Mark Huber, Ph.D.

I work in the area of computational probability, designing Monte Carlo methods for applications in statistics and computer science.

Selected Research and Publications

• M. Huber and J. Law, Fast approximation of the permanent for very dense problems, Proc. of Symposium on Discrete Algorithms (2008), pp. 681–689.
• M. Huber, Y. Chen, I. Dinwoodie, A. Dobra, and M. Nicholas, Monte Carlo algorithms for Hardy-Weinberg proportions, Biometrics, vol. 62 no. 1 (March, 2006), pp. 49–53.
• M. L. Huber, Fast perfect sampling from linear extensions, Discrete Mathematics, vol. 306 (2006), pp. 420–428.
• M. Huber, Perfect sampling using bounding chains, The Annals of Applied Probability, vol. 14 no. 2 (August, 2004), pp. 734–753.

Selected Awards and Affiliations

• NSF CAREER award
• NSF Postdoctoral Fellow in Mathematical Sciences NSF CAREER award