Dr. Nganguia’s earliest involvement in research dates back to his undergraduate studies. In his sophomore year he began learning about ways mathematics could be used to model various processes and natural phenomena. He was introduced to fluid dynamics, and later co-authored his first paper [NGA06] that investigated plausible links between coastal topology and whale strandings.

In graduate school, Dr. Nganguia’s then turned his focus to applications in medicine and physiology, and the central role it plays in machine learning. He went on to write his doctoral dissertation investigating the response of deforming boundaries to an externally applied electric field. He pursued this research topic during his first postdoctoral appointment. In particular he considered how droplets (simple boundaries defined by surface tension) [NGA13a, NGA15, NGA16], and vesicles (closed lipid layers frequently used as models for biological cells) [NGA13b] are affected by an imposed electric field.

Later during his second postdoctoral appointment, Dr. Nganguia branched out and began investigating microorganisms’ swimming in complex fluids. He quickly found the topic practically relevant and nontrivial, considering microorganisms live in a world with negligible inertia (a world where viscous forces dominate). Moreover, while propulsion in simple fluids has enjoyed decades of productive research, most biological fluids are polymeric and hence display complex rheological properties. He investigated the swimming mechanics of microorganisms in so-called thin-shearing fluids [NGA17], and in heterogeneous environments [NGA18].

Dr. Nganguia is now working on integrating these theories (electrohydrodynamics and microorganisms’ propulsion) to investigate problems of practical relevance. Funded by the U.S. National Science Foundation, he hopes his research will help develop electrically-driven artificial micro-swimmers that can be deployed to improve patients’ care and outcomes. He continues to collaborate with colleagues at various institutions on these and other research projects related to mathematical biology and fluid dynamics.

PI Nganguia acknowledges support from NSF LEAPS-MPS 2211633