My research broadly is in the field of Network Analysis, specifically focused on studying features of real data and constructing and analyzing graph models which maintain those features. A network, in this case, is a set of nodes (people, web pages, etc) connected by edges (physical connection, collaboration, etc). I am interested in random graph models, which are used to study how well an algorithm may do on a real-world network, and for testing properties that may further improve algorithms.
My research is at the intersection of math and computer science. I love using computational tools to explore (and validate!) hypotheses.
I am planning to take up to 4 students for Summer 2020. Projects will be focused on constructing higher-order graph models and tools. There will be mathematical and programming components. I will likely ask you to do your coding in Julia or Python. A description of the projects I am interested in can be read about on GrinnellShare.
Students interested in doing a summer MAP with me need to do the following two things:
- Fill out the Science Summer Research Application Form, found on GrinnellShare. This is due February 21, 2020.
- Fill out this application. This is due February 21, 2020.
If you’d like to discuss the possibility of working with me I’d be happy to chat with you in person.
- On Large-Scale Dynamic Topic Modeling with Nonnegative CP Tensor Decomposition.Preprint
- Chase-escape with death on Trees. Preprint
- Centrality in Dynamic Competition Networks.
Accepted for publication at Complex Networks 2019. Preprint
- Classes of Preferential Attachment and triangle Preferential Attachment models with Power-law Spectra. The Journal of Complex Networks. Link
- Coin-flipping, Ball-dropping, and Grass-hopping for Generating Random Graphs from Matrices of Edge Probabilities. SIAM Review. Link
- The HyperKron Graph Model for higher-order features.
IEEE International Conference on Data Mining (ICDM), 2018. Link
- Development of CNNs for feature extraction.
Algorithms for Synthetic Aperture Radar Imagery, International Society for Optics and Photonics. Link
- Dynamic Competition Networks: detecting alliances and leaders.
Algorithms and Models for the Web Graph. Link
- Revisiting Power-law Distributions in Spectra of Real World Networks.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD ’17). Link
- Measurement of the Energy-Dependent Angular Response of the ARES Detector System and Application to Aerial Imaging. IEEE Transactions on Nuclear Science. Link