What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Telecommunications
His primary areas of investigation include Communication channel, Electronic engineering, Wireless, Decoding methods and Computer network.
His research on Communication channel concerns the broader Telecommunications.
His Electronic engineering research is multidisciplinary, relying on both Spatial correlation, Channel state information, Delay spread and Dirty paper coding.
The Wireless study combines topics in areas such as Narrowband, Computer engineering, MIMO, Precoding and Transmitter.
His Decoding methods study is related to the wider topic of Algorithm.
His work on Adaptive filter as part of general Algorithm research is frequently linked to Expectation–maximization algorithm, bridging the gap between disciplines.
His most cited work include:
- Space-time codes for high data rate wireless communication: performance criterion and code construction (6988 citations)
- Space-time block codes from orthogonal designs (6705 citations)
- Space-time block coding for wireless communications: performance results (1620 citations)
What are the main themes of his work throughout his whole career to date?
Vahid Tarokh mostly deals with Algorithm, Electronic engineering, Communication channel, Computer network and Wireless.
Decoding methods and Block code are among the areas of Algorithm where he concentrates his study.
His research related to Space–time block code and Linear code might be considered part of Block code.
His Electronic engineering research focuses on Transmitter and how it connects with Antenna diversity and MIMO.
His Communication channel study necessitates a more in-depth grasp of Telecommunications.
His research investigates the link between Computer network and topics such as Wireless network that cross with problems in Base station.
He most often published in these fields:
- Algorithm (26.24%)
- Electronic engineering (18.89%)
- Communication channel (16.50%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (12.72%)
- Algorithm (26.24%)
- Mathematical optimization (8.95%)
In recent papers he was focusing on the following fields of study:
Vahid Tarokh mainly investigates Artificial intelligence, Algorithm, Mathematical optimization, Pattern recognition and Artificial neural network.
His work in Artificial intelligence covers topics such as Machine learning which are related to areas like Computational complexity theory and Parametric statistics.
He combines Algorithm and Momentum in his research.
His research integrates issues of Electricity generation, Rate of convergence, Upper and lower bounds and Convex optimization in his study of Mathematical optimization.
His Pattern recognition research focuses on subjects like Feature, which are linked to Decoding methods.
His work is dedicated to discovering how Decoding methods, Eye movement are connected with Feature vector and other disciplines.
Between 2015 and 2021, his most popular works were:
- Model Selection Techniques: An Overview (72 citations)
- SpiderBoost: A Class of Faster Variance-reduced Algorithms for Nonconvex Optimization. (40 citations)
- SpiderBoost and Momentum: Faster Stochastic Variance Reduction Algorithms (37 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Machine learning
Algorithm, Artificial intelligence, Mathematical optimization, Pattern recognition and Convergence are his primary areas of study.
His Algorithm research is multidisciplinary, incorporating perspectives in Feature, Time series, Spectral density, Feature vector and Nonlinear system.
His Spectral density study incorporates themes from Smoothing, Multitaper, Filter and Decoding methods, Neural decoding.
His biological study spans a wide range of topics, including Machine learning and Computer vision.
His Mathematical optimization study integrates concerns from other disciplines, such as Dual, Measure, Algorithm design, Convex optimization and Upper and lower bounds.
His study looks at the relationship between Computer network and fields such as Wireless, as well as how they intersect with chemical problems.
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