PhD Studentships
The Department has scope for PhD studies in a number of areas, some of which are discussed below. Funding for studentships is available from time to time. Currently we have the possibility of funding 2 EU based studentships starting in September 2009.
If you are interested in applying, please contact the person named in the particular proposal.
Second Life: Virtual and real world interaction
Multiple user virtual worlds such as Second Life (SL), offer an immersive environment where multiple users can interact through avatars. Users roam and interact with other avatars through behaviour and an instant message style communication. Some avatars elect to use voice too. To roam, avatars can walk, swim, fly, use moving objects such as cars, bikes, and even teleport at will.
An exciting aspect of SL is the ability to program in-world objects through a scripting language (Linden* Scripting Language or LSL) that is rather C-like in nature. The emphasis is on a state machine approach to provide behaviour in response to stimuli. There is a limited ability through HTTP and XML-RPC to communicate with external servers and devices. This affects the coordination between in-world objects and real-world devices.
This proposed PhD programme will investigate how environments such as SL can be extended to provide a more powerful link between in-world and real-world experiences. The goal is to use portable devices to interact with in-world objects to allow users that are not in-world to maintain a presence and activity in-world. The desire is to provide a more natural interaction rather than simply use an inadequate small screen as a conventional window.
* Linden Laboratories are the creators of Second Life.
Rigorous Decision Support
The aim of this PhD research would be to design a generic and rigorous methodology for creating a clinical DSS (Decision Support System). This would be evaluated in the field of chronic heart disease. The focus would be on developing new techniques for designing technical aspects of decision support, and would complementary to existing guidelines, models, methods, formats and tools. There is a substantial evidence showing that clinical DSS has the potential to improve practitioner performance, to reduce medical errors, and to improve patient care. The plan is to concentrate on two key aspects of clinical DSS design that need improvement: abstractness and analysis. See the more detailed description (PDF) of this topic for additional background and work plan.
An Individual Interactions Approach to Systems Biology
At Stirling we already have some success in using process algebra to model disease spread. We are keen to take the techniques developed for modelling epidemiology and apply them in the area of Systems Biology.
Systems Biology has become very popular as an application area for theoretical computer science in recent years. Most process algebra approaches are based on stochastic modelling of kinetic reactions in signal transduction pathways. Our approach will focus on the lifespan of certain cell elements. For example, when EGF (Epidermal Growth Factor) binds to a receptor at the cell surface the receptor is internalised and one of two things happens. Either the receptor is destroyed (reprocessed in some way), or is recycled to the cell surface again, without the EGF attached. In both cases as long as the EGF is attached it keeps signalling. Is is possible to investigate signalling levels by treating the process of EGF reception and subsequent death or recycling of the receptor as infection and death or recovery, i.e. as a disease?
A student in this area would be supported by those on the complementary EPSRC grant System Dynamics from Individual Interactions: A process algebra approach to epidemiology, and also by members of the applied formal methods, and mathematical biology research groups. The application area described above is just one example of many possible projects. The technique can be applied to a wide range of biological and computer systems: immunology, epidemiology, peer-to-peer networking, malware analysis, etc. The particular application can be modified depending on the experience and interests of the successful student.
Projects in Computational Neuroscience
Projects are available in the mathematical modelling and computer simulation of aspects of biological nervous systems. Topics range from studying cellular and subcellular details of single neurons, to the dynamics of information processing in neural microcircuits, to developmental aspects of neurons and the networks they form. Tools of the trade include the NEURON simulation package, serial and parallel simulations (72 node cluster available), MATLAB and standard programming languages such as Java. Specific topics around which projects can be defined include (but are not limited to):
- Signal integration in pyramidal cells
- Roles of inhibitory interneurons in neural microcircuits
- Signal transmission properties of chemical synapses
- Development of the electrical properties of neurons
- Development of neuronal morphology
Search Algorithms for Peer-to-Peer Overlay Networks
Peer-to-Peer (P2P) overlay network commonly does not require any central server component for data storage and lookup. This is in sharp contrast to client-server based architectures. Central servers do not scale well in terms of numbers of clients, render the system vulnerable due to the single point of failure, and are expensive to maintain. Due to these disadvantages of client-server based systems, P2P systems have recently greatly gained in popularity. P2P overlay system work on top of the IP network, typically the Internet. P2P overlays feature wide area routing, efficient search of data items, redundant storage, massive scalability, and fault tolerance.
Within P2P there are two different types of networks: structured and unstructured. In unstructured overlays (Gnutella, Kazaa), there is no fixed structure to the topology of the overlay, whereas in structured networks, a Distributed Hash Table (DHT) is used. Unstructured networks are very flexible and do not exhibit any significant amount of maintenance traffic. However, searches in unstructured overlays typically employ flooding algorithms or random walk algorithms. With flooding algorithms there is a good chance the data is found in the network, but at a cost of high volume of traffic. Random walk approaches may not find data which is not duplicated often in the network. However, unstructured overlays support wildcard searches. Searches in unstructured overlays are often referred to as Blind searches as the approach is not affected by what is actually looked for.
Structured overlay networks (Chord, CAN, D1HT, EpiChord, and Tapestry) use DHTs to structure the nodes and to assign data items to particular nodes. In such systems, each node is assigned a unique node ID. This is typically generated encoding their IP address with a secure hash function, such as SHA1. Likewise, data to be stored is assigned a file ID. Again this is generated applying a hash function on the file name or similar keyword. Each node stores data whose ID falls in a certain section of the overall ID space. Nodes locate content using a protocol, often also referred to as routing algorithm. Structured systems include short path lengths to insert/retrieve data and the guarantee that existing data will be found in the network. Structured searches are not blind as the routing of the search is based on the hash of the search string. However, structured overlays do not support wildcard searches where not the full name of the data item is known. An abbreviated name will result in a different hash which bears no relation to the hash of the data item.
This project will investigate wildcard searches in structured P2P overlay networks.
There is some ongoing research on blind search algorithms in structured overlays. However, current blind-search algorithms employ multiple indexing of data items creating a very large key base. Unlike previous work, the approach proposed here is to employ blind searches in the overlay by means of intelligently broadcasting the search. At the first glance this appears to create an enormous traffic overhead in the overlay as a message will need to be sent to every node. However, some overlays employ intelligent maintenance algorithms to inform nodes of a node joining or leaving the network. One such maintenance algorithm is EDRA* used by D1HT. This project will investigate the viability using such maintenance algorithms for wildcard searches in structured P2P overlays. An important research question will be finding solutions to minimise the message overhead.
Natural Computing / Computational Intelligence
A number of research topics are available, including in the following six interdisciplinary research areas:
Title 1:
Novel Computational Intelligence Methods for Immune System Modeling and
Analysis (in collaboration with the BBSRC Research Network on Immunology
Imaging and Modelling, I2M)
Title 2:
Novel Computational Intelligence Techniques for Real-world Problem Solving
e.g. in the medical, defense or business (such as financial and
telecommunications) industries - depending on the topic, this research
could be in collaboration with the Harvard Medical School, MIT Media Lab,
Boston, USA, and Sitekit Labs Ltd., Scotland.
Title 3:
Multi-modal (audio-visual) processing methods to improve the next generation
of telecommunications services (including intelligent avatars, remote health
monitoring and interactive dialogue systems), and development of new speech
processing (i.e. enhancement, analysis, synthesis and recognition) methods
including for foreign languages (Arabic, Urdu, etc.) - in collaboration with
the European Science Foundation (ESF) funded European Research Network
(COST-2102).
Title 4:
Neurobiologically inspired Cognitive Modeling and Control for Complex
real-world industrial & medical applications (such as, robotic control,
autonomous vehicle control, insulin regulation of blood sugar & diabetes
etc.) - in collaboration with the Department of Computational Neuroscience,
Sheffield University.
Title 5:
Common Sense Computing (including intelligent agents, natural language
processing, statistical machine learning, semantic data mining and multi-modal
HCI methods) for developing Next Generation Intelligent Web Applications
in e.g. e-health. e-health, e-tourism etc. (in likely collaboration with
MIT Media Lab, Harvard Medical School, Boston, USA, and Sitekit Labs Ltd.,
Scotland)
Title 6:
Non-linear Computational Intelligence based Signal Processing algorithms for
challenging real world applications such as high-resolution detection and
localization of multiple (non-stationary moving) targets and broadband signal
separation (in collaboration with the Centre of Excellence in Signal Image
Processing, Strathclyde University)
For further information on any of the above PhD research topics (or to propose any of your own ideas/suggestions), please contact Dr. Hussain or visit his webpage as below.
