A student from Pace University’s Seidenberg School of Computer Science and Information Systems had the opportunity of a lifetime when they were chosen to attend a conference in Washington D.C. last fall in September.
Yaodong Du, a Ph.D. candidate, was chosen by Juan Shan, assistant professor in the Department of Computer Science, to attend the CHASE2018 Conference from Sept. 26 to 28.
The conference, titled, The Third IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies, gave Du the chance to present his and Shan’s work on an advanced research project in the field of medicine. Du explained that the conference is a “leading international conference in the field of connected health, which is related to our research area.”
“[At] the conference, we [presented] our recent work on using [a] machine learning method to analyze 3D MRI images for knee osteoarthritis prediction,” explained Du.
The work presented at the conference by Du and Shan is dedicated to diagnosing this degenerative joint disease. Their machine learning method specializes in analyzing 3-dimensional magnetic resonance imaging (MRI) images to detect osteoarthritis of the knee. This means that their research can help doctors detect the disease before patients experience permanent joint damage.
Along with presenting their own work, Du and Shan had the opportunity to network and listen to other top industry professionals speak about their areas of expertise.
Du says that one of the best parts of the conference was when “many researchers from different institutions stopped by, [asked] questions and discussed.”
“[CHASE2018] widened my sight, and deepened my cognition on the research and my knowledge,” Du explained, highlighting the impact the conference had on him.
Our Seidenberg students are accessing and working with technology that has the ability to innovate and to heal. With brilliant minds and abundant opportunities, Seidenberg students make worthwhile change.
As for the future of their work, Du said, “we will continue our work on exploring useful information to help [in the field of] predicting diseases.”
Du and Shan’s work will continue to carve out a path in the Pace community for other Seidenberg students to follow.
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