Monica T. Dayao

Hi! I’m a computational biologist at Biohub and a member of the DeRisi Lab at UCSF. My current research is focused on developing and applying machine learning models to better understand autoimmune disease, specifically studying antibody-antigen interactions at scale.

Research Interests:

• machine learning for biology
• modeling antibody-antigen interactions
• biology foundation models for patient-focused research
• computer vision

Previously:

I did my PhD in the Systems Biology Group at Carnegie Mellon University, advised by Prof. Ziv Bar-Joseph. My thesis focused on developing machine learning methods for the analysis of spatial proteomics datasets, as part of the Human BioMolecular Atlas Program (HuBMAP). I collaborated closely with Enable Medicine and the University of Pittsburgh Medical Center (UPMC).

I earned my BA and MEng degrees in Engineering, with specializations in Information Engineering and Bioengineering, from the University of Cambridge. There, I worked with Dr. Timothy O’Leary and collaborated with Prof. Jim Haseloff on deep learning approaches for the segmentation of plant microscopy images.

Misc.

During my free time, I enjoy climbing, mountaineering, cooking/baking, cycling, golfing, and playing volleyball. My fiancé and I own a small camper van named Mochi, which we use for many of our outdoor adventures.