CV

Education

• Ph.D in Computational and Mathematical Engineering, Stanford University, 2023
• M.S. in Computational and Mathematical Engineering, Stanford University, 2020
• B.S. in Systems Science and Engineering, Washington University in St. Louis, 2018
• B.S. in Computer Science, Washington University in St. Louis, 2018

Work experience

• Oct 2023 - now: Postdoctoral Research Associate
  • Data Science Institute & Center for Computational Molecular Biology, Brown University, Providence, RI
  • Supervisor: Dr. Sohini Ramachandran
• June 2022 - Sep 2022: Data Scientist Intern
  • PayPal Global Data Science Group, San Jose, CA

Publications

ML-MAGES enables multivariate genetic association analyses with genes and effect size shrinkage

Liu, X., Crawford, L., & Ramachandran, S. (2025). "ML-MAGES enables multivariate genetic association analyses with genes and effect size shrinkage." Genome Research (accepted).

KAlignedoscope: an interactive visualization tool for aligned clustering results

Guo, A., Ramachandran, S., & Liu, X. (2025). "KAlignedoscope: an interactive visualization tool for aligned clustering results." (under review)

Using mathematical constraints to explain narrow ranges for allele-sharing dissimilarities

Liu, X., Ahsan, Z., & Rosenberg, N. A. (2025). "Using mathematical constraints to explain narrow ranges for allele-sharing dissimilarities." Theoretical Population Biology.

ML-MAGES: A Machine Learning Framework for Multivariate Genetic Association Analyses with Genes and Effect Size Shrinkage

Liu, X., Crawford, L., & Ramachandran, S. (2025, April). "ML-MAGES: A machine learning framework for multivariate genetic association analyses with genes and effect size shrinkage." In International Conference on Research in Computational Molecular Biology (pp. 321-324). Cham: Springer Nature Switzerland.

Combinatorics of a dissimilarity measure for pairs of draws from discrete probability vectors on finite sets of objects

Ahsan, Z., Liu, X., & Rosenberg, N. A. (2024). "Combinatorics of a dissimilarity measure for pairs of draws from discrete probability vectors on finite sets of objects." arXiv preprint.

Clumppling: cluster matching and permutation program with integer linear programming

Liu, X., Kopelman, N. M., & Rosenberg, N. A. (2024). "Clumppling: cluster matching and permutation program with integer linear programming." Bioinformatics, 40(1), btad751.

When is the allele-sharing dissimilarity between two populations exceeded by the allele-sharing dissimilarity of a population with itself?

Liu, X., Ahsan, Z., Martheswaran, T. K., & Rosenberg, N. A. (2023). "When is the allele-sharing dissimilarity between two populations exceeded by the allele-sharing dissimilarity of a population with itself?." Statistical Applications in Genetics and Molecular Biology, 22(1), 20230004.

A Dirichlet model of alignment cost in mixed-membership unsupervised clustering

Liu, X., Kopelman, N. M., & Rosenberg, N. A. (2023). "A dirichlet model of alignment cost in mixed-membership unsupervised clustering." Journal of Computational and Graphical Statistics, 32(3), 1145-1159.

Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy

Parikh, V. N., Ioannidis, A. G., Jimenez-Morales, D., Gorzynski, J. E., De Jong, H. N., Liu, X., ... & Ashley, E. A. (2022). "Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy." Nature Communications, 13(1), 5107..

Extracting hierarchical features of cultural variation using network-based clustering

Liu, X., Rosenberg, N. A., & Greenbaum, G. (2022). "Extracting hierarchical features of cultural variation using network-based clustering." Evolutionary Human Sciences, 4, e18.

Effects of cultural transmission of surnaming decisions on the sex ratio at birth

Liu, X., & Feldman, M. W. (2021). "Effects of cultural transmission of surnaming decisions on the sex ratio at birth." Theoretical Population Biology, 141, 44-53.

Diffusion histology imaging combining diffusion basis spectrum imaging (DBSI) and machine learning improves detection and classification of glioblastoma pathology

Ye, Z., Price, R. L., Liu, X., Lin, J., Yang, Q., Sun, P., ... & Song, S. K. (2020). "Diffusion histology imaging combining diffusion basis spectrum imaging (DBSI) and machine learning improves detection and classification of glioblastoma pathology." Clinical Cancer Research, 26(20), 5388-5399.

Predicting inpatient glucose levels and insulin dosing by machine learning on electronic health records

Liu, X., Jankovic, I., & Chen, J. H. (2020). "Predicting inpatient glucose levels and insulin dosing by machine learning on electronic health records." medRxiv, 2020-03.

Talks

Clustering alignment for single cell analyses: streamlining model comparison and revealing informative genes.

November 07, 2025

Talk at Genome Informatics, Cold Spring Harbor Laboratory, NY

ML-MAGES: A machine learning framework for multivariate genetic association analyses with genes and effect size shrinkage.

April 01, 2025

Talk at The Research in Computational Molecular Biology (RECOMB) 2025 Conference, Seoul, Korea

Clumppling: a new method for aligning replicate solutions in population structure analysis.

June 01, 2023

Talk at Evolution 2023 Conference, Albuquerque, NM

A Dirichlet model of alignment cost in mixed-membership clustering results of ancestry inference.

October 01, 2022

Talk at Bay Area Population Genomics Conference, Berkeley, CA

Teaching

DSCoV Workshop

Advanced MATLAB for Scientific Computing (CME 292)

Linear Algebra with Application to Engineering Computations (CME 200/ME 300A)

Ordinary Differential Equations for Engineers (CME 102)

Service and leadership

• Ambassador and Organizing Committee Member, Women in Data Science (WiDS) at Brown University
• International Chair, Brown Postdoc Council
• Reviewer for multiple journals