Faculty Profile - Dr. Sheela Ramanna
Dr. Sheela Ramanna of the MSc in Applied Computer Science program talks about her upcoming research projects
What are you working on right now with your graduate students?
My graduate students and I are working on tolerance forms of granular computing which admits different degrees of indiscernibility. This research on tolerance relations is motivated from a classical study of the topology of the brain by Zeeman. One area is automated text categorization of data derived from the web. Data is abundant on the web, but it is unlabeled. A second area is that of audio signals classification and retrieval of speech and music elements.
What interested you about this area?
Humans are able to make inferences with vague, imprecise or incomplete information. Designing intelligent systems capable of processing such information has always been a fascination for me. In particular, the field of machine learning offers tremendous theoretical as well as practical challenges and opportunities. I enjoy using mathematics, computer science and engineering in my research.
What are the practical implications of this work?
Reasoning with granular models is particularly useful when information is incomplete or imprecise in such areas as image analysis, audio signal classification and text categorization. We have also demonstrated that this particular form of set-theoretic methods lend themselves to parallel processing.
How have your students assisted you or contributed in your research?
My graduate students are very helpful in implementing different algorithms and experimenting with different data. They also contribute towards enhancing the theoretical framework.
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