S. Oliveira
North Carolina A&T State University, North Carolina, United States
Keywords: Artificial microbial communities; synthetic ecology for adaptive collective behavior; programmable microenvironments; microfluidics and bioreactor networks; high-content imaging; biofilm engineering; predictive modeling and digital twins.
Living systems compute, adapt, and self-organize, yet we still lack a quantitative workflow to design multicellular microbial behaviors with the reliability of engineered systems. In real environments, emergent function is governed by spatial organization, transport, confinement, and stochastic communication, limiting translation to applications such as microbiomes, infection models, and biofilm technologies. My research program at North Carolina A&T State University (JSNN), supported by DARPA YFA, NSF, and the North Carolina Collaboratory, develops a predictive framework to control collective microbial behavior through programmable microenvironments. We integrate (i) modular micro- and milli-fluidic platforms for scalable perturbations across bioreactor networks; (ii) high-content imaging pipelines, including Partaker; and (iii) modeling frameworks coupling transport physics and community dynamics for digital-twin-enabled control. This approach enables the design of functional biofilms as engineered living materials for defense applications such as biofouling mitigation, while supporting scalable biomanufacturing aligned with DOE GENESIS. Together, this program establishes a pipeline for designing, measuring, validating, and controlling microbial systems as programmable technologies, enabling robust translation from laboratory platforms to real-world, field-deployable biological systems, and supporting rapid design iteration, system optimization, and integration with autonomous experimental and decision-making workflows across diverse biological scales and environmental conditions.