2014 - Fellow, National Academy of Inventors
2013 - Member of the National Academy of Engineering For contributions to the theory and practice of statistical signal processing.
2005 - Fellow of the American Association for the Advancement of Science (AAAS)
1994 - IEEE Fellow For contributions to nonlinear filtering and model-based signal processing.
Algorithm, Signal processing, Artificial intelligence, Distributed algorithm and Distributed computing are his primary areas of study. His Algorithm study combines topics from a wide range of disciplines, such as Stochastic approximation, Markov process, Kalman filter, Control theory and Stochastic process. His study focuses on the intersection of Signal processing and fields such as Digital signal processing with connections in the field of Wavelet.
His Artificial intelligence research incorporates elements of Clutter, Computer vision and Pattern recognition. His studies in Distributed algorithm integrate themes in fields like Gossip protocol, Wireless sensor network, Network topology, Mathematical optimization and Rate of convergence. His work deals with themes such as Quality of service and Energy, which intersect with Distributed computing.
His primary scientific interests are in Algorithm, Artificial intelligence, Mathematical optimization, Computer vision and Signal processing. Jose M. F. Moura works in the field of Algorithm, focusing on Estimation theory in particular. The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Pattern recognition.
His studies deal with areas such as Distributed algorithm, Convergence, Rate of convergence and Applied mathematics as well as Mathematical optimization. Computer vision is frequently linked to Clutter in his study. His Signal processing study is concerned with the larger field of Signal.
His primary areas of investigation include Artificial intelligence, Graph, Algorithm, Deep learning and Mathematical optimization. The various areas that Jose M. F. Moura examines in his Artificial intelligence study include Natural language processing, Machine learning and Pattern recognition. His Graph study also includes
His Algorithm research focuses on Estimation theory in particular. His Mathematical optimization research incorporates themes from Function, Convergence and Maxima and minima. He works mostly in the field of Maxima and minima, limiting it down to topics relating to Gaussian noise and, in certain cases, Distributed algorithm, as a part of the same area of interest.
His scientific interests lie mostly in Artificial intelligence, Artificial neural network, Sequence, Natural language processing and Discriminative model. His research in Artificial intelligence intersects with topics in Machine learning, Computer vision and Pattern recognition. The study incorporates disciplines such as Cyber-physical system, State, Natural language and Human–computer interaction in addition to Sequence.
In the field of Natural language processing, his study on Semantic similarity overlaps with subjects such as Context. His study looks at the relationship between Distributed computing and topics such as Linear system, which overlap with Wireless sensor network. His Wireless sensor network study which covers Information retrieval that intersects with Signal processing and Graph.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Discrete Signal Processing on Graphs
A. Sandryhaila;J. M. F. Moura.
IEEE Transactions on Signal Processing (2013)
SPIRAL: Code Generation for DSP Transforms
M. Puschel;J.M.F. Moura;J.R. Johnson;D. Padua.
Proceedings of the IEEE (2005)
Gossip Algorithms for Distributed Signal Processing
Alexandros G Dimakis;Soummya Kar;José M F Moura;Michael G Rabbat.
Proceedings of the IEEE (2010)
Distributed Consensus Algorithms in Sensor Networks With Imperfect Communication: Link Failures and Channel Noise
S. Kar;J.M.F. Moura.
IEEE Transactions on Signal Processing (2009)
Graph Signal Processing: Overview, Challenges, and Applications
Antonio Ortega;Pascal Frossard;Jelena Kovacevic;Jose M. F. Moura.
Proceedings of the IEEE (2018)
Big Data Analysis with Signal Processing on Graphs: Representation and processing of massive data sets with irregular structure
Aliaksei Sandryhaila;Jose M.F. Moura.
IEEE Signal Processing Magazine (2014)
Big Data Analysis with Signal Processing on Graphs
Aliaksei Sandryhaila;José M. F. Moura.
IEEE Signal Processing Magazine (2014)
Discrete Signal Processing on Graphs: Frequency Analysis
Aliaksei Sandryhaila;Jose M. F. Moura.
IEEE Transactions on Signal Processing (2014)
Abhishek Das;Satwik Kottur;Khushi Gupta;Avi Singh.
computer vision and pattern recognition (2017)
Distributing the Kalman Filter for Large-Scale Systems
U.A. Khan;J.M.F. Moura.
IEEE Transactions on Signal Processing (2008)
Profile was last updated on December 6th, 2021.
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