground-based systems. Under European regulations (e.g. EU REG 373/2017), all software used in the delivery of Air Navigation Services (ANS) is required to be developed according to established software assurance processes such as from ED-109 or ED-153. This involves assigning a software assurance level (SWAL) based on the criticality of the software in the chain of the ANS delivery and impacts on that service should failures in the software occur. Each assurance level imposes an increasing burden regarding process, procedure and documentation requirements that must be followed during the software development lifecycle. In addition to the EU regulations, there are ISO standards (such as ISO/IEC 12207) which provide good practice software lifecycles regardless if the software is for ANS or not.

Following the above best practice and taking a systems approach, the ground-based decision support system developed within Dr Chen's group aligned to these development methodologies as early in the development as possible to ensure smooth transition to operational deployment in future.


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