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Michael T. Goodrich

Researcher at University of California, Irvine

Publications -  445
Citations -  14652

Michael T. Goodrich is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Planar graph & Time complexity. The author has an hindex of 61, co-authored 430 publications receiving 14045 citations. Previous affiliations of Michael T. Goodrich include New York University & Technion – Israel Institute of Technology.

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Computing the arrangement of curve segments: Divide-and-conquer algorithms via sampling

TL;DR: Two deterministic algorithms for constructing the arrangement determined by a set of (algebraic) curve segments in the plane use a divide-and-conquer approach based on derandomized geometric sampling and achieve the optimal running time O(n log n + k), where n is the number of segments and k is thenumber of intersections.
Proceedings ArticleDOI

Parallel external memory graph algorithms

TL;DR: All the solutions on a P-processor PEM model provide an optimal speedup of Θ(P) in parallel I/O complexity and parallel computation time, compared to the single-processor external memory counterparts.
Journal ArticleDOI

Finding the convex hull of a sorted point set in parallel

TL;DR: A parallel algorithm for finding the convex hull of a sorted planar point set using the use of a parallel data structure which is called the hull tree, which is optimal in O(log n) time.
Book ChapterDOI

Range Searching Over Tree Cross Products

TL;DR: This work introduces the tree cross-product problem, which abstracts a data structure common to applications in graph visualization, string matching, and software analysis, and design solutions with a variety of tradeoffs, yielding improvements and new results for these applications.
Journal ArticleDOI

Biased Skip Lists

TL;DR: This work designs a variation of skip lists that performs well for generally biased access sequences and presents two instantiations of biased skip lists, one of which achieves this bound in the worst case, the other in the expected case.