Investigating how much majority-class data models need and which negative examples best preserve performance, across molecular screening, baseball, and sandwich ratings. SciPy 2026 talk.

Poster presentation on machine learning for virtual screening of RNA-stabilizing excipients.

Using deep learning to screen antibacterials effective against Neisseria gonorrhoeae.

Using genetic algorithms and autoencoders to generate novel antibacterials.

Evaluate the effect of chromatin regulator combinations on gene expression in yeast.

Experimental and computational screening techniques to discover and characterize small molecules active against “metabolically dormant” bacteria.

Using explainable machine learning techniques to discover a structural class of antibiotics active against S. aureus.

Easing barriers for biologists to use machine learning to analyze, intepret, and design nucleic acid, peptide, and glycan sequences.

Sequence-to-function deep learning frameworks for engineered riboregulators.

A CRISPR-based assay for the detection of opportunistic infections post-transplantation and for the monitoring of transplant rejection.

LADL, light-activated dynamic looping for endogenous gene expression control. Highlighted in Nature’s technologies to watch in 2020.

Created neural machine translation and video capture algorithm. Honorable mention in Engineering senior design competition.