Hello, thanks for visiting my webpage! I am a 4th year PhD student in the Bioinformatics and Computational Biology (BCB) at UNC Chapel Hill. I am fortunate to be advised by Professor Peter Mucha. My research interests are related to community detection in networks, and specifically how to 1) use community structure for network classification 2) handle attributed network data and 3) pre-process or condense network to facilitate more tractable community detection. Generally, I am very interested in how to use community structure to explore and make conclusions from network data. I have spent the majority of my PhD developing network analysis tools that relate to community structure but I also enjoy collaborating with biologists on clustering and classification problems. Previously, I graduated with a B.S. mathematics in 2013 from Dickinson College and also spent a summer at The Biocomplexity Institute @ Virginia Tech (previously Virginia Bioinformatics Institute).
Office: 432 Chapman Hall, University of North Carolina, Chapel Hill
April 2017: I will be a speaker at the AI with the best webinar presenting Prediction and Modeling with Networks. Link
January 2017: I developed a module on network analysis @ UNC for graduate students. We covered topics such as community detection, link prediction, anomaly detection, graph compression.
September 2016: I will be a speaker in the AI with the best online Webinar, where I will present Challenges in Community Detection and Effective Inference Techniques for Network Analysis. Please visit the following link to see all of the great speakers participating here. AIWithTheBest
July 2016: I attended the SIAM Workshop on Network Science (SIAM NS16) to present work on ‘Incorporating Gaussian Attribute Data in SBM Inference’
July 2016: I attended the SIAM Annual meeting to present our paper ‘Clustering Network Layers with the Strata Multilayer Stochastic Block Model’, which won the SIAM student paper prize.
June 2015: I attended in the NetSci conference in Zaragoza Spain and gave a talk MLSBM: A Framework for Fitting Multilayer Stochastic Block Models at the Statistical Inference for Network Models satellite.