Dr. Todd A. LaMaskin       

Assistant Professor

Ph.D., 2009, University of Oregon, Eugene, Oregon

M.S., 1995, University of New Mexico, Albuquerque, New Mexico

B.S., 1992, Radford University, Radford, Virginia

 

Research Interests: Mesozoic tectonics of western North America; Sedimentary Provenance; Calibration of Geologic Time

 

 

 

Todd A. LaMaskin, Ph.D.

Assistant Professor

Department of Geography and Geology
University of North Carolina at Wilmington
601 South College Road
Wilmington, NC 28403-5944

 

(p) 910-962-2655

(f) 910 962-7077

 

lamaskint(AT)uncw.edu

Contact:

Adobe Systems

CV

Basin Analysis Research Group

...Sedimentation, Stratigraphy, Tectonics, Time...

Casey Albritton

B.S. University of South Florida

Research Interests: Stable-isotope and Conodont Biostratigraphy of the Carnian-Norian Boundary Interval (Late Triassic), Wallowa Mountains and Snake River, Oregon

 

 

Wes Massoll

B.S. University of North Carolina Wilmington

Research Interests: Sequence Stratigraphy of the Upper Triassic Martin Bridge Fm., southern Wallowa Mountains, Oregon

 

 

Nick Moore

B.S. University of North Carolina Wilmington

Research Interests: Structure, Stratigraphy, and Provenance of the Upper Jurassic Coon Hollow Formation, Oregon and Idaho

M.S. Students

Department of Geography and Geology

STUDENTS WANTED!!!

 

I am currently seeking a qualified student to begin Fall 2014 with research in the area of:

 

Quantitative Analysis of Detrital Mineral Data

 

We are working on a new method for comparing detrital age distributions. We use bootstrap resampling (n = 100, resampled 1000 times) to generate a statistical range of expected variability for small subsets when drawing a sample of ages from large compiled datasets representing hypothesized “source areas” (a Predictive Range). Comparisons of detrital samples to these resampled distributions allow us to identify the age components in the samples that remain unexplained by drawing from the source distribution, as well as quantification of how large the mismatch is.  Comparisons performed based on this method result in a single-value quantitative measure of similarity that has a statistical basis, and provides an assessment of the age components that are responsible for the mismatch.

 

Beginning fall 2014, I’d like to mentor an M.S.-level graduate student through a project to formalize the statistical algorithm and write a program using the language R.