About Me

I am a PhD candidate in Physics at the University of Illinois Urbana-Champaign.  My work in the Ferguson Group concerns the application of simulation and machine learning techniques to the design of smart nanomaterials.  In general, I am interested in machine learning for guided materials design and for the fundamental understanding of proteins both beneficial–such as those that can be used for organic nanoelectronics–and harmful–such as those that contribute to neurodegenerative diseases such as Alzheimer’s. 

My Current Project

Self-assembling organic molecules containing aromatic ring chemistries form multi-molecular aggregates that display electron delocalization over the entire aggregate. This property is due to the overlap of the π orbitals of the aromatics, and leads to semiconductive and optical properties that make aggregates of this type ideal choices for organic electronics, such as organic light-emitting diodes, organic field-effect transistors, and organic photovoltaic cells. Organic and biocompatible versions of electronics offer a plethora of benefits, including ease of manufacturing, use with noninvasive biomedical devices, and non-intrusive integration into ecological systems.

I am currently employed in using a combination of different computational techniques to study one such family of peptides a multiscale level, with an eye towards eventual design of similar organic molecules for a variety of applications.

I have recently become interested in the use of patchy particles as a toybox model for gaining a deeper understanding of a broad variety of physical systems.

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