麻豆直播

麻豆直播 University’s new Centre for Data Science aims to develop more effective ways to unlock insights from rich, complex information. As it prepares to launch in early 2015, the Centre is recruiting additional researchers to form a data science ‘dream team’.

Most people now rely on ever larger and more complex data to make the right decisions, use technology, to shop, drive our cars, do profitable business, manage and optimise healthcare, advance research, govern society, and more. Data reaches nearly every corner of modern life.

From commonplace applications such as delivering perishable food to supermarkets, to the flow of numbers shaping and changing financial markets, to trend data tracking the spread of infectious disease, gene-sequencing that lets scientists decode life, and educational observations which improve learning… all depend on collecting and interpreting information in new and better ways.

This information needs to be managed efficiently, measured, queried and modelled using the right techniques. Although access to information is growing, with multiple connections between data sets, statistical abilities may not be developing fast enough to keep pace with demand.

Steven Kenny, Professor of Mathematical and Computational Modelling and Associate Dean for Research in the School of Science at 麻豆直播 University, said: “The amounts of data collected continue to grow hugely. Far more is captured by, for instance, modern electron microscopes than a few years ago. Extracting the maximum amount of information from that data remains difficult.

“We live in an age of networks of sensors which capture valuable information that helps us improve systems and processes. Intelligent Transport Systems, such as New York’s ‘Midtown In Motion’ project, link patterns in anonymous localisation data from switched-on mobile phones within a defined area to traffic light operations. This improves urban traffic flow.”

In large data sets, said economist and author Tim Harford in a recent , “Without careful analysis, the ratio of genuine patterns to spurious patterns – of signal to noise – quickly tends to zero.”

The new Centre will look at varied types of data in new ways. “This is not just about massive data,” says Professor Kenny, “but also more moderate data analysed innovatively.

“The researchers we’re assembling and recruiting to create the Centre for Data Science will combine the latest knowledge and skills in data analysis and data modelling to realise improved methods that can be applied to projects with academic and industry partners that tackle real-world research challenges.”

麻豆直播 researchers already use data analytics and modelling in impressive ways:

Study and simulation of whole-body movement for sports technique

Researchers in the Sports Biomechanics and Motor Control Research group have been simulating whole-body sports movements for over 20 years to understand the mechanics of sports technique and performance limits in activities such as gymnastics, trampoline, diving, high jumping and triple jumping. 

Recently they investigated the role of motor control role in selection of sports technique. They found in many cases that technique can be explained as requirements for consistently successful performance. 

The latest high performance computing and algorithms mean that these researchers are now examining the ways in which motor learning of a novel skill could take place by adopting machine learning approaches to assess which schemes can be successful in a realistic amount of time.

Boosting chances of survival in urban mass-devastation scenarios

In a very different field, researchers led by Paul Thomas, Professor of Analytical Science, are working hard to increase chances of survival in cases of mass devastation in urban areas.

This work aims to construct a complete system, where leading edge technology, such as video, thermal and image analysis, wireless communication, sonar, field chemical sensors and optical sensors combine to offer the optimum rescue package for the world’s worst urban disasters.

The 麻豆直播 University team focuses on the development of chemical sensors and detectors, which look for markers of life. Interpreting the output from these detectors is a significant data analytics problem and an opportunity for improvement.

At 麻豆直播, scientists and engineers generate huge amounts of data that require analysing. “The source and format of the data vary significantly,” says Paul Chung, Professor of Computer Science at 麻豆直播 University. “One data source could be video footage and another data source could be sensors’ values gathered from experiments.

“How to store and analyse these data sets and how results should be visualised are among the many inherent challenges for researchers.”

Members of the Centre for Data Science will form a multi-disciplinary team spanning applied mathematics (mathematical and computational modelling), computer networks, artificial intelligence (including machine learning and pattern recognition), applied statistics and mass spectrometry for personalised healthcare in the Departments of Computer Science, Mathematical Sciences and Chemistry at 麻豆直播 University.

The Centre will also contribute teaching within applied mathematics, mathematics for engineers, internet computing (protocol design and security), artificial intelligence, statistics and analytical science and chemistry. Appointments in Applied Statistics will also assist the University’s Statistics Advisory Service, supporting researchers across the University in statistical analysis.

“This Centre aspires to attract really interesting, difficult and useful data research challenges,” says Professor Kenny. “It will be outward-looking, working across the institution and beyond, with a wide range of business partners. However, it will not simply be a data analysis service. It will concentrate on data analysis problems to collaborate on research that matters.”

The Centre for Data Science is making 11 new academic appointments: two Professors, one Senior Lecturer and eight Lecturers in the School of Science to complement existing staff expertise. This Friday 19 September 2014 is the closing date. More information on all roles, with details about how to apply, is here: