Edoardo (Edo) Airoldi

Assistant Professor
Department of Statistics
Systems Biology Ph.D. Program
Faculty of Arts & Sciences
Harvard University

mailing address: Science Center, Harvard University, 1 Oxford Street, Cambridge, MA 02138, USA
phone: (617) 496-8318  
fax: (617) 496-8057
email: airoldi AT fas DOT harvard DOT edu

now.   I develop statistical and computational elements for the analysis of complex graphs and interacting dynamical systems, including yeast molecular biology and social networks. The focus of my research is on (i) statistical methodology and theory for graphs and their attributes, including the exchangeable graph model, (ii) metabolism and cellular proliferation, (iii) hypotheses testing and inference on signaling and metabolic pathways, including the map-kinase pathways, and the pathways regulating carbon and nitrogen metabolism. More broadly, my interests include probabilitsic algorithms, approximation theorems, random matrix analysis, convex and combinatiorial optimization, and geometrical intuitions.

then.   In December 2006, I receved a Ph.D. from Carnegie Mellon, working on statistical machine learning and the analysis of complex systems with Stephen Fienberg and Kathleen Carley. My dissertation develops statistical and computational elements of graph theory that support data analysis of complex systems and their dynamics. Till December 2008, I was a postdoctoral fellow in the Lewis-Sigler Institute for Integrative Genomics of Princeton University working with Olga Troyanskaya, David Botstein, and James Broach. I developed mechanistic models to gain computational insights into aspects of the molecular biology of yeast cells that are not directly observable with experimental probes, working closely with biologists and in the areas of cellular differentiation, cellular development, and cancer.

  analyzing complex graphs   recent talks
  • Elements of statistical graph theory. Northeastern University (Center for Complex Networks Research), December 2nd 2009, Boston, MA.

  • A systems-level analysis of cellular proliferation. Harvard University (School of Engineering and Applied Sciences), November 19th 2009, Cambridge, MA.

  • Elements of statistical graph theory. University of Connecticut (Department of Statistics), November 18th 2009, Storrs, CT.

  • A statistical perspective on complex networks. Harvard University (Institute for Quantitative Social Sciences), November 4th 2009, Cambridge, MA.

  • Statistical analysis of graphs and node attributes. International Meeting of the Psychometic Society, July 23rd 2009, Cambrdge, UK.

  • The exchangeable graph model. University College Dublin, June 16th 2009, Dublin, Ireland.

  • A statistical perspective on cellular growth. ETH meeting on Statistical Advances in Genome-scale Data Analysis, May 5th, Ascona, Switzerland.

  • The exchangeable graph model. Harvard University (Radcliffe Institute for Advanced Studies), February 6-7th 2009, Cambridge, MA.

  2009
  1. Barutcuoglu, Z., Airoldi, E.M., Dumeaux, V., Schapire, R.E., & Troyanskaya, O.G. (2009). Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields. Bioinformatics, 25: 1307-1313. (pdf)

  2. *Airoldi, E.M., *Huttenhower, C., Gresham, D., Lu, C., Caudy, A., Dunham, M., Broach, J., Botstein, D., & Troyanskaya, O.G. (2009). Predicting cellular growth from gene expression signatures. PLoS Computational Biology, 5, e1000257. (pdf)
  2008
  1. Airoldi, E.M., Blei, D.M., Fienberg, S.E., & Xing, E.P. (2008). Mixed-membership stochastic blockmodels. Journal of Machine Learning Research, 9, 1981-2014. (pdf) (a shorter version appeared at NIPS 2008)

  2. Warren, R., Airoldi, E.M., & Banks, D. (2008). Network analysis of Wikipedia. In: Statistical Methods in E-Commerce Research, Jank & Shmueli, Eds., Wiley & Sons.

  3. Joutard, C.J., Airoldi, E.M., Fienberg, S.E., & Love, T.M. (2008). Discovery of latent patterns with hierarchical Bayesian mixed-membership models and the issue of model choice. In: Data Mining Patterns: New Methods and Applications, IGI.

  4. Brauer, M.J., *Huttenhower, C., *Airoldi, E.M., Rosenstein, R., Matese, J.C., Gresham, D., Boer, V.M., Troyanskaya, O.G., & Botstein, D. (2008). Coordination of growth rate, cell cycle, stress response and metabolic activity in yeast. Molecular Biology of the Cell, 19, 352-367. (pdf)
  2007
  1. Airoldi, E.M. (2007). Getting started in probabilistic graphical models. PLoS Computational Biology, 3, e252. (pdf)

  2. Airoldi, E.M., Fienberg, S.E., Skinner, K.K. (2007). Whose ideas? Whose words? Authorship of the Ronald Reagan radio addresses. Political Science & Politics, 40, 501-506. (pdf)

  3. Airoldi, Blei, Fienberg, Goldenberg, Xing & Zheng, Eds. (2007). Statistical Network Analysis: Models, Issues & New Directions. Lecture Notes in Computer Science, volume no. 4503. Springer-Verlag. (pdf)

  4. Airoldi, E.M. (2007). Discussion on Handcock, Raftery and Tantrum 'Model-based clustering for social networks'. Journal of the Royal Statistical Society, Series A, 170, Part 2, 30-31. (pdf)

  5. Silva, R., Airoldi, E.M., & Heller, K.A. (2007). Small sets of interacting proteins suggest latent linkage mechanisms through analogical reasoning. Gatsby Computational Neuroscience Unit Technical Report, GCNU TR 2007-001. (pdf)

  6. Malin, B., & Airoldi, E.M. (2007). Confidentiality preserving audits of electronic medical record access. World Congress on Health (Medical) Informatics (MEDINFO), Brisbane, Australia. (pdf)
  2006
  1. Airoldi, E.M. (2006). Bayesian mixed-membership models of complex and evolving networks. Unpublished doctoral dissertation, School of Computer Science, Carnegie Mellon University, PA USA. (pdf) (Recipient of the Savage award honorable mention, 2007)

  2. Airoldi, E.M., Anderson, A., Fienberg, S.E., Skinner, K.K. (2006). Who wrote Ronald Reagan's radio addresses? Bayesian Analysis, 1, 289-320. (pdf) (tr stat-03-789) (notes)
  2005
  1. Airoldi, E.M., & Carley, K.M. (2005). Sampling algorithms for pure network topologies: Stability and separability of metric embeddings. ACM KDD Explorations (Special Issue on Link Mining), 7, 13-22. (pdf)

  2. Airoldi, E.M., Blei, D.M., Fienberg, S.E., & Xing, E.P. (2005). A latent mixed-membership model for relational data. ACM KDD Workshop on Link Analysis, Chicago IL. (pdf) (Recipient of the John Van Ryzin award, 2006)

  3. Airoldi, E.M., Cohen, W.W., & Fienberg, S.E. (2005). Bayesian methods for frequent terms in text: Models of contagion and the Delta square statistic. CSNA & INTERFACE Annual Meetings, St. Louis MI. (pdf)

  4. Malin, B., Airoldi, E.M., & Carley, K.M. (2005). A social network analysis model for name disambiguation in lists. Journal of Computational and Mathematical Organization Theory, 11, 119-139. (pdf)

  5. Gross, R., Airoldi, E.M., Malin, B., & Sweeney, L.A. (2005). Integrating utility into face de-identification. Privacy Enhancing Technologies (Revised Selected Papers), Lecture Notes in Computer Science, vol. 3856, 227-242. (pdf)

  6. Malin, B., Airoldi, E.M., Edoho-Eket, S., & Li, Y. (2005). Configurable security protocols for multi-party data analysis with malicious participants. IEEE International Conference onf Data Engineering (ICDE), Tokyo Japan. (pdf)

  7. Airoldi, E.M., Malin, B., & Sweeney, L.A. (2005). Technologies to defeat fraudulent schemes related to email requests. AAAI Symposium on Artificial Intelligence Technologies for Homeland Security, Stanford CA. (pdf)
  2004
  1. Airoldi, E.M., & Faluotsos, C. (2004). Recovering latent time series from their observed sums: Network tomography with particle filters. ACM International Conference on Knowledge Discovery & Data Mining (KDD), Seattle WA. (pdf) (tr cs-04-130) (Runner-up for best paper award)
  earlier
  1. Airoldi, E.M. (2000). Forecasts for Italian and Greek macroeconomic indicators. Global Data Watch, J.P. Morgan Economic Research. (issues of March 6-13-20-27, April 3-10-17-24, May 1-8)

  2. Fornari, I., & Airoldi, E.M. (1999). Assessing Italy's inflation gap relative to the Euro area. Global Data Watch, J.P. Morgan Economic Research. (issue of December 20)

  3. Airoldi, E.M. (1999). The theory of weak convergence of probability measures and its applications in statistics. Unpublished dissertation, Institute for Quantitative Methods, Bocconi University, Milan Italy. (Gold medal for best graduates, 1999)

  collaborators
  • David Banks (Duke), Zafer Barutcuoglu (Princeton), David Blei (Princeton), David Botstein (Princeton), Kathleen Carley (Carnegie Mellon), William Cohen (Carnegie Mellon), Christos Faloutsos (Carnegie Mellon), Stephen Fienberg (Carnegie Mellon), Fan Guo (Carnegie Mellon), Katherine Heller (University College London), Curtis Huttenhower (Princeton), Ihor Lemischka (Mount Sinai School of Medicine), Jure Leskovec (Carnegie Mellon), Xiodong Lin (University of Cincinnati), Rong Lu (Stanford), Bradley Malin (Vanderbilt), Florian Markowetz (Princeton), Robert Schapire (Princeton), Ricardo Silva (University College London), Olga Troyanskaya (Princeton), Robert Warren (University of Waterloo), Eric Xing (Carnegie Mellon).