About the workshop:
In recognition of the pervasiveness of networks in science and society, the Department of Statistics at the Pennsylvania State University will host a Workshop on Statistical Network Science with Applications on May 19 and 20, 2023. The workshop will feature presentations by distinguished members of the field and extended discussions led by workshop participants, hoping to facilitate the exchange of ideas and plant the seeds for the next generation of statistical network scientists. The workshop will consist of 1 1/2 days of research presentations and extended discussions and a 1/2 day-long picnic in the scenic hills surrounding the Pennsylvania State University.
Date: MAY 19TH – 20TH, 2023
Register on Conference Website here: https://sites.psu.edu/snsa23/
See full speaker bios on the conference website here: https://sites.psu.edu/snsa23/speakers/
Reka Albert (Penn State University), "Connecting Network Structure, Dynamics, and Control"
Shankar Bhamidi (University of North Carolina at Chapel Hill), "Dynamic Networks: One Has to Do the 'Math'"
Yuguo Chen (University of Illinois Urbana-Champaign), "Inferring Social Influence in Dynamic Networks"
Bruce Desmarais (Penn State University), "Estimating Latent Diffusion Networks with Event History Models"
Yang Feng (New York University), "Pairwise Covariates-Adjusted Block Model for Community Detection"
Tracy Ke (Harvard University), "Optimal Network Membership Estimation under Severe Degree Heterogeneity"
Jing Lei (Carnegie Mellon University), "Spectral Clustering for Heterophilic Stochastic Block Models with Dynamic Node Memberships"
Martina Morris (University of Washington), "ERGMs: Niche or Necessary?"
Sarah Rajtmajer (Penn State University), "Information Operations in Turkey: Manufacturing Resilience with Free Twitter Accounts"
Purnamrita Sarkar (University of Texas at Austin), "When Random Initializations Help: a Study of Variational Inference for Community Detection
Ji Zhu (University of Michigan), "A Latent Space Model for Hypergraphs with Diversity and Heterogeneous Popularity"
David R. Hunter, Maggie Niu, and Yubai Yuan, Jacob Cornejo, Alina Kuvelkar, and Yin Tang