Research Interests of Prof. Keshab K. Parhi
Overview
Digital signal processing (DSP) applications are becoming more prevalent in everyday use. Because of this widespread usage and advances in computer technology, the DSP algorithms themselves are being subjected to more demanding specifications. There is a constant need for designing systems with lower power, higher speed, and lower area. Current research in this area is devoted to design of architectures that can operate at very high speed (such as 100 gigabits per second) or with low power for portable and biomedical applications.Another area of research involves use of advanced signal and image processing techniques in classification of biomedical signals. The objective here is to use signal processing for preprocessing and feature extraction and use classifiers for classification. Applications include epilepsy detection and prediction, lung sound signal processing, automated fundus eye scan analysis for diabetic retinopathy and glaucoma screening, and detection of neural disorders. These efforts are in collaborations with various faculty in Biomedical Engineering and Medical School at the University of Minnesota. The work on seizure prediction has been carried out in collaboration with Prof. Tay Netoff of Biomedical Engineering dept. The work on diabetic retinopathy is in collaboration with Dr. Dara Koozekanani of Opthalmology dept. at the University of Minnesota. The work on language understanding of Schophrenic patients from MEG signals is in collaboration with Prof. Massoud Stephane.
Another effort is directed towards synthesizing various signal processing functions by chemical or molecular reactions. These reactions are mapped to DNA strands. The objective here is to synthesize molecular reactions for a specified signal processing function. The emphasis is on design of robust reactions that are (almost) rate-independent. This research is expected to find applications in drug delivery and biosensing. This work is in collaborations with Prof. Marc Riedel.
Current research projects are listed below.
Research Topics
High-Speed/Low-Power VLSI Digital Signal Processing Architectures Hardware Security: PUFs, Reverse Engineering Seizure Prediction from EEG
Automated Fundus Eye Scan Analysis Language Understanding of Schizophrenic Patients Molecular Signal Processing