Laura Toma Professor of Computer Science.
		Department of Computer Science Bowdoin College 8650 College Station Brunswick, ME 04011		Office: Searles 219 Email: ltoma@bowdoin.edu Phone:

Publications | Student research | Teaching | CV | About me

My research is in the theory and practice of cache-efficient algorithms for large data, and in particular applications that involve large, high-resolution data in Geographic Information Systems (GIS). Together with great students I explore algorithms for fundamental problems on terrains such as visibility, flooding, sea level rise and least-cost-path surfaces. Our goal is to come up with approaches that are resource-efficient (CPU, IO, cache, parallel), are backed by algorithms that we can theoretically prove efficient, and at the same time work well in practice. Ultimately, our goal is to transfer these algorithms into free and open-source software. I am grateful for the past support of NSF award 0728780 (2007-2013) which enabled me to launch this research with students at Bowdoin. Memory-efficient algorithms and parallel algorithms share many techniques and insights which brought me towards exploring high-performance computing using Bowdoin's HPC grid. My DBLP page | Google Scholar page.

I finished my Ph.D in 2003 at Duke University, Department of Computer Science. My thesis advisor was Lars Arge. My dissertation focused on IO-efficient algorithms for modeling flow on very large terrains (terraflow | terrastream), as well algorithms for basic graph problems like IO-efficient breadth-first search and depth-first search, IO-efficient topological sort, IO-efficient minimum spanning trees and IO-efficient shortest paths.

Teaching

Other classes I taught (see teaching for links to course websites): Introduction to Computer Science (1101), Data Structures (2101), Algorithms (2200), Computational geometry (3250), Algorithms for GIS, Spatial data structures, Computing with massive data.

(Some) Projects

• A multi-resolution apprach for visibility [with Lily Smith and Herman Haverkort]
• Faster algorithms for viewsheds and total viewsheds in 2D [with Drew Prescott and Herman Haverkort]
• Sea-level rise for the coast of Maine [with Cory Alini and Eileen Johnson]
• Exploring self-efficacy and its impact in teaching and learning algorithms [with Jan Vahrenhold]
• IO- and cache-efficient algorithms for viewsheds on grid terrains (r.viewshed) [with Bob Wei, Jeremy Fishman and Herman Haverkort]
• Computing multi-source shortest path surfaces on terrains in external memory (r.terracost) [with Tom Hazel and Jan Vahrenhold]
• Algorithms for flow-related indices on terrains in external memory (r.terraflow)