What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Algorithm
Michael Kazhdan mostly deals with Topology, Algorithm, Artificial intelligence, Similarity and Fourier transform.
The concepts of his Topology study are interwoven with issues in Optimal alignment, Curse of dimensionality, Coordinate system, Shape matching and Invariant.
His Algorithm research incorporates themes from Linear system, Mathematical optimization and Boundary.
His Mathematical optimization research includes elements of Space partitioning, Hierarchy and Surface reconstruction.
His Artificial intelligence study combines topics in areas such as Surface and Polygon mesh.
His study in Similarity is interdisciplinary in nature, drawing from both Information retrieval and Blossom algorithm.
His most cited work include:
- Poisson surface reconstruction (1790 citations)
- The Princeton Shape Benchmark (1257 citations)
- Rotation invariant spherical harmonic representation of 3D shape descriptors (1108 citations)
What are the main themes of his work throughout his whole career to date?
Michael Kazhdan spends much of his time researching Artificial intelligence, Computer vision, Algorithm, Surface and Radiation treatment planning.
His research links Machine learning with Artificial intelligence.
Michael Kazhdan has included themes like Linear system, Poisson's equation, Geometry processing, Solver and Topology in his Algorithm study.
His Linear system research is multidisciplinary, incorporating elements of Mathematical optimization and Surface reconstruction.
His studies in Surface integrate themes in fields like Flow, Polygon mesh, Mathematical analysis and Position.
His Radiation treatment planning study incorporates themes from Histogram and Medical physics.
He most often published in these fields:
- Artificial intelligence (31.11%)
- Computer vision (23.33%)
- Algorithm (23.33%)
What were the highlights of his more recent work (between 2012-2021)?
- Algorithm (23.33%)
- Artificial intelligence (31.11%)
- Computer vision (23.33%)
In recent papers he was focusing on the following fields of study:
Michael Kazhdan mainly investigates Algorithm, Artificial intelligence, Computer vision, Geometry processing and Convolution.
His Algorithm research includes themes of Poisson's equation, Linear system, Filter and Interpolation.
His study in the field of Spline interpolation is also linked to topics like Poisson distribution and Screened Poisson equation.
His work on Feature detection, Tracking and Color correction as part of general Artificial intelligence research is frequently linked to Domain, bridging the gap between disciplines.
His research in Computer vision tackles topics such as Polygon mesh which are related to areas like Image processing.
His Geometry processing research focuses on subjects like Solver, which are linked to Topology and System of linear equations.
Between 2012 and 2021, his most popular works were:
- Screened poisson surface reconstruction (915 citations)
- A Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster. (339 citations)
- The open connectome project data cluster: scalable analysis and vision for high-throughput neuroscience (39 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
His primary scientific interests are in Postsynaptic potential, Neuroscience, Mushroom bodies, Electron microscope and Data cluster.
Postsynaptic potential is connected with Cell type, Olfaction, Biological neural network, Connectomics and Entire brain in his study.
His studies link Anatomy with Neuroscience.
His Data cluster research incorporates elements of Throughput, Spatial database, NoSQL, Distributed computing and Web service.
His Throughput research includes elements of Scalability, Data-intensive computing, Disk array and Data set.
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