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Prof Jon Timmis
Department of Computer Science and Department of Electronics
University of York
Heslington, York. YO10 5DD
Tel +44 (0) 1904 322318/325361
Email: jon (dot) timmis (at) york (dot) ac (dot) uk |
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I am Professor of Natural Computation and hold a joint appointment between the Department of Computer Science and the Department of Electronics . I am a member of the Non Standard Computation group, the Intelligent Systems group and the York Centre for Complex Systems Analysis (YCCSA).
Research
My work cuts across many areas, but most of my work revolves around immunology, either developing computational models of immune function (computational immunology), or fault-tolerance achieved via bio-inspired engineering with a focus on the immune system (immuno-engineering). In terms of applications, I focus mainly on swarm robotic systems as a platform for testing our ideas realting to fault tolerence and anomaly detection. My wider interests are in modelling and simulation of complex systems.
I currently hold a Royal Society Wolfson Research Merit Award where my work is focussed on computational immunology and self-healing swarm robotic systems.
I work on a variety of robotic platforms, we made a video for some fun, of our flying robots (make sure the volume is turned up).
I am Visiting Professor at the Universiti Kebangsaan Malaysia.
A few years ago, Nature did a piece on AIS, take a read
If you want to know more about AIS, I have written a few papers that you might find interesting all with pre-final version PDFs provided for you (you can find the full reference for citation purposes on my publication page):
I have recently helped to guest edit a number of special issues on AIS:
Jobs and Studentships
Applications are invited for a 4-year BBSRC/CASE PhD studentship in Computational Biology of the Intestinal Tract at the University of York in partnership with GlaxoSmithKline (GSK). The studentship provides a unique opportunity to gain high-quality research training in collaboration with one of the world's leading research-based pharmaceutical companies. Please see the advert for more information and on how to apply.
Conferences in 2011
Research Activities
Current Research Council Projects
Current Industrial Funding
I hold two current research grants from a major manufacture of electro-mechanical devices where we develop ideas for dynamic data fusion.
I hold a grant from DSTL on chemical agent detection deployed on robotic platforms.
I hold a grant from Syngenta to develop a decision support tool for farmers to optimise bird life diversity on their land.
Activities
Books
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In Silico Immunology
Darren R. Flower, Jon Timmis, editors, in silico Immunology
Overview: Immunology is an all important science, addressing as it does, the most pressing medical needs of our time: infectious disease and transplantation medicine. It has given us vaccines on the one hand and therapeutic antibodies on the other. After a century of emperical research, it is now poised to finally reinvent itself as a quantitative, genome-based science.
Theoretical immunology is the application of mathematical modeling to diverse aspects of immunology ranging from T cell selection in the Thymus to the epidemiology of vaccination. Immunoinformatics, the application of computational informatics to the study of immunological macromolecules, address important questions in immunobiology and vaccinology. Artificial Immune Systems (AIS) is an area of computer science which uses ideas and concepts from immunology to guide and inspire the development of new algorithms and architectures.
These three different disciplines-theoretical immunology, immunoinformatics and AIS are now poised to engineer a paradigm shift from hypothesis- to data-driven research, with new understanding emerging from the analysis of complex datasets. in silico immunology will summarize these emergent disciplines and, while focusing on cutting edge developments, will address the issue of synergy as it shows how these three are set to transform immunological science and the future of health care.
See it on-line using the doi link 10.1007/978-0-387-39241-7
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Overview: Over the past few decades there has been a growing interest in the use of biology as a source of inspiration for solving computational problems. This area of research is often referred to as Biologically Inspired Computing. The motivation of this field is primarily to extract useful metaphors from natural biological systems, in order to create effective computational solutions to complex problems in a wide range of domain areas. The more notable developments have been the neural networks inspired by the working of the brain, and the evolutionary algorithms inspired by neo-Darwinian theory of evolution.
More recently however, there has been a growing interest in the use of the biological immune system as a source of inspiration to the development of these computational systems. The immune system contains many useful information-processing abilities, including pattern recognition, learning, memory and inherent distributed parallel processing. For these and other reasons, the immune system has received a significant amount of interest to use as a metaphor within computing. This emerging field of research is known as Artificial Immune Systems (AIS).
Essentially, AIS are the use of immune system components and processes as inspiration to construct computational systems. AIS is very much an emerging area of biologically inspired computation and has received a significant amount of interest from researchers and industrial sponsors in recent years. Applications of AIS include such areas as machine learning, fault diagnosis, computer security, scheduling, virus detection, and optimisation. The field of AIS is showing great promise of being a powerful computing paradigm and therefore the writing of this book is very timely.
The book will present a general introduction to the field of immunology, stressing the key areas that are currently used within the field of AIS. A framework for engineering AIS is then introduced to the reader, followed by an up to-date review of the state of the art in AIS, in then light of that framework. It is hoped that through these initial chapters the reader will become aware of the powerful metaphor of the immune system and be left with a concrete set of ideas of how to create their own AIS. The book then goes onto describing the natural immune system in context with other biological systems and explores interaction between those systems. This will allow the reader to develop an understanding and appreciation for the richness of biology and its possible inspiration. This is then followed by a discussion of the field of AIS in relation to other computational intelligence paradigms. It is hoped that this chapter will allow the reader to become familiar with other techniques and understand the relative strengths and weaknesses of each and where the use of each (including AIS) would be appropriate.
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Current Research
My work cuts across many areas, but most of my work revolves around immunology, either developing computational models of immune function (computational immunology), or fault-tolerance achieved via bio-inspired engineering with a focus on the immune system (immuno-engineering) In terms of applications, I focus mainly on swarm robotic systems as a platform for testing our ideas. My wider interests are in modelling and simulation of complex systems.
Below is a current list of people, that in one way or another, work with me.
Computational Immunology
Complex Systems
Bio-Inspired Engineering
PhD students writing up
Submitted
Old Projects
Past Students/RA's
Below is a list of people, who I am pleased to say survived working with me!
Research Associates
Graduate Students
Completed (some awaiting final CRC of thesis):
- Dr. Omer Qadir. Protien Processor Associate Memory. (2011)
- Dr Mark Read. Statistical and Modelling Techniques to Build Confidence in the Investigation of Immunology through Agent-Based Simulation. (2011)
- Dr. Richard Greaves. Computational Modelling of Treg Networks in Experimental Autoimmune Encephalomyelitis. (2011) (MSc by Research)
- Dr Nick Owens. From Biology to Algorithms. (2010)
- Dr Luca Albergante (Milan). A Petri Net Model of Liver Response to Visceral Leishmaniasis: self-regulation and complex interplay in the vertebrate immune system. (2010)
- Dr Adam Knowles Immunologically Inspired Data Fusion for Anomaly Detection in Electromechanical Systems PhD. 2010 Thesis commercially sensitve and is unavailable
- Dr Yang Liu A Neuro-Immune Inspired Computational Framework and its Applications to a Mchine Visual Tracking System PhD. 2010. PDF of thesis
- Dr Ed Clark A Framework for modelling stochastic optimisation algorithms with Markov chains. PhD. 2009. PDF of thesis
- Dr Paul AndrewsAn Investigation of a Methodology for the Development of Artificial Immune Systems: A Case-Study in Immune Receptor Degeneracy PhD. 2009. PDF of thesis
- Dr. Peter May. An Artficial Immune System Approach to Mutation Testing Test Data Generation PhD. 2006.
- Dr. Andy Secker. Artificial Immune Systems for Web Content Mining: Focusing on the Discovery of Interesting Information PhD. 2006. Thesis .
- Dr. Modupe Ayara. An Immune Inspired Approach For Adaptable Error Detection in Embedded Systems PhD. 2005.
- Dr. Andrew Watkins. Exploiting Immunological Metaphors in the Development of Serial, Parallel and Distributed Learning Algorithms PhD. 2005.PDF of thesis
- Dr. Tom Knight. MARIA: A Multilayered Unsupervised Machine Learning Algorithm Based on the Vertebrate Immune System PhD. 2005.download PDF of thesis
- Dr Giuseppe Nicosia (Catania, Italy). Immune Algorithms for Optimisation and Protein Structure Prediction, 2004.
- Anton Flugge. Computational Modelling of Granuloma Formation in the Liver MSc. 2008
- Will Normand. Analysis of Swarm Robotic Behaviours MSc. 2007.
- Liang Zhang. Dendritic Cells and Computation MSc, 2007.
- Johnny Kelsey. An Immune Inspired Algorithm for Function Optimisation . MSc. 2004.
- Jeong Sik Jang. An Empiricial Investigation into an Artificial Immune System for Email Classification AISEC MSc. 2004.
- Nyrki Rantonen. An Artificial Immune System for Document Classification . MSc. 2004.
- Alex Kilgour. Developing a Practicle Artificial Immune System for Email Classification. MSc. 2004.
- Camilla Edmonds. Artificial Immune Networks for Function Optimisation MSc. 2003.
Other Collaborations
I was a Visiting Professor at the Helsinki University of Technology, Finland, in the Power Electronics Laboratory. I was also a Visiting Professor at the University of Technology, Malaysia.
I work with Vipin Kumar at TPIMS, Paul Kaye and Mark Coles of the CII here at York and Prof Eva Qwarnstrom at Sheffield on various aspects of immune system modelling.
Research Opportunities
I have many possibilities for research topics centred around the area of Artificial Immune Systems and homeostatic systems. Given my joint appointment, some topics for PhD are more suitable for Computer Science and others for Electronics candidates:
- The general area of Artificial Immune Systems: applications and theory;
- Integration of natural and artificial immune, neural and endocrine systems;
- Immunological modelling;
- Immune inspired fault tolerance;
- Long-term autonomy in robotic systems;
- Pervasive adaptive systems
- Other natural computation areas such as particle swarms, artificial life and evolutionary systems.
- If you are not sure if you are ready for a PhD quite yet, think about a taught MSc in Natural Computation. See the website for more information.
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Publications
For my full list of published papers (most with PDF's) see here.
Papers Recently Submitted
Journal Papers
Conference Papers
Papers in Preperation
Journal Papers
Book Chapters
Conference Papers
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Teaching
In Computer Science I currently teach on the following courses:
In Electronics
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Admin
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Misc.