My research examines the use of a Geographic Information System (GIS) -inspired model as the conceptual basis for interacting with Wireless Sensor Networks (WSNs). It builds on existing research in declarative and spatial models for WSN interaction (programming, tasking and querying WSNs) by using a GIS metaphor for the WSN, and creating efficient underlying mechanisms that support the interaction transparently as a distributed computation, examining the tradeoffs involved.
My research focuses on the development of a biosensor to detect and monitor multiple species of the marine dinoflagellete Alexandrium, the genus that produces the toxins responsible for Paralytic Shellfish Poisoning. I am developing a portable, surface plasmon resonance biosensor that utilizes peptide nucleic acid probes for species recognition in minimally processed samples collected at suspected bloom sites. This tool will be used to monitor and track the spatial occurrence of these Harmful Algal Blooms throughout the coast of the Gulf of Maine.
My research applies a geoinformatics perspective to a traditionally geochemical problem. I am combining data integration techniques with fate and transport modeling as a novel approach for non-point source pollution evaluation. I am analyzing mercury biogeochemical relationships using legacy data across multiple sample types, study sites and time series while exploring the use and limitations of marine bivalves as ubiquitous biosensors for coastal pollution.
My research is centered in the mathematical concept of anisotropy. We live in an anisotropic world that we model in isotropic media, creating significant gaps in reasoning and representation. Sensors not only are slave to the anisotropic world, but they give a source to witness the anisotropy and build systems to reason more effectively through knowledge.
My research is on the detection of areal events, such as storms, disease outbreaks, or traffic jams, by networks of simple sensors. This work follows two threads: ontology, and simulation. The ontology is an explicit specification of the conceptual components of areal events, and the relations among those components. It describes spatially extensive phenomena as they exist in the world, independent of how they are perceived. The second research thread explores events as they are perceived by sensor networks. The simulation framework aims to provide a way of defining occurrences in the network which is sound and complete with respect to the ontology.
My research has focused on the development of distributed
algorithms, using algebraic topology as a computational foundation.
The goal of this work is to discover topological properties of dynamic
spatial events, e.g. forest fires, using
wireless sensor networks. A scalable solution has been developed for
planar (2d) and non-planar (3d) deployments.
My research explores the effects of bioselective layer conformation on the associated biosensor sensitivity. This is accomplished by measuring shear horizontal, surface acoustic wave (SH-SAW) of a photosensitive polymer, allowing the determination of the viscoelastic sensitivity of the SH-SAW device. Further SH-SAW measurements of enzymatic biomolecule modifications were performed to determine the contribution of biomolecule conformation to SH-SAW biosensor response.
My research interest is in the area of sensor networks and autonomous sensing. More specifically, event detection, knowledge discovery, data modeling, resource conservation, and the self-organization of sensor nodes.
Sensitive and selective sensors are currently needed for the reliable detection of low, air-borne concentrations of hydrogen fluoride. The goal of my research is to design, fabricate, and test quartz-based surface acoustic wave resonators with
platinum electrodes, for the detection of hydrogen fluoride.
My research explores the use of artificial neural network models as spatiotemporal field interpolators, directed for use on wireless sensor network nodes embedded in a natural environment. Anticipated graduation is: Summer 2011.
My research focuses on minimizing energy consumption in wireless sensor networks through efficient computation and communication algorithms.
My research focuses on high precision indoor localization of passive wireless sensor nets. By analyzing indoor channels and combining RSS, AOA and TOA methods into one hybrid methodology, high resolution tracking systems can be developed. These
methods can then be used for shape-monitoring of inflatable structures in NASA's Lunar Habitat Program.
Genomics, or the study of genes and their function, is revolutionizing the way diseases are understood, diagnosed, and treated. DNA sequencing is a key technology to this field and the nanopore gene sequencing project which I am researching aims to dramatically reduce the cost and time required for sequencing. The goal is to pass a strand of DNA through a tiny hole, called a nanopore, and electronically sense each chemical base as it passes through.