Edoardo M. Airoldi
Analysis of network data
Design of experiments on networks
Ill-posed inverse problems
Regulation and signaling dynamics
Edoardo M. Airoldi
Associate Professor of Statistics
- Methodology for the analysis of network data
- Design and analysis of experiments on large networks
- Geometry of inference in ill-posed inverse problems, including network tomography and contingency tables
- Modeling and inference of regulation and signaling dynamics, including sequencing and mass spectrometry
- Approximate inference strategies for data analysis at scale
- Ph.D. in Computer Science, Carnegie Mellon University, January 2007.
- M.S. in Computational and Statistical Learning, Carnegie Mellon University, August 2003.
- M.S. in Statistics, Carnegie Mellon University, August 2003.
- B.S. in Mathematical Statistics, Bocconi University, October 1999.
- January 2013 - present, Associate Professor of Statistics, Harvard University
- September 2011 - present, Associate Faculty, The Broad Institute of MIT and Harvard
- January 2009 - December 2012, Assistant Professor of Statistics, Harvard University
- December 2006 - December 2008, Postdoctoral Fellow, Lewis-Sigler Institute for Integrative Genomics & Department of Computer Science, Princeton University
- P Toulis, EM Airoldi. Asymptotic and finite-sample properties of estimators based on stochastic gradients. Annals of Statistics. In press.
- AW Blocker, EM Airoldi. Template-based methods for analyzing chromatin structure dynamics genome-wide. Journal of the American Statistical Association. In press.
- S Lunagomez, S Mukherjee, R Wolpert, EM Airoldi. Geometric representations of distributions on hypergraphs. Journal of the American Statistical Association. In press.
- M Roberts, B Stewart, EM Airoldi. A topic model for experimentation in the social sciences. Journal of the American Statistical Association. In press.
- EM Airoldi, JM Bischof. A regularization scheme on word occurrence rates that improves estimation and interpretation of topical content (with discussion). Journal of the American Statistical Association. Forthcoming in December 2016.
- E Solis, J Pandey, X Zheng, D Jin, P Gupta, EM Airoldi, D Pincus, V Denic. Defining the essential function of yeast Hsf1 reveals a compact transcriptional program for maintaining eukaryotic proteostasis. Molecular Cell, 63, 60-71, 2016.
- EJ Wallace, JL Kear-Scott, EV Pilipenko, MH Schwartz, PR Laskowski, AE Rojek, CD Katanski, JA Riback, MF Dion, AM Franks, EM Airoldi, T Pan, BA Budnik, DA Drummond. Heat stress triggers formation of reversible, specific, functional aggregates of endogenous proteins in yeast. Cell, 162, 1286â€“1298, 2015.
- AM Franks, G Csardi, DS Choi, EM Airoldi, DA Drummond. Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast. PLoS Genetics, 11, e1005206, 2015.
- AM Franks, G Csardi, DA Drummond, EM Airoldi. Estimating a structured covariance matrix from multilab measurements in high-throughput biology. Journal of the American Statistical Association, 110, 27-44, 2015.
- P Toulis, EM Airoldi. Scalable estimation strategies based on stochastic approximations: Classical results and new insights. Statistics and Computing, 25, 781-795, 2015.
- R Silva, S Kang, EM Airoldi. Predicting traffic volumes and estimating the effects of shocks in massive transportation systems. Proceedings of the National Academy of Sciences, 12, 5643-5648, 2015.
- EM Airoldi, T Costa, F Bassetti, F Leisen, M Guindani. Generalized species sampling priors with latent Beta reinforcements. Journal of the American Statistical Association, 109, 1466-1480, 2014.
- EM Airoldi, AW Blocker. Estimating latent processes on a network from indirect measurements. Journal of the American Statistical Association, 108, 149-164, 2013.
- DS Choi, PJ Wolfe, EM Airoldi. Stochastic blockmodels with growing number of classes. Biometrika, 99, 273-284, 2012.
- EM Airoldi, B Haas. Polytope samplers for ill-posed inverse problems. Journal of Machine Learning Research, W&CP, 15, 110-118, 2011.
- Y Katz, E Wang, EM Airoldi, CB Burge. Analysis and design of RNA sequencing experiments for identifying mRNA isoform regulation. Nature Methods, 7, 1009-1015, 2010.
- A Goldenberg, AX Zheng, SE Fienberg, EM Airoldi. A survey of statistical network models. Foundations and Trends in Machine Learning, 2, 129-233, 2009.
- EM Airoldi, DM Blei, SE Fienberg, EP Xing. Mixed-membership stochastic blockmodels. Journal of Machine Learning Research, 9, 1981-2014, 2008.
- EM Airoldi, A Anderson, SE Fienberg, KK Skinner. Who wrote Ronald Reagan's radio addresses? Bayesian Analysis, 1, 289-320, 2006.