PI Spotlight: Dr. Vijay Raghavan

Vijay V. Raghavan, Ph. D obtained his B.S. in Mechanical Engineering from the Indian Institute of Technology in Madras, India. After moving to Canada, he earned his Master’s in Business Administration from McMaster University in Hamilton and his doctorate in Computing Science from the University of Alberta in Edmonton.

Dr. Raghavan's very first area of research, Information Retrieval, was goaled to help people find information that actually satisfied their information need through statistical techniques that helped in indexing and searching unstructured text. These days, Dr. Raghavan's research covers all aspects of dealing with structured, semi-structured and unstructured data. He also studies automated techniques for data preprocessing like cleaning, transformations, data integration, and data analysis as well as deriving knowledge and data visualization.

A relatively new research interest for Dr. Raghavan is Visual Analytics, which has been brought about by an Operation and Management research project currently being funded by the National Science Foundation through the Center for Visual and Decision Informatics. However, this isn't the only project that Dr. Raghavan has funded here at the University. The titles of some of Dr. Raghavan’s other funded research projects are Novel, Alignment-Free Representation for Understanding Protein-Protein Relationships and Hypothesis Discover from Biomedical Literature. He is also involved in major research on infrastructure development for the University's Center for Visual and Decision Informatics and is active in the co-direction of the University's LS-LAMP program with Dr. DeCuir.

Not only does he focus on his own research, but Dr. Raghavan is also very passionate about the research interests of his students, which he says often serves as inspiration for his own research. With between eight and ten doctoral students under his direction, Dr. Raghavan guides his students in finding important problems within their interest areas and assists them in coming up with solutions to those problems. These interest areas span over a wide area of topics such as Social Media Analysis, the development of a medical imaging-based Alzheimer's disease marker, the enhancement of semantic technologies, the hypotheses generation to building recommender systems, and Protein 3-D structure analysis.

In the future, Dr. Raghavan plans to study some of the Big Data issues of today. In particular, he is interested in helping organizations exploit their data and create more value for their shareholders and clients.