Hi, I'm Jocelyn and I'm an assistant professor in Computational Health Sciences at the University of Minnesota Twin Cities. I'm also an affiliate faculty member at the School of Statistics and lead for the Real World Data Analytics Methods core at the Center for Learning Health System Sciences.
- I was a recipient of the NSF Mathematical Sciences Postdoctoral Research Fellowship, where I was mentored by Deanna Needell in the Department of Mathematics at UCLA.
- I completed my PhD studies in statistics with a concentration in mathematics at NC State, where I was advised by Ilse Ipsen.
- During my PhD studies, I was a recipient of the NSF Mathematical Sciences Graduate Internship and worked with Sherry Xiaoye Li in the Scalable Solvers Group at Lawrence Berkeley National Laboratory.
Research
My research interests are in scalable statistical data analysis and computing using tools from randomized algorithms, machine learning, low rank matrix and tensor factorizations, stochastic optimization, and numerical analysis. My work focuses on developing provable randomized algorithms to scale statistical machine learning methods for the analyses of modern massive, complex, and structured data. My computational projects have included applications to biobank data, hyperspectral imaging, and survey data containing free-form text responses. Please find my publications here and on Google Scholar.
Keywords: Scalable statistical computing, randomized algorithms, statistical machine learning, stochastic optimization, numerical analysis, nonnegative matrix factorization, tensors
Contact
Email: jocelync [at] umn [dot] edu