Research

Working papers and publications:

• Parikh, Lanners, Akras, Zafar, Rudin and Volfovsky. Estimating Trustworthy and Safe Optimal Treatment Regimes.
• Katta, Parikh, Rudin and Volfovsky. Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data.
• Volfovsky, Airoldi and Rubin. Causal inference for ordinal outcomes. code
• Weltz, Fiez, Volfovsky, Laber, Mason, Nassif and Jain. Experimental Designs for Heteroskedastic Variance NeuRIPS (2023).
• Belloni, Fang and Volfovsky. Neighborhood Adaptive Estimators for Causal Inference under Network Interference (2023).
• Lanners, Parikh, Volfovsky, Rudin and Page. From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference. UAI2023.
• Parikh, Rudin and Volfovsky. MALTS: Matching After Learning to Stretch. JMLR (2023).
• Morucci, Rudin and Volfovsky. Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics (2023).
• Chen and Volfovsky. Identifying World Events in Dynamic International Relations Data Using a Latent Space Model (2023).
• Tierney and Volfovsky. Bias and Excess Variance in Election Polling: A Not-So-Hidden Markov Model (2023).
• Parikh, Hoffman, Sun, Ge, Jing, Amerineni, Liu, Sun, Zafar, Struck, Volfovsky, Rudin, and Westover. Effects of Epileptiform Activity on Discharge Outcome in Critically Ill Patients (2023). Lancet Digital Health.
• Mathews and Volfovsky. Latent Community Adaptive Network Regression (2021).
• Orlandi, Murray, Linearo and Volfovsky. Density Regression with Bayesian Additive Regression Trees (2021). Laplace SBSS Student Paper Award!
• Weltz, Volfovsky and Laber. Reinforcement learning methods in public health. Clinical Therapeutics (2021+)
• Tierney, Bail and Volfovsky. Author Clustering and Topic Estimation for Short Texts (2021).
• Tierney and Volfovsky. Sensitivity Analysis for Causal Mediation through Text: an Application to Political Polarization. Proceedings of the First Workshop on Causal Inference & Natural Language Processing (2021).
• Bu, Aiello, Volfovsky and Xu. Likelihood-based Inference For Partially Observed Stochastic Epidemics With Individual Heterogeneity (2021).
• Chauhan, Orlandi, Rajab, Bedeir, Volfovsky, and Mokashi. Post-operative Outcomes in Infants Undergoing ABO Incompatible Heart Transplantation in the US. The Annals of Thoracic Surgery, 2021.
• Brinkley-Rubinstein, LeMasters , Nguyen, Nowotny, Cloud, and Volfovsky. The association between intersystem prison transfers and COVID-19 incidence in a state prison system. PLOS One (2021).
• Zivich, Volfovsky, Moody, and Aiello. Assortativity and Bias in Epidemiologic Studies of Contagious Outcomes: A Simulated Example in the Context of Vaccination American Journal of Epidemiology (2021).
• Morucci, Orlandi, Roy, Rudin and Volfovsky. Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation. UAI2020. arXiv:2003.01805
• Awan, Morucci, Orlandi, Roy, Rudin and Volfovsky. Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference. AISTATS2020. arXiv:2003.00964
• Bail, Guay, Maloney, Combs, Hillygus, Merhout, Freelon and Volfovsky. Assessing the Russian Internet Research Agency’s impact on the political attitudes and behaviors of American Twitter users in late 2017. Proceedings of the National Academy of Sciences (2019)
• Parikh, Rudin and Volfovsky. An Application of Matching After Learning to Stretch (MALTS). Observational Studies, 2019.
• Bu, Aiello, Xu, and Volfovsky. Likelihood-based Inference for Partially Observed Epidemics on Dynamic Networks. arXiv:1910.04221. Journal of the American Statistical Association (2022). SBSS Student Paper Award!
• Mathews, Mayya, Volfovsky and Reeves. Gaussian Mixture Models for Stochastic Block Models with Non-Vanishing Noise. CAMSAP2019. arXiv:1911.01855
• Reeves, Mayya, and Volfovsky. The Geometry of Community Detection via the MMSE Matrix. ISIT2019. arXiv:1907.02496
• Awan, Liu, Morucci, Roy, Rudin and Volfovsky. Interpretable Almost-Exact Matching With Instrumental Variables. UAI2019.
• Dieng, Liu, Roy, Rudin and Volfovsky. Collapsing-Fast-Large-Almost-Matching-Exactly: A Matching Method for Causal Inference. AISTATS2019.
• Bu, Xu, Heller and Volfovsky. SMOGS: Social Network Metrics of Game Success. AISTATS2019. arXiv:1806.06696
• Bail, Argyle, Brown, Bumpus, Chen, Hunzaker, Lee, Mann, Merhout, and Volfovsky. Exposure to Opposing Views can Increase Political Polarization: Evidence from a Large-Scale Field Experiment on Social Media. Proceedings of the National Academy of Sciences (2018). SocArXiv:10.17605/OSF.IO/4YGUX
• Wang, Morucci, Awan, Liu, Roy, Rudin, Volfovsky. FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference. Journal of Machine Learning Research. arXiv:1707.06315
• Jagadeesan, Pillai and Volfovsky. Designs for estimating the treatment effect in networks with interference. Annals of Statistics 2019+. arXiv:1705.08524
• Hollenbach, Bojinov, Minhas, Metternich, Minhas, Ward and Volfovsky. Principled Imputation Made Simple: Multiple Imputation Using Gaussian Copulas. Sociological Methods and Research, Accepted 2018.
• Basse, Volfovsky and Airoldi. Observational studies with unknown time of treatment. arXiv:1601.04083
• Sussman, Volfovsky and Airoldi. Analyzing statistical and computational tradeoffs of estimation procedures. arXiv:1506.07925
• Volfovsky and Airoldi. Sharp total variation bounds for finitely exchangeable arrays (2016). Statistics & Probability Letters 114, 54-59.
• Volfovsky and Hoff. Testing for nodal dependence in relational data matrices (2015). Journal of the American Statistical Association 110 (511), 1037-1046
• Volfovsky and Hoff. Hierarchical array priors for ANOVA decompositions of cross-classified data (2014). The Annals of Applied Statistics 8 (1), 19
• Hoff, Fosdick, Volfovsky and Stovel. Likelihoods for fixed rank nomination networks (2013). Network Science 1 (03), 253-277