The Ken Kennedy Institute's August Member of the Month, Dr. Vicky Yao, is an Assistant Professor of Computer Science.
Vicky was a postdoctoral fellow at the Lewis-Sigler Institute for Integrative Genomics and received her PhD from the Department of Computer Science at Princeton University. She has numerous publications including her most recent, "RNA Identification of PRIME Cells Predicting Rheumatoid Arthritis Flares" in the New England Journal of Medicine (Jul 2020).
Her research focus is on computational biology, where she develops machine learning and statistical methods to improve understanding of the biological circuitry that underlies living organisms and how its dysregulation may lead to disease. She has also worked on modeling tissue and cell type specificity as well as disease progression, both by developing general methods (such as semi-supervised network integration) and in applying them to decipher the molecular underpinnings of diseases such as Alzheimer's, Parkinson's, and rheumatoid arthritis. Dr. Yao has worked closely with experimental biologists and clinicians in many of her projects including Paul Greengard's Lab at Rockefeller University, Coleen Murphy's Lab at Princeton University, and Bob Darhell's Lab at Rockefeller University.
What is your favorite book?
It's too had to choose a single favorite book! Of the books that I've read recently, some favorites are:
- Educated, by Tara Westover
- Stride Toward Freedom, by MLK Jr.
- Creativity, Inc., by Ed Catmull
- Uprooted, by Naomi Novik
How do you explain your research in one sentence?
I work on developing statistical and machine learning methods to improve our understanding of the biological circuitry that underlies living things and how malfunctions may contribute to disease.
What is your favorite aspect of your research?
Ultimately, the big motivating factor for me is the downstream potential to impact human health.
And along the way, I really enjoy collaborations, especially with biomedical researchers - when there's a good synergistic relationship, it can be a lot of fun. It's always exciting when the methods, tools, or predictions we make are put to actual use and end up helping discover something new about biology. Also, I get to learn so much about vastly different areas of research directly from a domain expert!
What challenges do you see in your research that you didn't expect?
Just as good collaborations are one of my favorite pasts of research, they can also have unexpected challenges. Miscommunication and/or differing expectations can occur when people of differing backgrounds are brought together. Sometimes, these can be easily resolved; other times, it can become difficult to navigate.
What is a favorite experience with the Ken Kennedy Institute or describe a time the Ken Kennedy Institute supported you in the past?
I enjoy the monthly luncheons that the Ken Kennedy Institute hosts, especially as someone who only recently started at Rice. It's a really nice balance between breadth and depth, where diverse computational problems and solutions across disciplines are presented, but also with enough detail to get a taste of the big goals and challenges of the research.
