Jingru Zhang 0002

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EDBT 2026 Demo / reviewers in the wild / expert

dblp:22/10441-2 · DBLP profile ↗

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9ranked-venue papers

0as first author

1since 2021 · last 2021

0000-0003-2586-8271ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 9 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science

2 papers

Computational geometry · 58% Algorithms and data structures · 42%

Topics — the 3 heaviest of 3, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Algorithms and data structures › clustering k-center clustering	0.8	2	2021	An O(nlog n)-Time Algorithm for the k-Center Problem in Trees · SIAM J. Comput. 2021 An O(n log n)-Time Algorithm for the k-Center Problem in Trees · SoCG 2018
Computational geometry › geometric optimization parametric search	0.8	2	2021	An O(nlog n)-Time Algorithm for the k-Center Problem in Trees · SIAM J. Comput. 2021 An O(n log n)-Time Algorithm for the k-Center Problem in Trees · SoCG 2018
Computational geometry geometric optimization	0.3	1	2018	An O(n log n)-Time Algorithm for the k-Center Problem in Trees · SoCG 2018

Methods — techniques the papers use, named apart from their topics

parametric search · 0.3

Year	Publication	Venue	Position
2021	An O(nlog n)-Time Algorithm for the k-Center Problem in Trees abstract We consider a classical $k$-center problem in trees. Let $T$ be a tree of $n$ vertices such that every vertex has a nonnegative weight. The problem is to find $k$ centers on the edges of $T$ such that the maximum weighted distance from all vertices to their closest centers is minimized. Megiddo and Tamir [ SIAM J. Comput., 12 (1983), pp. 751--758] gave an algorithm that can solve the problem in $O(n\log^2 n)$ time by using Cole's parametric search. Since then it has been open for over three decades whether the problem can be solved in $O(n\log n)$ time. In this paper, we present an $O(n\log n)$ time algorithm for the problem and thus settle the open problem affirmatively. Haitao Wang 0001, Jingru Zhang 0002	SIAM J. Comput.	2
2019	Covering Uncertain Points in a Tree Haitao Wang 0001, Jingru Zhang 0002	Algorithmica	2
2018	An O(n log n)-Time Algorithm for the k-Center Problem in Trees abstract We consider a classical k-center problem in trees. Let T be a tree of n vertices and every vertex has a nonnegative weight. The problem is to find k centers on the edges of T such that the maximum weighted distance from all vertices to their closest centers is minimized. Megiddo and Tamir (SIAM J. Comput., 1983) gave an algorithm that can solve the problem in O(n log^2 n) time by using Cole's parametric search. Since then it has been open for over three decades whether the problem can be solved in O(n log n) time. In this paper, we present an O(n log n) time algorithm for the problem and thus settle the open problem affirmatively. Haitao Wang 0001, Jingru Zhang 0002	SoCG	2
2017	Covering Uncertain Points in a Tree Haitao Wang 0001, Jingru Zhang 0002	WADS	2
2017	Computing the Center of Uncertain Points on Tree Networks Haitao Wang 0001, Jingru Zhang 0002	Algorithmica	2
2015	Computing the Center of Uncertain Points on Tree Networks Haitao Wang 0001, Jingru Zhang 0002	WADS	2
2015	One-dimensional k-center on uncertain data Haitao Wang 0001, Jingru Zhang 0002	Theor. Comput. Sci.	2
2014	One-Dimensional k-Center on Uncertain Data Haitao Wang 0001, Jingru Zhang 0002	COCOON	2
2014	Line-Constrained k -Median, k -Means, and k -Center Problems in the Plane Haitao Wang 0001, Jingru Zhang 0002	ISAAC	2