Mark Huber, Assistant Professor of Mathematics and Statistics

Contact Info:

Office Location:	215 Physics Bldg
Office Phone:	(919) 660-6970
Email Address:
Web Page:	http://www.math.duke.edu/~mhuber

Teaching (Fall 2008):

• MATH 288.01, TOPICS IN PROBABILITY Synopsis

  Physics 205, TuTh 01:15 PM-02:30 PM

Education:

Doctorate of Philosophy Cornell University 1999
BS Harvey Mudd College 1994
B.S. in Mathematics at Harvey Mudd College, 1994
Masters in Operations Research at Cornell University, 1997
Ph.D. in Operations Research at Cornell University, 1999

Specialties:

Probability
Applied Math

Research Interests: Monte Carlo simulation and stochastic computation

Current projects: approximating the permanent, studying speed of covergence for parallel tempering, Markov chains for generating regular graphs, restoration of grayscale images, applications of the Randomness Recycler

For high dimensional problems, Monte Carlo samples are a fast way to estimate integrals without the need to construct grids with exponentially many points. Within Monte Carlo simulation, my primary area of expertise is perfect sampling, algorithms that generate random variates from a variety of distributions that are interesting from either a theoretical or pratical point of view.

Keywords:

perfect simulation • Monte Carlo algorithms • mixing times

Curriculum Vitae

Current Ph.D. Students  

• Wai (Jenny) J. Law  

Postdocs Mentored

• Ruriko Yoshida (August 26, 2004 - May 31, 2006)  

Recent Publications   (More Publications)

1. M. Huber, Perfect simulation for image restoration, Stochastic Models, vol. 23 no. 3 (August, 2007), pp. 475--487, Taylor and Francis  [abs]
2. M. Huber, Perfect simulation with exponential tails, Random Structures and Algorithms (Accepted, June, 2007)  [abs]
3. D. B. Woodard, S. Schmidler, and M. Huber, Conditions for Torpid Mixing of Parallel and Simulated Tempering on Multimodal Distributions, Stochastic Processes and their Applications (Submitted, 2007)
4. D. B. Woodard, S. C. Schmidler and M. Huber, Conditions for Rapid Mixing of Parallel and Simulated Tempering on Multimodal Distributions, Annals of Applied Probability (Submitted, 2007)
5. M. Huber and J. Law, Fast approximation of the permanent for very dense problems, in SODA 2008 (Accepted, 2007)  [abs]

Recent Grant Support

• Perfect sampling for high dimensional integration, NSF, CAREER: DMS-05-48153, 2006/01-2007/12.