Active Research Projects

Chemical Informatics
Discovering new drugs is an expensive and challenging process. Any new drug should not only produce the desired response to the disease but should do so with minimal side effects and be superior to the existing drugs in the market. The goal of this project is to develop effective and efficient algorithms for analyzing chemical compound databases and identifying biologically active compounds.
Bioinformatics has emerged as an exciting new research area giving rise to numerous challenging computational problems whose successful solution will ultimately impact every aspect of our every day life. This is currently one of the lab's main research thrust areas and is primarily designed to develop and apply data-mining and knowledge-based techniques to solve various problems arising in this field.
Data Mining
The goal of this project is to develop effective and computationally efficient algorithms for analyzing large volumes of data. The ultimate purpose of these analyses is to discover key and actionable information and gain insights about the underlying processes/systems that created the data (or are being described by the data).
Graph Partitioning
This project is probably the longest running research activity in the lab and dates back to the time of George's PhD work. The fundamental problem that is trying to solve is that of splitting a large irregular graphs into k parts. This problem has applications in many different areas including, parallel/distributed computing (load balancing of computations), scientific computing (fill-reducing matrix re-orderings), EDA algorithms for VLSI CAD (placement), data mining (clustering), social network analysis (community discovery), pattern recognition, relationship network analysis, etc.