Graph mining unlocks secrets in data

The widespread use of technology presents computer scientists with infinite opportunities to interpret and manage massive volumes of resulting data. Through a variety of algorithms and complex code, Dr. Guimu Guo uses parallel and distributed computing to decipher graph data, from social networking to biological gene mapping.

An assistant professor of computer science in the College of Science & Mathematics , Guo uses graph mining under different computing conditions to develop more complex and efficient ways to organize and investigate millions of data points from a wide range of sources (domains).

"Graph mining in computer science is like finding hidden patterns or insights in a network of connected items," Guo said. "Imagine a social network where people are connected as friends; graph mining helps discover interesting groups of friends, popular people, or common interests. It's a way to analyze large and complex networks to understand how things are connected and uncover useful information, such as trends, clusters, or unusual connections, which can help in making decisions or predictions."

Through his research and collaborations, Guo applies graph mining to a variety of domains, including social networks analysis and biomedical applications.

An important distinction in Guo's work is his progression from parallel graph mining on central processing units (CPUs) to a focus on "leveraging parallel processing with graphics processing units (GPUs)."

In simple terms, a CPU is one standalone computing unit that performs complex calculations, one step at a time. A GPU can manage greater volumes of graph data while also running multiple processes at a time.

With the GPU's multitasking capability, Guo is exploring graph mining using parallel GPU computing techniques to tackle even more challenging problems.

"The synergy between parallel GPU computing and graph mining holds tremendous potential," he said. "By using multi-GPUs, we can develop more intelligent systems capable of making sense of the vast and intricate data structures that define our world."

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