The algorithms group at UMIACS is a very active group with expertise spanning a wide variety of specialties including parallel algorithms, combinatorial optimization, and computational geometry.

Experimental Parallel Algorithmics:

A fundamental problem in parallel computing is to design high-level, architecture independent, algorithms that execute efficiently on general purpose parallel machines. The purpose of this project is to advance our understanding of the main factors required for designing practical parallel algorithms and to develop techniques and data sets for experimentally validating the results. As a byproduct, we are developing portable parallel programs and data sets for a number of specific important problems arising in combinatorial computing and image processing.

Parallel Algorithms:

A rich parallel algorithmic theory that includes many paradigms and techniques is being developed with the active participation of UMIACS researchers.

Computational Geometry:

UMIACS has an active research program on the design and analysis of algorithms for problems of a geometric nature. Specific problems recently addressed include nearest neighbor searching, computation of statistically robust eliminators for line and curve fitting, ray shooting, and spanners with low diameter.

Graph Algorithms and Combinatorial Optimization:

This activity involves a broad range of issues arising in transportation, network design, optimization and VSLI layout.

Algorithmic Aspects in Vision and Robotics:

UMIACS researchers are developing new techniques to handle a number of selected problems arising in image processing, pattern matching in a digitized image, and robot navigation and motion planning in general discretized space.

---

Back to the Research Page

---