Research highlights

I am strongly motivated by application, which serves as a base for developing new statistical methodologies. My goal is to create simple yet effective methods that are theoretically justified and useful to practitioners who need to draw scientific conclusions.

My current line of work involves improving on Bayesian non-negative matrix factorization algorithms, with a strong emphasis on cancer genomics and mutational signatures analysis.

During my Ph.D. at Duke, I developed Bayesian nonparametric methodologies under the supervision of Professor David Dunson within Project LIFEPLAN, an international research group whose aim is to quantify biodiversity across the globe.

Ph.D. Dissertation Ph.D. defense slides Google Scholar

Publications and manuscripts

Preprints

  1. Xue, C., Zito, A. and Miller, J. W. (2024+). Improved control of Dirichlet location and scale near the boundary. Submitted, awaiting decision [ArXiv] [GitHub] - JSM 2025 SBSS student paper competition award received by Cathy Xue

  2. Zito, A. and Miller, J. W. (2024+). Compressive Bayesian non-negative matrix factorization for mutational signature analysis. Received Reject and Resubmit, working :) [ArXiv] [GitHub]

  3. Lee, C. J., Zito, A., Sang, H., and Dunson, D. B. (2024+). Logistic-Beta Processes for dependent random probabilities with beta marginals. Submitted, awaiting decision. [ArXiv] [GitHub]

Articles in refereed journals

  1. Zito, A., Greaves, D., Soriano, J. and Richardson, L. (2025). Pareto optimal proxy metrics. conditionally accepted at Applied Stochastic Models in Business and Industry [ArXiv]

  2. Zito, A., Rigon, T., and Dunson, D. B. (2024). Bayesian nonparametric modeling of latent partitions via Stirling-gamma priors. Bayesian Analysis, [Pub][ArXiv] [R Package]

  3. Zito, A., Rigon, T., and Dunson, D. B. (2023). Inferring taxonomic placement from DNA barcoding aiding in discovery of new taxa. Methods in Ecology and Evolution, 14, 529–542. [Pub] [ArXiv] [Code] [R package]. - Best poster award at IBSA2022 world meeting.

  4. Zito, A., Rigon, T., Ovaskainen, O., and Dunson, D. B. (2023). Bayesian modeling of sequential discoveries. Journal of the American Statistical Association (T&M), 118(544), 2521–2532. [Pub] [Manuscript] [R package] - Best Student/Postdoc Contributed paper award at IBSA2021 world meeting. - BEST award for Ph.D. student research 2022, Dept. of Statistical Science, Duke University

Refereed conference proceedings and discussions

  1. Zito, A. and Miller, J. W. (2024). Discussion to Sparse Bayesian factor analysis when the number of factors is unknown by Fruhwirth–Schnatter, S., Hosszejini, D., and Lopes, F. L., Bayesian Analysis [Pub]

  2. Zito, A., Rigon, T. and Dunson, D. B. (2021). Modelling of accumulation curves through Weibull survival functions. In Book of Short Papers of the Italian Statistical Society 2021 (Perna, C., Salvati, N. and Schirripa Spagnolo, F., editors). ISBN: 9788891927361. [Link part 1] [Link part 2]

Manuscripts in preparation

  1. Zito, A., Xue, C., Parmigiani, G., and Miller, J. W. (2024+). Localized mutational signature analysis.

  2. Zito, A., Parmigiani, G., Miller, J. W. and Samur, M. (2024+). Mutational signature analysis of RNA somatic mutations.

  3. Zito, A., Rigon T. and Dunson D. B. (2024+). A novel generalized linear model for quantifying biodiversity.

  4. Orsholm, J.*, Zito, A.*, Chazlot, N, Roslin, T. and Furneaux, B. (2024+). Comparing model performance for taxonomic classification of unknown DNA barcodes.


Address:
655 Huntington Ave, Boston, MA 02115, United States
Email:
azito@hsph.harvard.edu
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