Research highlights

I develop statistical methodologies to aid scientific discovery.

My current line of work involves a combination of theory, methods, and application. These include

  • Probabilistic machine learning methods for large-scale biodiversity assessment
  • Generative stochastic process frameworks for genomic data
  • Bayesian Non-negative matrix factorization algorithms
  • Flexible nonparametric models for density estimation
  • Biological investigation of somatic modification in cancer and RNA editing

In recognition of my doctoral dissertation, I received the Savage Award in Applied Methodology at the 2025 Joint Statistical Meeting. Read it below!

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

Publications and manuscripts

Preprints

  1. Zito, A., Rigon T., Roslin T., Niittynen, P., Hebert P. D. N., iBOL consortium, Ovaskainen O. and Dunson D. B. (2026). Predicting global biodiversity via Hubbell regression. Submitted to ?? :) [bioRxiv]

  2. Modi, A., Zito, A., and Parmigiani, G. (2026). Pan-Cancer Genomic Scars of Alternative End Joining and Single-Strand Annealing. Submitted to BMC Cancer . [bioRxiv]

  3. Zito, A., Parmigiani, G. and Miller, J. W. (2025). Poisson process factorization for mutational signature analysis with genomic covariates. Journal of the American Statistical Association ACS, Major Revision. [arXiv]

  4. Xue, C., Zito, A. and Miller, J. W. (2024). Improved control of Dirichlet location and scale near the boundary. Bayesian Analysis, R&R [ArXiv] [GitHub] - JSM 2025 SBSS student paper competition award received by Cathy Xue

  5. Zito, A. and Miller, J. W. (2024). Compressive Bayesian non-negative matrix factorization for mutational signature analysis. Biometrics, Major Revision. [ArXiv] [GitHub]

Articles in refereed journals

  1. Orsholm, J.*, Zito, A.*, Somervuo, P., Braga M, Chazlot, N, Roslin, T. and Furneaux, B. (2025). Discovering the unseen: a performance comparison of taxonomic classification methods under unknown DNA barcodes. Methods in Ecology and Evolution, in press [bioRxiv]

  2. Lee, C. J., Zito, A., Sang, H., and Dunson, D. B. (2025). Logistic-Beta Processes for dependent random probabilities with beta marginals. Bayesian Analysis, in press [ArXiv] [GitHub] - Lindley Prize 2025 - honorable mention

  3. Zito, A., Greaves, D., Soriano, J. and Richardson, L. (2025). Pareto optimal proxy metrics. Applied Stochastic Models in Business and Industry, 41: e70003 [Pub][ArXiv]

  4. 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]

  5. 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.

  6. Zito, A., Rigon, T., Ovaskainen, O., and Dunson, D. B. (2023). Bayesian modeling of sequential discoveries. Journal of the American Statistical Association (Theory & Methods), 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., Xue, C., and Miller, J. W. (2025). Accounting for Transcriptional Asymmetries in Mutational Signature Analysis Using Compressive Bayesian Non-negative Matrix Factorization In: di Bella, E., Gioia, V., Lagazio, C., Zaccarin, S. (eds) *Statistics for Innovation IV. SIS 2025. Italian Statistical Society Series on Advances in Statistics. Springer, Cham.

  2. 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]

  3. 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., Parmigiani, G., Miller, J. W. and Samur, M. (2026+). Joint analysis of mutational process in DNA and RNA from multiple myeloma.

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