Edoardo M Airoldi

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Stephen E Fienberg 1942-2016Maurice Falk University Professor of Statistics and Social ScienceVerified email at cs.cmu.edu
David BleiProfessor of Statistics and Computer Science, Columbia UniversityVerified email at columbia.edu
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UVerified email at cs.cmu.edu
Gábor CsárdiRStudioVerified email at rstudio.com
Panagiotis (Panos) ToulisUniversity of Chicago, Booth SchoolVerified email at chicagobooth.edu
Alexander FranksDepartment of Statistics and Applied Probability, University of California Santa BarbaraVerified email at pstat.ucsb.edu
Olga TroyanskayaPrinceton University and Flatiron Institute, Simons FoundationVerified email at princeton.edu
Margaret E. RobertsPolitical Science, University of California San DiegoVerified email at ucsd.edu
Brandon M. StewartPrinceton UniversityVerified email at princeton.edu
Bradley MalinAccenture Professor of Biomedical Informatics, Biostatistics, and Computer Science, VanderbiltVerified email at vanderbilt.edu
Tamás NepuszDepartment of Biological Physics, Eötvös Loránd UniversityVerified email at hal.elte.hu
Eric WangUniversity of FloridaVerified email at ufl.edu
Tuan Q. PhanAssociate Professor of BusinessVerified email at hku.hk
Nikolai SlavovNortheastern University, Harvard University, MIT, Princeton UniversityVerified email at fas.harvard.edu
D. Allan DrummondAssociate Professor, Biochemistry and Molecular Biology, Genetic MedicineVerified email at uchicago.edu
David BotsteinPrinceton UniversityVerified email at princeton.edu
Dave ChoiCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Jean Pouget-AbadieGoogle ResearchVerified email at google.com
Laura ForastiereAssistant ProfessorVerified email at yale.edu
Patrick J. WolfeProfessor of Statistics, University College LondonVerified email at stat.harvard.edu

Edoardo M Airoldi

Professor of Statistics & Data Science Temple University & PI, Harvard University

Verified email at fas.harvard.edu

Statistics Causal Inference Network Science Statistical Machine Learning Artificial Intelligence


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Guidelines for the use and interpretation of assays for monitoring autophagy DJ Klionsky, K Abdelmohsen, A Abe, MJ Abedin, H Abeliovich, ... Autophagy 12 (1), 1-222, 2016	13437*	2016
Statistical network analysis with the igraph software package G Csárdi, T Nepusz, EM Airoldi New York, NY: Springer, 2016	13144*	2016
Mixed membership stochastic blockmodels EM Airoldi, DM Blei, SE Fienberg, EP Xing Journal of Machine Learning Research 9 (3), 1981-2014, 2008	2604	2008
The structural topic model and applied social science ME Roberts, BM Stewart, D Tingley, EM Airoldi NIPS Workshop on Topic Models: Computation, Application, and Evaluation 4, 1-20, 2013	1976*	2013
Analysis and design of RNA sequencing experiments for identifying isoform regulation Y Katz, ET Wang, EM Airoldi, CB Burge Nature methods 7 (12), 1009-1015, 2010	1495	2010
A survey of statistical network models A Goldenberg, AX Zheng, SE Fienberg, EM Airoldi Foundations and Trends in Machine Learning 2 (2), 129-233, 2010	1139	2010
A model of text for experimentation in the social sciences ME Roberts, BM Stewart, EM Airoldi Journal of the American Statistical Association 111 (515), 988-1003, 2016	772	2016
Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast MJ Brauer, C Huttenhower, EM Airoldi, R Rosenstein, JC Matese, ... Molecular biology of the cell 19 (1), 352-367, 2008	661	2008
Reversible, specific, active aggregates of endogenous proteins assemble upon heat stress EWJ Wallace, JL Kear-Scott, EV Pilipenko, MH Schwartz, PR Laskowski, ... Cell 162 (6), 1286-1298, 2015	485	2015
Systems-level dynamic analyses of fate change in murine embryonic stem cells R Lu, F Markowetz, RD Unwin, JT Leek, EM Airoldi, BD MacArthur, ... Nature 462 (7271), 358-362, 2009	331	2009
Summarizing topical content with word frequency and exclusivity J Bischof, EM Airoldi Proceedings of the 29th international conference on machine learning (icml …, 2012	295	2012
Stochastic blockmodels with a growing number of classes DS Choi, PJ Wolfe, EM Airoldi Biometrika 99 (2), 273-284, 2012	284	2012
Stochastic blockmodel approximation of a graphon: Theory and consistent estimation EM Airoldi, TB Costa, SH Chan Advances in Neural Information Processing Systems (NIPS), 2013	217	2013
Differential stoichiometry among core ribosomal proteins N Slavov, S Semrau, EM Airoldi, B Budnik, A van Oudenaarden Cell Reports, 2015	202	2015
Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast G Csárdi, A Franks, DS Choi, EM Airoldi, DA Drummond PLoS Genetics 11 (5), e1005206, 2015	202	2015
Mixed membership stochastic block models for relational data with application to protein-protein interactions EM Airoldi, DM Blei, SE Fienberg, EP Xing ENAR International Biometrics Society Annual Meeting, 2006	202	2006
Integrating utility into face de-identification R Gross, E Airoldi, B Malin, L Sweeney International Workshop on Privacy Enhancing Technologies (PET), 227-242, 2005	200	2005
Post-transcriptional regulation across human tissues A Franks, E Airoldi, N Slavov PLoS computational biology 13 (5), e1005535, 2017	193	2017
Defining the essential function of yeast Hsf1 reveals a compact transcriptional program for maintaining eukaryotic proteostasis EJ Solís, JP Pandey, X Zheng, DX Jin, PB Gupta, EM Airoldi, D Pincus, ... Molecular Cell, 2016	193	2016
Identification and estimation of treatment and interference effects in observational studies on networks L Forastiere, EM Airoldi, F Mealli Journal of the American Statistical Association, 2021	187	2021

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