The Professor Is In: Juan Shan
Seidenberg Assistant Professor Juan Shan, PhD, talks to Opportunitas about her grant from the National Science Foundation, and her quest to use computer science to better understand arthritis pain.
Juan Shan, PhD, is an Assistant Professor of Computer Science at the Seidenberg School of Computer Science and Information Systems. A 2016 Kenan Award winner, Shan took time this month to chat with Opportunitas about exciting research developments, the National Science Foundation, and what Seidenberg might look like come 2025.
Congratulations on your recent NSF Grant! Would you be able to describe your research, and what you hope to accomplish with the NSF grant?
Thank you! The research project is about using machine learning methods to predict the progression of knee osteoarthritis (OA), which is mainly characterized by the loss of cartilage. Through learning the pattern of cartilage thickness change on MRI images, trained models can predict the future status of cartilage layers given a patient's current MRI images. We hope to build a 3D prediction model that can predict and reconstruct the whole knee cartilage layer in the future, e.g., two years later, four years later, six years later, and eight years later. Patients that have great chance to lose cartilage should take early treatment and prevention programs that could delay or stop the progression of OA.
What are you excited to be working on right now?
Right now we are conducting a preliminary study to validate some early concepts using some representative slides of the whole knee. The first stage experiment results are promising, so we are ready to move to next step-building a model for the whole cartilage layer. Currently, I have two graduate students working on this project, and we have an online meeting with our collaborator at Tufts Medical Center once a week. The collaboration with Tufts Medical Center is going well.
Where do you hope to see Seidenberg in five years? Ten years?
In five years, we are going to grow in both the student enrollment and new faculty employment. We will be more research-oriented while we keep the excellence of teaching at the same time. In 10 years, Seidenberg's investment in research and excellent teaching should start paying us back by improved reputation, more grants, and higher rankings.
What is your favorite thing about working at Pace?
My favorite thing about working at Pace is its diversity and the possibility to explore different opportunities. From undergraduate teaching to PhD teaching, from grant application 101 to NSF grant finalization, from doing research with undergrads to doing research with working professionals, there are many different experiences that have enriched my academic portfolio and fostered my career. No matter what kind of help I am seeking, I can find it from Pace Community.
What professor at Pace would you most want to take a class with (and why)?
I would want to take a class with Carol Wolf, professor emerita of computer science. During my first year at Pace, I asked Carol to observe my teaching of Java programming class, as a peer evaluation is required. Carol has provided many valuable and useful suggestions to help me improve my teaching, and is a very well-respected professor by students and colleagues.
What four people, living or dead, would you invite to a dinner party?
- > My grandpa, who passed 19 years ago. I want to let him know that the little girl he loved has grown a lot and want to share with him the good things that happened in my life. He would be very happy and proud of me.
- > My childhood best friend, with whom the contact has been lost for many years. I want to know how she is doing and wish the best for her.
- > My husband. We haven't gone out for a date in quite a while, so I guess it will be great if we could go to a dinner party together.
- > My three-month-old son. He is such a cute baby that I would love to take him everywhere with me if possible.
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