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About

I am a 5th-year PhD student in Biostatistics at Harvard University, advised by Rafael Irizarry and Giovanni Parmigiani. Previously, I earned a Bachelor's degree in Chemical & Biological Engineering from Princeton University. I work on statistical methods for genomic applications, with special interests in single-cell technologies and multi-dataset integration.

Preprints

"Significance Analysis for Clustering with Single-Cell RNA-Sequencing Data". Isabella N. Grabski, Kelly Street, Rafael A. Irizarry. bioRxiv (2022).

Manuscripts in Progress

"Multi-Study Non-negative Matrix Factorization for Mutational Signatures". Isabella N. Grabski, Lorenzo Trippa, Giovanni Parmigiani.

"Bayesian Bivariate Quantile Copula Model". Roberta De Vito, Isabella N. Grabski, Barbara E. Engelhardt.

Publications

"Bayesian Combinatorial Multi-Study Factor Analysis". Isabella N. Grabski, Roberta De Vito, Lorenzo Trippa, Giovanni Parmigiani. Annals of Applied Statistics (accepted).

"A Probabilistic Gene Expression Barcode for Annotation of Cell Types from Single-Cell RNA-seq Data". Isabella N. Grabski, Rafael A. Irizarry. Biostatistics (2022).

Presentations

Multi-Study Non-negative Matrix Factorization for Mutational Signatures. Isabella N. Grabski, Lorenzo Trippa, Giovanni Parmigiani. ISBA, 2022 (invited talk).

Multi-Study Non-negative Matrix Factorization for Mutational Signatures. Isabella N. Grabski, Lorenzo Trippa, Giovanni Parmigiani. BAYSM, 2022 (contributed talk).

Multi-Study Non-negative Matrix Factorization for Mutational Signatures. Isabella N. Grabski, Lorenzo Trippa, Giovanni Parmigiani. ENAR, 2021 (invited talk).

Bayesian Combinatorial Multi-Study Factor Analysis with the Indian Buffet Process. Isabella N. Grabski, Roberta De Vito, Lorenzo Trippa, Giovanni Parmigiani. Joint Statistical Meetings, 2020 (contributed talk).

A Probabilistic Gene Expression Barcode for Annotation of Cell-Types from Single Cell RNA-Seq Data. Isabella N. Grabski, Rafael A. Irizarry. BioC, 2020 (Poster).

Bayesian Combinatorial Multi-Study Factor Analysis with the Indian Buffet Process. Isabella N. Grabski, Roberta De Vito, Lorenzo Trippa, Giovanni Parmigiani. Workshop for Women in Machine Learning, 2019 (Poster).

Awards

  • National Science Foundation Graduate Research Fellowship, 2020-2023.
  • ISBA Travel Award, 2022.
  • BAYSM Travel Award, 2022.
  • Biostatistics Teaching Award, Harvard University, 2021.
  • Certificate of Distinction in Teaching, Harvard University, 2021.
  • Workshop for Women in Machine Learning Travel Award, 2019.

Teaching Experience

  • PhD Preparatory Program (Instructor, Summer 2021, Summer 2022).
  • Biostatistics 230, Probability Theory and Methods (Teaching Assistant, Fall 2020, Fall 2021).
  • Biostatistics 223, Applied Survival Analysis (Teaching Assistant, Spring 2020).
  • Biostatistics 210, Applied Regression (Teaching Assistant, Fall 2019).
  • StatStart Summer Program, Statistical Methods (Instructor, Summer 2019).
  • Pipelines into Biostatistics (Graduate Student Research Mentor, Summer 2019).