Who I am: I am a Professor of Mathematics at Boston College. Although my formal training was in pure mathematics and computer science, I have worked in the area of statistics since I was an NCI (National Cancer Institute) Postdoctoral Fellow in Biostatistics at Memorial Sloan-Kettering Cancer Center in New York. While at Sloan-Kettering, I worked with a multidisciplinary team of researchers on statistical issues in the analysis of CT (computed tomography) brain scans in cancer patients. Since then, I have collaborated with medical and environmental scientists, and with research statisticians, on various projects.
My research has included the design and implementation of computer-intensive statistical methods for the analysis of discrete data; statistical modeling and analyses of clinical data on treatments for premature infants; and statistical modeling and analyses of data from fisheries studies of important shellfish populations in the northeast (the softshell clam, Mya arenaria, and the oyster, Crossostrea virginica) and of an invasive species to the northeast (the Asian shore crab, Hemigrapsus sanguineus).
I recently began collaborating with a team of researchers at Boston College interested in forecasting earthquakes. A collection of papers, including a paper written by our team, on issues in developing appropriate likelihood models for forecasting earthquakes in southern California can be obtained here.
My current interests include statistical issues in the analysis of data from large-scale genetics studies. An important challenge in this area of research is dealing with the size and complexity of the data gathered in such studies. Although the fundamental theory of statistics was developed in the first half of the twentieth century (and extended in the second half of the century to include non-classical situations), the methods of twentieth century statistics were not designed to handle the size and complexity of data sets routinely gathered today in fields such as genetics, geophysics and astrophysics. Thus, innovative analysis methods will be required to meet the challenges of twenty-first century science. (An article from the September 2007 issue of Amstat News on the future of statistics, written by Stanford University Professor Brad Efron, can be obtained here.)
Curriculum development related to statistics: I have worked on several curriculum development projects related to statistics. The goal of the first project was to introduce modern statistical methods to students in mathematical statistics courses; information on the text developed from this project can be obtained here. The goal of the second project was to develop a course in applied mathematics for doctoral candidates in the behavioral and social sciences and in the professional schools interested in pursuing the Graduate Statistics Minor; information on this course can be obtained here. My most recent project involved developing a mathematics core course for nursing majors designed to introduce the principles of probability and statistics, with applications in the health sciences; information on this course can be obtained here.
Course web pages: The courses I have taught in recent years include Principles of Statistics for the Health Sciences (MT180), Multivariable Calculus (MT202), Linear Algebra (MT210), Mathematics for Management Science (MT235), Probability Theory (MT426), Mathematical Statistics (MT427), Applied Mathematics for Statistics (MT580), Topics in Modern Statistics (MT853).
Curriculum vitae: A curriculum vitae can be obtained here.