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Above, left to right: Steven Wang, Huaiping Zhu and Zijiang Yang, with framed letters of congratulations from the president and CEO of CFI
Canada Foundation for Innovation (CFI) recently sent letters of congratulations to three York researchers for their project on mathematical and statistical analysis of complex systems, large data sets and performance analysis. CFI has provided $250,045 in funding for the $600,000 project.
Right: SARS coronavirus
What this translates to is funding for research into transmission of mosquito-borne diseases, such as the West Nile virus, and infectious diseases, such as SARS. As well, it will enable researchers to continue working on improving classification of genes related to human diseases, such as cancer, and to drug discovery.
Another facet of the research is into complex optimization algorithms operating on very large databases, which will provide an objective tool to measure information technology (IT) performance and a science-based guideline to optimize corporate IT spending.
Project leader is York mathematician and statistician Huaiping Zhu, whose colleagues include Steven Wang and Zijiang Yang.
Left: Researchers will be studying mosquito-borne diseases
“The funding is for the building up of a high-power parallel computing lab in the department: the main server of 64 paralleled nodes and 16 workstations,” said Zhu. “The Faculty of Arts and the Department of Mathematics and Statistics have been very supportive in finding space for the lab and making plans to renovated the space.”
Zhu’s work includes mathematical modelling and analysis in ecology and epidemiology as he studies transmission of mosquito-borne and infectious diseases. By using both analytical techniques and complex computer simulations, Zhu can predict the possible outbreaks of the disease and its transmission pattern and make recommendations for public health policy.
Wang is building sophisticated statistical models for classifications and predictions. These models will be applied to find lead compounds for drug discovery and to understand protein functions. He and his team members will also develop advanced statistical algorithms to partition massive data sets into smaller and more interpretable subsets. The findings will have wide applications to data mining.
Yang’s research is focused on information technology (IT) investment evaluation, performance analysis and data mining algorithms. The research on evaluating IT investment will provide an objective tool to measure IT performance and provide a science-based guideline for companies to optimize IT spending. Performance analysis, meanwhile, can have a significant impact on improving managerial performance. In addition, the findings will provide a peer group for comparisons. This information can be applied in many fields, from banking to bioinformatics.