In this project, we design a comprehensive suite of algorithms (IPzip) for compressing IP network packets. Our offline algorithms reduce the storage space significantly (up to 20% better compression ratio than gzip), and our online algorithms are real time and able to compress tier-1 network traffic data on the fly without buffering (up to 10% better compression ratio than gzip). When applied to aggregated traffic data set, IPzip can squeeze the data set to be less than 1% of original size (gzip can only reduce it to 30%).

This work is described in the paper "IPZip: a stream-aware IP compression algorithm"

In this project, we introduce new Haar wavelet synopses which approximate the time-varying data in databases with nonuniform accuracy, which is specified by the biased queries from users (weights). Our data synopses are designed to be efficient not only in generation but also in maintainance when dealing with time varying data. The generation cost is linear in term of both time and space, and the update cost is sublinear. The accuracies of our synopses are validated against other linear methods by using both synthetic and real data sets.

This work is described in the paper "Nonuniform Compression in Databases with Haar Wavelet"

"DUDE" is a universal denoiser which is asymptotically optimal for both semi-stochastic and stochastic settings. We propose three better algorithms that reduce the DUDE's cost from suplinear to linear as well as an efficient denoiser performance estimator with only linear complexity.

This work is described in the paper "Efficient string matching algorithms for combinatorial universal denoising"

In this project, we use physiological, behavioral, and environmental sensors to detect patterns in the subject's daily life. For behavioral sensing we use accelerometers, interfaced with the BlueSentry. For environmental and behavioral sensing we use microphones. For physiological sensing we use EKG and EMG sensors. With all the signals captured by these sensors, we discover interesting patterns that may be of potential benefits to the health care industry.

This work is described in the paper "Wireless in loco sensor data collection and applications"

In this project, we studied several routing curves for a novel routing protocol, named trajectory based routing, which forwards packet along a pre-defined path. The idea behind it is that in dense networks, traditional information forward is too costly in network operations like flooding and discovery, while trajectory based routing can be an ideal information forwarding method in these senario.

In this project, we tried a totally different approach to solve the problem "finding the genetic reason for diseases". Instead of reconstructing haplotype from SNP data, we reject a genetic region directly by correlate the sick people with their SNP data.