🌪 Turbulence, Flows, Plasmas, and Machine Learning

Landry Horimbere

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Dan Lathrop

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Project type: Computation and Experiments

Nonlinear dynamical systems are everywhere in nature. Their complex behavior gives rise to interesting phenomena such as chaos, turbulence and unpredictability. In the Lathrop Lab, a variety of experiments are currently underway exploring the nonlinear characteristics of selected systems. These experiments include, broadly, liquid metal dynamos and turbulence, rotating fluids in planetary geometries, and specialized electronics. The lab also uses machine learning for prediction of these phenomena.

Past work by undergraduate researchers has included:

  • Use of machine learning to predict convection waves in a benchtop experiment
  • Exploration of the dynamics of soap bubbles to understand the singularity formed at pinch-off
  • Studies of the relationship between the applied electric potential and the morphology of dendrites
  • Explorations of the dynamics of collapsing bubbles in a foam, through statistical analysis of audio recordings of steady-state foam
  • Understanding droplet separation in liquids by monitoring an applied electric current between the separating droplets

Landry Horimbere is a graduate student in the Lathrop lab focusing specifically on plasma dynamics. He is a TREND almunus and has mentored various TREND students. Professor Lathrop has had success in guiding undergraduate researchers, having mentored over 20 students, some of whom have appeared as coauthors in peer-reviewed publications such as Nature.

Landry and Professor Lathrop aim to increase student independence by having the students manage and conduct all aspects of the research from experimental design to analysis and presentation.

Alumni/Previous Projects

Want help getting in touch with these mentors? Reach out to Daniel.