Department of Mathematics
PEOPLE: Faculty

Alan Schumitzky

Professor of Mathematics

Contact Information
E-mail: schum@math.usc.edu
Phone: (213) 740-2392
Office: DRB 262

LINKS
Curriculum Vitae
Faculty Profile on Departmental Website
 

Education

  • M.S. , Cornell University
  • Ph.D. , Cornell University
  • B.S. , Washington University

Description of Research

Summary Statement of Research Interests
Professor Shumitzky's research interests are focused on estimation and control theory, applied pharmocokinetics, and complex analysis.

Funded Research

Contracts and Grants Awarded
  • Biomedical Simulations Resource (NIH/NIBIH), D.Z. D'Argenio, V. Marmarelis, $38,000,000, 09/01/2003-08/31/2013  
Other Funded Research
  • NIH Grants, On Sabbatical for the academic year 2007-2008. Was supported by grants listed under "Funded Research". Worked on important projects in "Optimizing Coordinated Drug Therapy" at the USC Medical School. Developed new software for "Analyzing Clinical Trials for Populations of Differing Pharmacogenetic Subjects" at the USC Bioengineering Department. Co-authored three research papers and one book (see "Publications")., $63,000, 2007-2008   

Publications

Book
  • Tatarinova, T., Schumitzky, A. (2008). Bayesian Analysis of Linear and Nonlinear Mixture Models. Springer DM.
Journal Article
  • Bayard, D. S., Schumitzky, A. (2008). Implicit Dual Control Based on Particle Filtering and Forward Dynamic Programming. International Journal on Adaptive Control and Signal Processing.
  • Tatarinova, T., Schumitzky, A. (2007). Kullback-Leibler Markov Chain Monte Carlo – a new algorithm for finite mixture analysis and its application to gene expression data. Journal of Bioinformatics and Computational Biology.
  • Wang, X., Schumitzky, A., D'Argenio, D. Z. (2007). Nonlinear Random Effects Finite Mixture Models: Maximum Likelihood Estimation via the EM Algorithm. Computational Statistics & Data Analysis/Elsevier. Vol. 51 (12), pp. 6614-6623.
  • Wang, X., Schumitzky, A., D'Argenio, D. Z. (2007). Population pharmacokinetic mixture models via maximum a posteriori estimation. Computational Statistics & Data Analysis.

Service to the Profession

Professional Memberships
  • American Mathematical Society, 2006-2007   
Reviewer for Publication
  • See Description, SIAM J. Control and Optimization IEEE Trans. Biomedical Engineering J.Pharmacokinetics and Biopharmaceutics J. Pharmaceutical Sciences J. Therapeutic Drug monitoring Clinical Pharmacokinetics, 2007-2008