Abstract:

DNA computing is of interest as it can enable monitoring rates of protein molecules, and in generating trigger signals to activate or inhibit pathways. Other applications include drug delivery and molecular therapy. In the first part of the talk, I will describe implementation of simple signal processing functions such as digital filters and fast Fourier transforms using molecular computing in general and DNA strands in particular. In the second part of the talk, I will describe design of molecular reactions for intelligent computing. The goal is to design a machine learning system that can monitor one or more proteins, compute some features to be used by a classifier that computes a decision variable that is converted to either a hard or soft decision. The classifier output triggers an action such as whether to deliver a drug or not using a hard decision, or to deliver a variable amount of drug in case of soft decision. A new fractional coding approach, inspired from stochastic logic based computing, is used to realize molecular reactions for machine learning functions such as artificial neural networks. These reactions can be mapped to DNA-strand displacement reactions.

Biography:

Keshab K. Parhi received the B.Tech. degree from the Indian Institute of Technology (IIT), Kharagpur, in 1982; the M.S.E.E. degree from the University of Pennsylvania, Philadelphia, in 1984; and the Ph.D. degree from the University of California, Berkeley, in 1988. He has been with the University of Minnesota, Minneapolis, since 1988, where he is currently Distinguished McKnight University Professor and Edgar F. Johnson Professor in the Department of Electrical and Computer Engineering. He has published 600 papers, is the inventor of 29 patents, and has authored the textbook VLSI Digital Signal Processing Systems (Wiley, 1999) and coedited the reference book Digital Signal Processing for Multimedia Systems (Marcel Dekker, 1999). Dr. Parhi is widely recognized for his work on high-level transformations of iterative data-flow computations, for developing a formal theory of computing for design of digital signal processing systems, and for his contributions to multi-gigabit Ethernet systems on copper and fiber and for backplanes. His current research addresses VLSI architecture design of signal processing, communications and biomedical systems, error control coders and cryptography architectures, high-speed transceivers, stochastic computing, hardware security, and molecular computing. He is also currently working on intelligent classification of biomedical signals and images, for applications such as seizure prediction and detection, schizophrenia classification, biomarkers for mental disorders, brain connectivity, and diabetic retinopathy screening. Dr. Parhi is the recipient of numerous awards including the 2012 Charles A. Desoer Technical Achievement award from the IEEE Circuits and Systems Society, the 2004 F. E. Terman award from the American Society of Engineering Education, the 2003 IEEE Kiyo Tomiyasu Technical Field Award, the 2001 IEEE W. R. G. Baker prize paper award, and a Golden Jubilee medal from the IEEE Circuits and Systems Society in 2000. He is a Fellow of IEEE (1996). He served as the Editor-in-Chief of the IEEE Trans. Circuits and Systems, Part I during 2004-2005 and as an elected member of the Board of Governors of the IEEE Circuits and Systems society from 2005 to 2007.