What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Telecommunications
- Algorithm
His primary scientific interests are in Algorithm, Spread spectrum, Code division multiple access, Electronic engineering and Artificial intelligence.
His Algorithm research is multidisciplinary, incorporating perspectives in Signal-to-interference-plus-noise ratio, Autocorrelation matrix, Mathematical optimization and Estimator.
His biological study spans a wide range of topics, including Discrete mathematics, Signature, Simple and Multipath propagation.
The concepts of his Code division multiple access study are interwoven with issues in Upper and lower bounds, Energy, Binary number and Combinatorics.
Dimitris A. Pados focuses mostly in the field of Electronic engineering, narrowing it down to matters related to Transmission and, in some cases, Wireless network, Communication complexity and Signal-to-noise ratio.
His studies in Artificial intelligence integrate themes in fields like Computer vision and Pattern recognition.
His most cited work include:
- An iterative algorithm for the computation of the MVDR filter (195 citations)
- New bounds on the total squared correlation and optimum design of DS-CDMA binary signature sets (158 citations)
- Joint space-time auxiliary-vector filtering for DS/CDMA systems with antenna arrays (154 citations)
What are the main themes of his work throughout his whole career to date?
Dimitris A. Pados mainly investigates Algorithm, Electronic engineering, Code division multiple access, Artificial intelligence and Spread spectrum.
His studies deal with areas such as Signal-to-interference-plus-noise ratio, Autocorrelation matrix, Theoretical computer science and Binary number as well as Algorithm.
His Electronic engineering research integrates issues from Wireless, Linear filter, Multipath propagation, Communication channel and Testbed.
His Multiuser detection study in the realm of Code division multiple access interacts with subjects such as Rake.
His Artificial intelligence research includes elements of Machine learning, Computer vision and Pattern recognition.
His Spread spectrum research incorporates elements of Embedding, Steganography, Antenna array and Bit error rate.
He most often published in these fields:
- Algorithm (34.72%)
- Electronic engineering (19.91%)
- Code division multiple access (17.13%)
What were the highlights of his more recent work (between 2017-2021)?
- Algorithm (34.72%)
- Principal component analysis (12.96%)
- Outlier (7.41%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Algorithm, Principal component analysis, Outlier, Communication channel and Electronic engineering.
He interconnects Subspace topology, Norm, Signal and Antenna array in the investigation of issues within Algorithm.
Optimization problem is closely connected to Data mining in his research, which is encompassed under the umbrella topic of Principal component analysis.
His Outlier research is multidisciplinary, incorporating elements of Matrix, Contrast, Unimodular matrix and Estimation theory.
His work in the fields of Multipath propagation and Channel state information overlaps with other areas such as Chirp.
His Electronic engineering study integrates concerns from other disciplines, such as Signal-to-noise ratio, Waveform, Transmitter and Linear filter.
Between 2017 and 2021, his most popular works were:
- X60: A Programmable Testbed for Wideband 60 GHz WLANs with Phased Arrays (38 citations)
- L1-Norm Principal-Component Analysis of Complex Data (29 citations)
- Comprehending the IoT cyber threat landscape: A data dimensionality reduction technique to infer and characterize Internet-scale IoT probing campaigns (18 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Telecommunications
- Algorithm
Principal component analysis, Data mining, Outlier, Linear subspace and Algorithm are his primary areas of study.
The various areas that Dimitris A. Pados examines in his Principal component analysis study include Tensor and Algebra.
The study incorporates disciplines such as Function, Matrix and Optimization problem in addition to Outlier.
His study in Linear subspace is interdisciplinary in nature, drawing from both Attack time and Norm.
With his scientific publications, his incorporates both Algorithm and Streaming data.
In his research, Testbed is intimately related to Wideband, which falls under the overarching field of Antenna array.
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