SFU computing scientist Martin Ester is world’s most influential data-mining scholar
Computing science professors Jian Pei and Ke Wang named among top 100
The international list names the world's top-cited research scholars in science and engineering, recognizing outstanding technical achievements that have lasting impact on the research community.
Data miners look for patterns in big data and the AMiner list is a data-mining tool itself. It tracks and ranks scholars using an algorithm based on citation counts collected by top publications.
AMiner credits Ester with authoring 169 papers, reaping more than 21,000 citations and hitting 50 on the h-index, which measures published scholars’ productivity and citation impact. He also scored well in research diversity and sociability (the number of collaborations on papers with colleagues).
Ester is currently co-director of SFU’s Databases and Data Mining Laboratory with professor Ke Wang, who also made the list at No. 59. The pair are leveraging their expertise to develop data-mining methods that make sense of big data in genomics by relating them to clinical patient data.
By doing so, they hope personalized medicine can become a reality.
“Right now, most medical treatments are designed for the average patient using a one-size-fits-all-approach,” says Ester. “This approach is successful for some patients but not for others.
“Personalized medicine is an emerging approach to disease diagnosis, prognosis, treatment and prevention that takes into account differences in people’s genes, environments and lifestyles.”
Computing science professor Jian Pei also made the list at No. 18.
Pei, a Canada Research Chair (Tier 1) in Big Data Science, is one of the world’s foremost researchers on big data. He is recognized for developing effective and efficient ways to analyze and capitalize on the vast stores of data housed in applications—from social networks and network security informatics to healthcare informatics, business intelligence and web searches.
He is currently leading a big-data research project to improve healthcare delivery, decision-making and outcomes. The project—the Pacific Blue Cross Health Informatics Lab—is a partnership between SFU and Pacific Blue Cross.