School of Engineering


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  • Gaddiel Ouaknin

    Gaddiel Ouaknin

    Research Engineer, Chemical Engineering

    BioMy research interests include computational mechanics, soft matter, shape optimization, parallel algorithms, and stochastic calculus. During my PhD, using polymer field theory and level set methods, I developed shape optimization algorithms for predicting the phases of polymeric materials with a free surface. Previously, in my postdoc, I developed parallel algorithms on distributed memory architecture for Accelerated Stokesian Dynamics (ASD) to simulate large-scale stochastic particle systems correlated through hydrodynamic interactions. Recently, as a research engineer, I developed a novel algorithm for fast and accurate computation of correlated Brownian motion of particles in a Stokes flow with many-body hydrodynamic interactions with near- and far-field interactions. I am also interested in stochastic calculus theory and applications.