Published research on cell process models, revealing more robustness than previously proposed, challenging the 'edge of chaos' theory. Developed Python libraries pystablemotifs and cubewalkers for fast attractor detection, control, and GPU-accelerated simulation in Boolean networks.
Research Experience
Prior to joining PNNL, was a postdoctoral research associate at the CASCI laboratory at Binghamton University. Research areas include systems biology modeling, machine learning applications to protein structure, complexity science, and network dynamics.
Education
Postdoctoral research associate studying complex systems at the CASCI laboratory at Binghamton University. Specific details about degrees, schools, and advisors are not provided.
Background
A computational biologist with a background in math and physics. Current research focuses on the application of data science and dynamics to systems biology, particularly on how feedback loops in biological networks give rise to complex behaviors.
Miscellany
Interests include developing methods to sparsify multi-layer networks while taking into account multiple data sources. These methods are applied to various problems in computational social science, health, and biomedical complexity.