Manfred Minimair, Ph.D.
Dr. Minimair specializes in symbolic computation, data visualization and analysis, and computing for life sciences.
I am a computing scientist and applied mathematician with strong interests in symbolic computation, in data visualization and analysis and in computing for life sciences. I teach data visualization, computer graphics, data analysis and various topics in applied computing and mathematics.
I am studying how to use the structures of large-scale composed mathematical models from engineering and science in order to efficiently simplify the underlying systems of polynomial equations. In another line of research, I am investigating how to efficiently determine the consistency of parametric systems of polynomial equations.
I have been involved in developing pioneering certificate programs in Data Visualization and Analysis at Seton Hall University. I conducted a pilot project for the New Jersey State Police, developing an online visualization of data from a survey on gang activities in New Jersey. One of my papers on biological data investigates and visualizes data on culturing spermatogenic cysts of fruit flies. In 2010, I supervised the research project of the Clare Boothe Luce scholar Juliana Newman. The project was on analyzing and visualizing data on the environmental biology of the Kearny Marsh near New York City.
- Ph.D., North Carolina State University, Raleigh, NC, 2001
- Dipl.-Ing. (M.S. equivalent), Johannes Kepler University, Linz, Austria, 1997
- Director of the undergraduate and graduate certificate programs in Data Visualization and Analysis
- Study Abroad and Internship Advisor for Computer Science
- Adviser of the German club
- NSF RUI grant (2004-2007) on resultant techniques for composed polynomials
- Researcher of the Year 2004/05: Awarded by the Provost and the College of Arts and Science
- The effects of glutathione, insulin and oxidative stress on cultured spermatogenic cysts
Spermatogenesis, 1(2), 159- 171,
- Multivariate Resultants in Bernstein Basis (Book Chapter)
In T. Sturm and C. Zengler (Eds.), "Automated Deduction in Geometry," Springer Verlag, 60- 85,
- Cayley-Dixon Projection Operator for Multi-Univariate Composed Polynomials
Journal of Symbolic Computation, 44(8), 972- 999,
- Basis-Indepedent Polynomial Division Algorithm Applied to Division in Lagrange and Bernstein Basis
Asian Symposium on Computer Mathematics, ASCM, LNAI 5081, ISBN: 978-3-540-87826-1, 72-87,
- Resultants of Skewly Composed Polynomials
ISSAC MMVI, International Symposium on Symbolic and Algebraic Computation, Association of Computing Machinery (ACM), ISBN: 1-59593-276-3, 228- 233,
- Resultants of Partially Composed Polynomials
Journal of Symbolic Computation, 41(5), 591- 602,
- Cayley-Dixon Resultant Matrices of Multi-Univariate Composed Polynomials
CASC 2005, Computer Algebra in Scientific Computing, Springer Verlag, Lecture Notes in Computer Science 3718, 125- 137,
- Solving Polynomial Equations for Chemical Problems Using Groebner Bases
Molecular Physics, 102(23- 24), 2521- 2535,