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Student projects

Below follows a list of project descriptions for students. Some of the projects are finished, some are in progress, and some are still available to students that want to do a UG4, MSc or a PhD projects.

If you want to do an MSc or PhD with us then you need to go through the application procedures set by the School of Informatics. Make sure you discuss your research proposal first with Malcolm Atkinson or David Robertson. Important to note: you need to apply under Intelligent Systems & their Applications.

List of projects

Create Parallel Data Mining Algorithms for Cloud Computing

Student: 
Tantana Saengngam
Grade: 
first

Principle goal: to take an existing algorithm and to make it parallel in a cloud computing environment following the Map and Reduce approach of Google.

Project status: 
Finished
Degree level: 
MSc
Supervisors @ NeSC: 
Subject areas: 
Algorithm Design
Computer Architecture
Distributed Systems
Machine Learning/Neural Networks/Connectionist Computing
Student project type: 
References: 
[1] C.-T. Chu, S. K. Kim, Y.-A. Lin, Y. Yu, G. R. Bradski, A. Y. Ng, and K. Olukotun. Map-reduce for machine learning on multicore. In B. Schölkopf, J. C. Platt, and T. Hoffman, editors, NIPS, pages 281–288. MIT Press, 2006. [2] http://eucalyptus.cs.ucsb.edu/

Predicting earthquake impact with laptop motion sensors

Student: 
Gary Mcgilvary
Grade: 
first

Principle goal: to make clever use of the sudden motion sensor of Apple notebooks to map the impact of earthquakes in densely populated areas.

Project status: 
Finished
Degree level: 
UG4
Supervisors @ NeSC: 
Other supervisors: 
Rémy Bossu, European-Mediterranean Seismological Centre, France; Fabrice Cotton, Grenoble University, France
Subject areas: 
e-Science
Distributed Systems
Mobile Computation
WWW Tools and Programming
References: 
[1] http://en.wikipedia.org/wiki/Seismic_wave [2] http://en.wikipedia.org/wiki/Sudden_Motion_Sensor [3] http://www.agu.org/pubs/crossref/2008/2008EO250001.shtml [4] http://www.suitable.com/tools/seismac.html [5] http://www.emsc-csem.org/
Student project type: 

Mining Andean-to-Amazon ecosystem data to understand the underlying environmental factors

Student: 
Makrymallis Antonios
Grade: 
second1

Principle goals: to use data mining techniques to understand how variables drive ecosystem functioning and a qualitative study to determine which of a variety of data mining techniques best replicates observed ecosystem processes.

Project status: 
Finished
Degree level: 
MSc
Background: 
Courses on Data Mining and Exploration; Genetic Algorithms and Genetic Programming; Introductory Applied Machine Learning courses are desirable but not critical for this project.
Supervisors @ NeSC: 
Other supervisors: 
Dr Rachel Walcott (School of Geosciences) and Dr Patrick Meir (School of Geosciences)
Subject areas: 
Genetic Algorithms/Evolutionary Computing
Machine Learning/Neural Networks/Connectionist Computing
References: 
[1] Re: the SOM Algorithm: http://www.cis.hut.fi/research/som_lvq_pak.shtml [2] Publication analysing Martian landscape data: http://www.lpi.usra.edu/science/stepinskiWebPage/pdfFiles/compGeo32y2006.pdf [3] The Andean project: http://darwin.winston.wfu.edu/andes/index.php?n=Main.HomePage
Student project type: 

Mining and visualising family tree networks from online genealogy information

Principle goal: to construct a data harvesting system with an associated semantic web-enabled store for genealogical data with a method for querying the data which you test using at least one query.

Project status: 
Finished
Degree level: 
UG4
Background: 
Applied Databases; Data Integration and Exchange; Querying and Storing XML; Knowledge Modelling and Management courses are desirable but not critical for this project.
Supervisors @ NeSC: 
Other supervisors: 
Rachel Walcott (School of GeoSciences)
Subject areas: 
e-Science
Databases
WWW Tools and Programming
References: 
[1] http://www.familysearch.org [2] http://en.wikipedia.org/wiki/GEDCOM [3] http://www.backspace.com/mapapp/
Student project type: 

Grid-enable A Biomedical Database

Student: 
Mark MacGillivray
Grade: 
first

The number of databases that contain biomedical data is increasing rapidly. Many of these databases are stand-alone and this makes it difficult for researchers to perform queries and analyses over data that spans multiple databases.

Project status: 
Finished
Degree level: 
MSc
Background: 
Practical experience with web services and databases essential. Knowledge of workflow concepts desirable.
Supervisors @ NeSC: 
Other supervisors: 
Marco Roos, Bioinformatician, Institute for Informatics, University of Amsterdam Wendy Bickmore, Group leader, Human Genetics Unit, Medical Research Council
Subject areas: 
e-Science
Databases
Other
Student project type: 

Generate A Portal for Brain Imaging

Student: 
Albert Heyrovsky
Grade: 
first

Although some scientists, such as many physicists, may prefer a command line approach to submitting computational jobs, a majority of scientists want to be shielded from the innards of a computer. A popular approach is to build portals; user community web sites that allow job submissions from the convenience of a web browser.

Project status: 
Finished
Degree level: 
MSc
Background: 
Proficient in XML
Other supervisors: 
Trevor Carpenter, SFC Brain Imaging Research Centre, University of Edinburgh.
Subject areas: 
e-Science
Other
Projects: 
Student project type: 

Gaussian Process deconvolution for perfusion imaging: evaluation of the usage of distributed and parallel computing

Student: 
Fan Zhu

Final version of the thesis submitted.

Original project description:

Project status: 
Finished
Degree level: 
PhD
Background: 
MSc in Computer Science essential. Strong background in imaging and distributed computing important.
Other supervisors: 
Prof Joanna Wardlaw (SF Brain Imaging Research Centre, University of Edinburgh) Dr Trevor Carpenter (BRIC, University of Edinburgh)
Subject areas: 
Bioinformatics
Projects: 
References: 
1. Ostergaard L, Weisskoff RM, Chesler DA, Gyldensted C and Rosen BR “High resolution measurement of cerebral blood flow using intravascular tracer bolus passages: I.Mathematical approach and statistical analysis” Magn. Reson. Med. 36 715–25 2. Andersen IK et al; “Perfusion Quantification Using Gaussian Process Deconvolution”. Magnetic Resonance in Medicine 48:351-361 (2002). 3. Williams CKI and Rasmussen CE; “Gaussian processes for regression”. Advances in neural information processing systems, (1996), 514-520. 4. Choudhury A, Nair PB and Keane A; “A Data Parallel Approach for Large-Scale Gaussian Process Modeling”. Proc. the Second SIAM International Conference on Data Mining (2002).
Student project type: 

Parallelising CocaPhase

Student: 
Omer Jilani

The purpose of the project is to improve the efficiency of an existing application (CocaPhase) used to analyze a subset of chromosomes within a large genotype data. The project will take the program CocaPhase as an input and will reduce its run time by applying parallel programming techniques in the first phase. The second phase will enable the program to be run in a distributed environment over a Grid network (NGS and/or ECDF).

Project status: 
Finished
Degree level: 
MSc
Supervisors @ NeSC: 
Other supervisors: 
Murray Cole, School of Informatics
Subject areas: 
e-Science
Distributed Systems
Parallel Programming
Student project type: 

Mobile Code Execution in a Workflow Environment

Student: 
Adarsh Hiremangalur Ramsesh

The OGSA-DAI system provides an extensive suite of activities that can extract, transform, deliver and store data held in a variety of distributed data resources. While it is easy to add new activities to provide new functionality it would be of great interest to be able to add new behaviour to OGSA-DAI workflows dynamically.

Project status: 
Finished
Degree level: 
MSc
Background: 
The student should be comfortable with the Java programming language and willing to do some investigation on the potential interfaces between OGSA-DAI's activities and the external code.
Supervisors @ NeSC: 
Subject areas: 
e-Science
References: 
OGSA-DAI: http://www.ogsadai.org.uk Mobile Code: Internal OGSA-DAI report (can send on request) Java's Scripting framework: https://scripting.dev.java.net/ and http://www.mozilla.org/rhino/ScriptingJava.html
Student project type: 

Generating Graphical User Interfaces for Grid Computing Portals

Student: 
Carl Orebäck
Grade: 
first

Carl was awarded both the Agilent Prize and the Class Medal for best performance in the BEng Electronics and Computer Science degree

To investigate the use of graphical user interface languages and their generators and use these in conjunction with the Rapid Development Tool for Job Submission Portlets (RAPID), which is being developed at the National e-Science Centre.

Project status: 
Finished
Degree level: 
UG4
Background: 
You should definitely not be afraid of XML.
Supervisors @ NeSC: 
Subject areas: 
e-Science
Human-Computer Interaction
Other
Software Engineering
Projects: 
References: 
The RAPID project http://research.nesc.ac.uk/node/61
Student project type: 

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