2020 - Fellow, National Academy of Inventors
2020 - ACM Fellow For contributions to architectures and design tools for signal processing and networking accelerators
2017 - Fellow of the American Association for the Advancement of Science (AAAS)
2003 - IEEE Kiyo Tomiyasu Award "For pioneering contributions to highspeed and low-power digital signal processing architectures for broadband communications systems."
His scientific interests lie mostly in Parallel computing, Algorithm, Very-large-scale integration, Decoding methods and Electronic engineering. His work deals with themes such as Fast Fourier transform and Latency, which intersect with Parallel computing. His research in Algorithm intersects with topics in Digital filter, Upper and lower bounds, Wavelet transform and Filter design.
His Digital filter study integrates concerns from other disciplines, such as Theoretical computer science, Adaptive filter, Interleaving, Signal processing and Finite impulse response. His research integrates issues of Parallel algorithm, Algorithm design, Cryptography and Finite field in his study of Very-large-scale integration. His biological study spans a wide range of topics, including Round-off error, Multiplexer, Adder and Equalization.
Keshab K. Parhi mostly deals with Algorithm, Parallel computing, Electronic engineering, Decoding methods and Very-large-scale integration. In his study, Filter is strongly linked to Digital filter, which falls under the umbrella field of Algorithm. His Parallel computing study incorporates themes from Digital signal processing and Adder.
Digital signal processing is a subfield of Computer hardware that Keshab K. Parhi explores. His Electronic engineering research focuses on Finite impulse response and CMOS. His research investigates the connection with Turbo code and areas like Serial concatenated convolutional codes which intersect with concerns in Error floor.
His primary areas of study are Algorithm, Artificial intelligence, Pattern recognition, Artificial neural network and Computation. His Algorithm research includes elements of Electronic circuit, Theoretical computer science and Coding. The concepts of his Artificial intelligence study are interwoven with issues in Graph and Computer vision.
His study in the fields of Support vector machine, Feature selection and Classifier under the domain of Pattern recognition overlaps with other disciplines such as Major depressive disorder. Computation connects with themes related to Fast Fourier transform in his study. He interconnects Algorithm design and Communication channel in the investigation of issues within Decoding methods.
His main research concerns Artificial intelligence, Pattern recognition, Algorithm, Segmentation and Image segmentation. His Artificial intelligence study combines topics from a wide range of disciplines, such as Infomax, Blind signal separation and Group. The study incorporates disciplines such as False positive rate and Human Connectome Project in addition to Pattern recognition.
His Algorithm research is multidisciplinary, incorporating perspectives in Digital filter, Theoretical computer science, Perceptron and Trigonometric functions. His work in Fast Fourier transform addresses subjects such as Overhead, which are connected to disciplines such as Digital signal processing. His study in Decoding methods is interdisciplinary in nature, drawing from both Sorting, Very-large-scale integration and Critical path method.
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Vlsi Digital Signal Processing Systems: Design And Implementation
Keshab K. Parhi.
High-speed VLSI architectures for the AES algorithm
Xinmiao Zhang;K.K. Parhi.
IEEE Transactions on Very Large Scale Integration Systems (2004)
VLSI architectures for discrete wavelet transforms
K.K. Parhi;T. Nishitani.
IEEE Transactions on Very Large Scale Integration Systems (1993)
VLSI digital signal processing systems
Keshab K. Parhi.
Static rate-optimal scheduling of iterative data-flow programs via optimum unfolding
K.K. Parhi;D.G. Messerschmitt.
IEEE Transactions on Computers (1991)
Pipeline interleaving and parallelism in recursive digital filters. I. Pipelining using scattered look-ahead and decomposition
K.K. Parhi;D.G. Messerschmitt.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1989)
Seizure prediction with spectral power of EEG using cost-sensitive support vector machines
Yun Park;Lan Luo;Keshab K. Parhi;Theoden Netoff.
DREAM: diabetic retinopathy analysis using machine learning.
Sohini Roychowdhury;Dara D. Koozekanani;Keshab K. Parhi.
IEEE Journal of Biomedical and Health Informatics (2014)
Low-Energy Digit-Serial/Parallel Finite Field Multipliers
Leilei Song;Keshab K. Parhi.
application specific systems architectures and processors (1998)
Distributed scheduling of broadcasts in a radio network
R. Ramaswami;K.K. Parhi.
international conference on computer communications (1989)
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