What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Geometry
- Algorithm
Ying He mainly investigates Solid modeling, Topology, Algorithm, Artificial intelligence and Polycube.
His Solid modeling study combines topics in areas such as Visualization, Distance transform and Spline.
As a part of the same scientific study, he usually deals with the Topology, concentrating on Curve fitting and frequently concerns with Gravitational singularity and Parametrization.
The Algorithm study combines topics in areas such as Geometric primitive, Solid geometry, Computer graphics and Geodesic.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning, Computer vision and Pattern recognition.
Ying He interconnects Divide and conquer algorithms, Hexahedron and Bijection in the investigation of issues within Polycube.
His most cited work include:
- Harmonic volumetric mapping for solid modeling applications (105 citations)
- A Review of the Functional and Anatomical Default Mode Network in Schizophrenia. (101 citations)
- Manifold SLIC: A Fast Method to Compute Content-Sensitive Superpixels (79 citations)
What are the main themes of his work throughout his whole career to date?
Ying He mainly focuses on Artificial intelligence, Algorithm, Computer vision, Topology and Polygon mesh.
Much of his study explores Artificial intelligence relationship to Pattern recognition.
The concepts of his Algorithm study are interwoven with issues in Point cloud, Surface and Solid modeling.
His Solid modeling research is multidisciplinary, relying on both Polycube and Spline.
Computer vision is closely attributed to Computer graphics in his work.
His research investigates the connection between Polygon mesh and topics such as Geodesic that intersect with problems in Time complexity and Voronoi diagram.
He most often published in these fields:
- Artificial intelligence (24.77%)
- Algorithm (22.36%)
- Computer vision (15.71%)
What were the highlights of his more recent work (between 2019-2021)?
- Algorithm (22.36%)
- Artificial intelligence (24.77%)
- Point cloud (5.74%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Algorithm, Artificial intelligence, Point cloud, Point and Polygon mesh.
Ying He works in the field of Algorithm, namely Computation.
His work carried out in the field of Artificial intelligence brings together such families of science as Distraction, Computer vision and Pattern recognition.
His Computer vision study integrates concerns from other disciplines, such as Grid and Projection.
In his study, which falls under the umbrella issue of Pattern recognition, Topology, Net and Graph is strongly linked to Vertex.
His studies in Polygon mesh integrate themes in fields like Smoothing, Vertex and Geodesic.
Between 2019 and 2021, his most popular works were:
- Alteration of the gut microbiome in first-episode drug-naïve and chronic medicated schizophrenia correlate with regional brain volumes (8 citations)
- Parallel and Scalable Heat Methods for Geodesic Distance Computation (8 citations)
- On the Security Risks of the Blockchain (7 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Geometry
- Algorithm
His main research concerns Algorithm, Polygon mesh, Point cloud, Geodesic and Point.
His research integrates issues of Smoothing, Solver and Artificial intelligence in his study of Algorithm.
The various areas that he examines in his Artificial intelligence study include Iterative method, Computation and Code.
His Polygon mesh research includes themes of Discrete mathematics, Time complexity and Vertex.
He has included themes like Distance transform and Quadratic programming in his Geodesic study.
His research on Point also deals with topics like
- Matrix that intertwine with fields like Jacobian matrix and determinant, Surface, Feature vector and Tangent space,
- Upsampling that connect with fields like Surface reconstruction, Approximation algorithm and Low-rank approximation,
- Position, which have a strong connection to Noise.
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