I’m a PhD student at Columbia, advised by professor John Cunningham. My research interests include statistical machine learning, data mining, and bioinformatics. Prior to Columbia, I studied Mathematics and Statistics at Oxford.


I have built and maintain R and Python implementations of CoDaCoRe, which can be found at R-codacore and py-codacore. For any questions or comments related to these, please drop me a line at eg2912@columbia.edu.

Preprints and Publications

  • Thom Quinn, Elliott Gordon-Rodriguez, and Ionas Erb. “A critique of differential abundance analysis, and advocacy for an alternative.” arXiv (Submitted). [paper]

  • Elliott Gordon-Rodriguez, Thom Quinn, and John Cunningham. “Learning Sparse Log-Ratios for High-Throughput Sequencing Data.” Bioinformatics, 2021 (Accepted). [paper]

  • Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, Geoff Pleiss and John Cunningham. “Uses and Abuses of the Cross-Entropy Loss: Case Studies in Modern Deep Learning.” In 1st I Can’t Believe It’s Not Better Workshop, Neural Information Processing Systems (NeurIPS), 2020. [paper] [talk]

  • Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, and John Cunningham. ‘‘The Continuous Categorical: a Novel Simplex-Valued Exponential Family." In International Conference on Machine Learning (ICML), 2020. [paper] [talk]