My undergraduate training was in computer science, physics and math, while my graduate degree is in Scientific Computing (?). I've striven to integrate these diverse interests into a knowledge and experience base than can be applied to a wide breadth of research interests in different disciplines.
With this sort of interdisciplinary perspective, I've recently been working on integrating some complex systems and network algorithms into use for genome assembly. Genome assembly Integrating the mathematics, physics and computer science view points to solve a vital step in the reassembly process for genomic data. This had led to a few developments both in complex systems that I've presented at conferences, and in genomics research that I've published. My Ph.D. dissertation will focus on this improvement in genome assembly and the algorithms developed to support and analyze genomic data.
Previously I've spent time working in the Laboratory for Nonlinear Dynamics in Optical Systems which is part of the Chaos group at University of Maryland. Working with Dr. Rajarshi Roy I performed simulations of nonlinear synchronization in small networks of optical systems. Chaos and non-linearity still hold a distinct fascination for me, though my current research has drifted more to large network analysis and dynamics, apart from chaos.
Generally speaking the topics I find fascinating to discuss and think about are fairly varied but focus on the following areas:
Chaos
Large network dynamics
Complex systems: synchronization, dynamics
Network algorithms
Computational Algorithms including efficiency and implementations
Effective teaching techniques for mathematics and computer science
Cognitive and Neurological processes behind learning (HOW people learn)