John Hershberger
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John Hershberger
John E. Hershberger (born 1959) is an American computer scientist and software professional, a principal engineer at Mentor Graphics Corporation since 1993. He is known for his research in computational geometry and algorithm engineering. Biography Hershberger did his undergraduate studies at the California Institute of Technology, graduating in 1981. He earned a Ph.D. in Computer science from Stanford University in 1987 under the supervision of Leonidas Guibas. He was a member of the technical staff at the Digital Equipment Corporation Systems Research Center in Palo Alto, California, until 1993, when he joined Mentor Graphics as a software engineer and project leader. He was program committee chair for the 25th ACM Symposium on Computational Geometry in 2009, and program committee co-chair for the Workshop on Algorithm Engineering and Experiments (ALENEX) in 2009. In 2012 he was elected as a fellow of the Association for Computing Machinery "for contributions to ...
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Mentor Graphics
Siemens EDA is a US-based electronic design automation (EDA) multinational corporation for electrical engineering and electronics, headquartered in Wilsonville, Oregon. Founded in 1981 as Mentor Graphics, the company was acquired by Siemens in 2017. The company distributes products that assist in electronic design automation, simulation tools for analog mixed-signal design, VPN solutions, and fluid dynamics and heat transfer tools. The company leveraged Apollo Computer workstations to differentiate itself within the computer-aided engineering (CAE) market with its software and hardware. History Siemens EDA was founded as Mentor Graphics in 1981 by Tom Bruggere, Gerry Langeler, and Dave Moffenbeier, all formerly of Tektronix. The company raised $55 million in funding through an initial public offering in 1984. Mentor initially wrote software that ran only in Apollo workstations. When Mentor entered the CAE market the company had two technical differentiators: the first ...
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Visibility Graph
In computational geometry and robot motion planning, a visibility graph is a graph of intervisible locations, typically for a set of points and obstacles in the Euclidean plane. Each node in the graph represents a point location, and each edge represents a visible connection between them. That is, if the line segment connecting two locations does not pass through any obstacle, an edge is drawn between them in the graph. When the set of locations lies in a line, this can be understood as an ordered series. Visibility graphs have therefore been extended to the realm of time series analysis. Applications Visibility graphs may be used to find Euclidean shortest paths among a set of polygonal obstacles in the plane: the shortest path between two obstacles follows straight line segments except at the vertices of the obstacles, where it may turn, so the Euclidean shortest path is the shortest path in a visibility graph that has as its nodes the start and destination points and the verti ...
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Kinetic Data Structure
A kinetic data structure is a data structure used to track an attribute of a geometric system that is moving continuously. For example, a kinetic convex hull data structure maintains the convex hull of a group of n moving points. The development of kinetic data structures was motivated by computational geometry problems involving physical objects in continuous motion, such as collision or visibility detection in robotics, animation or computer graphics. Overview Kinetic data structures are used on systems where there is a set of values that are changing as a function of time, in a known fashion. So the system has some values, and for each value v, it is known that v=f(t). Kinetic data structures allow queries on a system at the current virtual time t, and two additional operations: *\textrm(t): Advances the system to time t. *\textrm(v,f(t)): Alters the trajectory of value v to f(t), as of the current time. Additional operations may be supported. For example, kinetic data stru ...
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