Hi.

I am a PhD student at the Johns Hopkins University (JHU) in the Department of Applied Mathematics and Statistics (AMS). Before JHU, I studied mathematics at Brown University. I am an NSF Graduate Research Fellow, an opportunity that I am grateful to be selected for.

My current research is in Bayesian statistics and machine learning for medical data analysis, advised by Tamás Budavári and in collaboration with researchers from Johns Hopkins Neurology. 

I am motivated by a delicious mix of theory, computation, and application. In particular, changing the basis or finding transforms of a problem interests me. For example, I felt most alive when I learned the Fourier transform, SVD, Laplacian Eigenmaps, conjugate gradient method, Newton-Raphson optimization, or neat counting tricks.

Teaching and mentoring is also important and fulfilling to me. I seek to bring meaningful and uplifting experiences to others. I have experience teaching students from the elementary to the university levels. It amazes how some parts of our human nature don't change all that much—what works for children also works for adults. (๑˃ᴗ˂)ﻭ

In the past, I organized the JHU Directed Reading Program (DRP) and the JHU AMS graduate student seminar. Back at Brown, I co-organized the Symposium for Undergraduates in the Mathematical Sciences (SUMS).


See:


CV

email:   j  lim 76   [at-sign]   jhu  •d.o.t•  edu

office: Wyman Park Building, Room S415