Kenneth M. Levasseur

Kenneth M. Levasseur is a Professor in the Department of Mathematics & Statistics at the University of Massachusetts Lowell, within the Kennedy College of Sciences. His academic career spans over four decades with significant contributions to discrete mathematics, abstract algebra, and computational mathematics.

Education:

• Ph.D. in Mathematics (1980), University of Rhode Island (Dissertation: Best Approximation with Respect to Two Objectives)
• MS in Mathematics (1973), University of Rhode Island
• BA in Mathematics (1971), St. Anselm College

Levasseur's research primarily focuses on discrete mathematics and abstract algebra, with special emphasis on implementing algorithms and computational approaches using Mathematica. His work extends into data visualization and computational number theory. He has developed numerous interactive resources for teaching abstract algebra concepts.

His publication history reveals a strong trajectory from theoretical approximation theory in the early 1980s toward discrete structures and educational applications of computational mathematics. Recent work (2019-2023) centers on applied discrete structures, Markov chains, and combinatorial games, demonstrating his sustained engagement with both theoretical and applied aspects of discrete mathematics.

Awards:

• Mathematical Sciences Teaching Excellence Award (2008)
• Mathematical Sciences Teaching Excellence Award (2002)

Professor Levasseur has secured numerous research grants, particularly in mathematics education. Notable projects include the UTeach replication grant (2012), ARRAS - U-TEACH UMass Lowell (2011), and multiple NSF-funded Focus on Mathematics initiatives (2009-2010). His grant portfolio reflects a strong commitment to improving mathematics education at multiple levels.

He co-authored the textbook "Applied Discrete Structures" with his late colleague Al Doerr and has developed significant Mathematica resources including "Exploring Abstract Algebra with Mathematica" (EAAM) and a Baseball package for analyzing Retrosheet data. His work bridges theoretical mathematics with practical computational applications and educational tools.