School of Mechanical, Electrical and Manufacturing Engineering


Dr David Mulvaney BSc (Hons), PhD, MIEEE

Photo of Dr David Mulvaney

Senior Lecturer in Embedded Microelectronic Systems

David’s areas of research include machine learning for real-time applications, novel electronic design automation tools, robot navigation, elevator scheduling systems and embedded software development.

David is also a Founder and Director of Axilica, a spin-out company specializing in novel EDA tool flows. He is the Principal Investigator of a UKIERI project on remote health monitoring and diagnosis and on an ARTEMIS-JU project to improve design flows for embedded systems.

Before joining Loughborough, David worked as a Senior Software Engineer at Cambridge Consultants where he developed a number of real-time systems for military applications. He has carried out consultancy work for BP, Otis, Cadbury-Schweppes and GE Lighting.


1980: First Class Degree with Honours in Electrical and Electronic Engineering, University of Leeds.

1983: PhD in Mechanical Engineering, University of Leeds.

Previous work experience

1983-1987 Research Assistant then Lecturer in Robotics, Department of Electronic Engineering, University of Hull.

1987-1989 Senior Software Engineer in the Artificial Intelligence Group, Cambridge Consultants Ltd, Cambridge.

1989 - 1990 Freelance Software Engineer.

1990 - 1991 Consultant in the Advanced Technology Group, Brender Management Services Ltd, Mayfair, London.

Research Projects

David is the Principal Investigator of a British Council UKIERI project on remote health monitoring and diagnosis, in collaboration with IIT Delhi, Kingston University, All India Institute of Medical Sciences and Aligarh University. The aim of the project is to exploit mobile communications to improve health care provision for monitoring heart disease and diabetes, which affect millions of people globally. The knowledge transfer effort is being augmented by the development of pre-production systems in both India and the UK to be used in a planned series of clinical trails.

He is also the Principal Investigator on an ARTEMIS-JU European project in collaboration with over 20 European partners including ABB, Artisan Software, Delft University of Technology, Honeywell, SELEX Galileo, Siemens and Thales, with the aim of enabling design engineers to explore architectural design space at a high level of abstraction, choose a cost effective design, and from the abstract models produce semi-automatically the hardware and software implementations in a cost effective balance. Loughborough University is working on meta-model extensions to incorporate co-design solutions and collaborating in the development of an instance of the hardware/software co-design flow.

David is a Co-Investigator on the FP7 ENOSYS project in collaboration with Softeam, Axilica, Intracom, Thales and the University of Peloponnese, to specify and develop a tool supported design flow for designing and implementing embedded systems by seamless integration of high-level system specifications, software code generation, hardware synthesis and design space exploration. Loughborough University’s contribution relates the integration of a extensible processor core into the Axilica flow and the design space exploration of alternative embedded solutions.

Research Students

One of his research students is carrying out PhD work in the area of digital watermarking, and important technology in the successful deployment of the UKIERI project discussed above.

He also has a research student working on the implementation of the FastSLAM robot localization and mapping algorithm on an extensible processor core and dedicated hardware. This will enable its implementation on much smaller and lighter platforms than is possible at present.

Two of David's research students are working in the area of speech recognition. One project involves the use of visual information to improve the performance of speech recognition systems in noisy environments. The second has identified and implemented those areas of the SPHINX speech recognition algorithm that are best suited to acceleration by implementation in hardware. This work will allow speech recognition systems to be made considerably smaller and consume less power and so have the potential to be incorporated in mobile systems.

One research students is investigating the implementation of asynchronous cellular automata and their ability to adjust connection strengths and to reconfigure their architecture in response to sequences of input patterns.

Other research activities

Member of the Institute of Electronic and Electrical Engineers.

Editorial Committee Member of Engineering Letters, since 2005.

International Programme Committee Member for the Artificial Intelligence and Soft Computing Conference, since 1999.

David teaches the following courses

  • Computer Architecture (year 2)
  • Software Engineering (year 2)
  • Microprocessor Architecture (year 3)
  • Embedded System verification (year 4)
  • C programming (MSc)