Hi, I'm a 4th year PhD student in the Machine Learning Department at Carnegie Mellon where I'm advised by Prof. Eric Xing and am a member of the SAILING Lab. I am very thankful to be supported by an NSF Graduate Fellowship. Before that, I was an undergraduate in Computer Science and Applied Math at Princeton, and worked with Prof. Rob Schapire.
My main research interests are in theoretical and applied statistical learning techniques: particularly probabilistic graphical models and kernel/spectral methods. I also recently taught a few lectures on kernel and spectral methods for graphical models as part of CMU's Probabilistic Graphical Models class, and you can find the slides here.
See the tabs above for more information about my research and teaching.