Mission
The Faculty of
Computer Science and Information Technology curriculum grounds learning in real world applications and issues. Faculty works actively with both undergraduates and graduate students, providing valuable hands-on teaching and research experience. Lecture series and seminars round out the students' educational experience, and provide a variety of forums to expose students to the widest possible spectrum of information.
One of faculty's great strengths has been its ability to push experimental computer science ideas from theory to practical demonstration, continuously testing new insights by constructing prototype systems in which they are embodied.
One of faculty's great strengths has been its ability to push experimental computer science ideas from theory to practical demonstration, continuously testing new insights by constructing prototype systems in which they are embodied.
Research
The primary goal of our group is to extend the state of the art in the field of artificial intelligence, data mining, natural language processing, computational intelligence and bioinformatics. Toward that end, we collaborate with researchers to invent new approaches and tools that will become the basis for future software products. Development efforts are primarily fueled by data and problems brought to us by our industrial, and academic partners.
Mining Large-Scale Text Repositories
The need to mine large text corpora continues to grow in importance as the amount of information the web is producing continues to expand at exponential rates. It is becoming impossible even for experts to monitor the totality of information that is generated annually in their fields. We are drowning in data. Text mining is prepared to offer some relief.
We are interested in research leading to methods and tools that enable people to understand and organize large amounts of text and to extract the information they need to enhance understanding and foster more effective decision making. We are actively researching unsupervised and supervised learning approaches applied to very large-scale data sets. We are also interested in approaches that extend beyond the standard bag-of-word approaches toward more human like understanding of natural language.
Bioinformatics
Bioinformatics and computational biology researchers at the faculty discover and implement algorithms that facilitate the understanding of biological processes through the application of statistical and machine learning techniques. Because these methods are often compute-intensive, we strive to create algorithms and heuristics that are computationally efficient on serial and parallel computers. Members of the group study the primary (sequence) and tertiary (3-dimensional) structures of protein sequences, as well as gene expression analysis.
Mining Large-Scale Text Repositories
The need to mine large text corpora continues to grow in importance as the amount of information the web is producing continues to expand at exponential rates. It is becoming impossible even for experts to monitor the totality of information that is generated annually in their fields. We are drowning in data. Text mining is prepared to offer some relief.
We are interested in research leading to methods and tools that enable people to understand and organize large amounts of text and to extract the information they need to enhance understanding and foster more effective decision making. We are actively researching unsupervised and supervised learning approaches applied to very large-scale data sets. We are also interested in approaches that extend beyond the standard bag-of-word approaches toward more human like understanding of natural language.
Bioinformatics
Bioinformatics and computational biology researchers at the faculty discover and implement algorithms that facilitate the understanding of biological processes through the application of statistical and machine learning techniques. Because these methods are often compute-intensive, we strive to create algorithms and heuristics that are computationally efficient on serial and parallel computers. Members of the group study the primary (sequence) and tertiary (3-dimensional) structures of protein sequences, as well as gene expression analysis.