What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mathematical analysis
- Algorithm
His scientific interests lie mostly in Artificial intelligence, Computer vision, Algorithm, Acoustics and Microphone.
Artificial intelligence is frequently linked to Pattern recognition in his study.
His research investigates the link between Pattern recognition and topics such as Kernel density estimation that cross with problems in Background subtraction and Kernel.
His Computer vision study integrates concerns from other disciplines, such as Audio signal processing and Computer graphics.
His studies in Algorithm integrate themes in fields like Multivariate kernel density estimation, Variable kernel density estimation, Mathematical optimization, Graphics and Speedup.
His work carried out in the field of Acoustics brings together such families of science as Transfer function, Attenuation and Azimuth.
His most cited work include:
- Background and foreground modeling using nonparametric kernel density estimation for visual surveillance (1358 citations)
- Efficient mean-shift tracking via a new similarity measure (298 citations)
- Fast multiple object tracking via a hierarchical particle filter (292 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial intelligence, Fast multipole method, Mathematical analysis, Computer vision and Algorithm.
Ramani Duraiswami combines subjects such as Audio signal processing, Speech recognition and Pattern recognition with his study of Artificial intelligence.
His research in the fields of Speaker recognition overlaps with other disciplines such as Gaussian process.
His Mathematical analysis research includes elements of Boundary element method and Translation.
His Computer vision study frequently draws connections between related disciplines such as Computer graphics.
His Algorithm research incorporates elements of Kernel density estimation, Mathematical optimization, Kernel and Speedup.
He most often published in these fields:
- Artificial intelligence (27.99%)
- Fast multipole method (19.03%)
- Mathematical analysis (18.28%)
What were the highlights of his more recent work (between 2011-2021)?
- Fast multipole method (19.03%)
- Mathematical analysis (18.28%)
- Algorithm (16.04%)
In recent papers he was focusing on the following fields of study:
Ramani Duraiswami mainly focuses on Fast multipole method, Mathematical analysis, Algorithm, Computation and Boundary element method.
His research in Mathematical analysis focuses on subjects like Boundary, which are connected to Discretization, Singular boundary method and Boundary knot method.
His Algorithm research includes themes of Factorization, Discrete mathematics, Kernel and Frequency domain.
The study incorporates disciplines such as Room acoustics, Quadratic equation, Scattering and Speedup in addition to Computation.
Ramani Duraiswami has researched Boundary element method in several fields, including Helmholtz equation, Boundary value problem, Laplace's equation, Method of images and Surface integral.
Inference is a primary field of his research addressed under Artificial intelligence.
Between 2011 and 2021, his most popular works were:
- Head-Mounted Display Visualizations to Support Sound Awareness for the Deaf and Hard of Hearing (46 citations)
- A hierarchical algorithm for fast Debye summation with applications to small angle scattering. (22 citations)
- A method to compute periodic sums (19 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mathematical analysis
- Algorithm
Ramani Duraiswami mostly deals with Fast multipole method, Artificial intelligence, Gaussian process, Mathematical analysis and Pattern recognition.
His Artificial intelligence research is multidisciplinary, relying on both Audio signal processing and Computer vision.
The Feature research Ramani Duraiswami does as part of his general Computer vision study is frequently linked to other disciplines of science, such as Domain, therefore creating a link between diverse domains of science.
His Mathematical analysis research includes themes of Fast Fourier transform, Computation and Surface.
His Pattern recognition study integrates concerns from other disciplines, such as Channel, Speech recognition, Head-related transfer function and Kernel partial least squares.
As part of one scientific family, Ramani Duraiswami deals mainly with the area of Transfer function, narrowing it down to issues related to the Interpolation, and often Audio signal and Kernel regression.
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