| 2021 | WSDM | Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction. | Shuxi Zeng, Murat Ali Bayir, Joseph J. Pfeiffer III, Denis Charles, Emre Kiciman |
| 2015 | WWW | Overcoming Relational Learning Biases to Accurately Predict Preferences in Large Scale Networks. | Joseph J. Pfeiffer III, Jennifer Neville, Paul N. Bennett |
| 2015 | SIGIR | Modeling Website Topic Cohesion at Scale to Improve Webpage Classification. | Dhivya Eswaran, Paul N. Bennett, Joseph J. Pfeiffer III |
| 2014 | ICDM | A Scalable Method for Exact Sampling from Kronecker Family Models. | Sebastin Moreno, Joseph J. Pfeiffer III, Jennifer Neville, Sergey Kirshner |
| 2014 | ICDM | Composite Likelihood Data Augmentation for Within-Network Statistical Relational Learning. | Joseph J. Pfeiffer III, Jennifer Neville, Paul N. Bennett |
| 2014 | KDD | Assortativity in Chung Lu Random Graph Models. | Stephen Mussmann, John Moore, Joseph J. Pfeiffer III, Jennifer Neville |
| 2014 | WWW | Attributed graph models: modeling network structure with correlated attributes. | Joseph J. Pfeiffer III, Sebastin Moreno, Timothy La Fond, Jennifer Neville, Brian Gallagher |
| 2011 | ICWSM | Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure. | Joseph J. Pfeiffer III, Jennifer Neville |
| 2009 | WACV | A general framework for reconciling multiple weak segmentations of an image. | Soumya Ghosh, Joseph J. Pfeiffer III, Jane Mulligan |