Scott C Schmidler, Assistant Professor of Statistical Science

Office Location:	223D Old Chemistry Bldg.
Office Phone:	919 684-8064
Email Address:
Web Page:	http://www.stat.duke.edu/~scs/

Teaching (Fall 2008):

• STA 140.01, STATISTICAL DECISION ANALYSIS Synopsis

  Old Chem 025, TuTh 02:50 PM-04:05 PM

• STA 214.02, PROBABILITY/STAT MODELS Synopsis

  Old Chem 101, TuTh 11:40 AM-12:55 PM

Education:

PhD	Stanford University	2002
B.A.	University of California, Berkeley	1995

Specialties:

Bayesian Statistics

Research Interests: Bioinformatics, Monte Carlo Methods, Statistical Shape Analysis, Machine Learning, Computational Chemistry

Current Ph.D. Students  

• Ben Cooke  
• Merrill Liechty  
• Ming Liao  
• Jason Cooper  
• Juliette Colinas  

Postdocs Mentored

• Jeff Krause (2002)  

Recent Publications

1. S.C. Schmidler, Discussion of "A Statistical Approach to Modeling Genomic Aberrations in Cancer Cells" by Newton et. al, Bayesian Statistics7 (2003), Oxford University Press
2. Schmidler, S.C., Liu, J.S., Brutlag, D.L., Bayesian segmentation of protein secondary structure, Journal of Computational Biology, vol. 7 no. 1/2 (2000), pp. 233-248
3. Schmidler, S.C., Liu, J.S., Brutlag, D.L., Probabilistic modeling for protein structure prediction, FASEB Journal, vol. 13 no. 7 (1999), pp. A1542
4. Schmidler, S.C., Liu, J.S., Brutlag, D.L., Bayesian protein structure prediction, Case Studies in Bayesian Statistics, vol. 5 (1999), pp. 363-378
5. Wu, T.D., Schmidler, S.C., Hastie, T., Brutlag, D.L., Regression analysis of multiple protein structures, Journal of Computational Biology, vol. 5 no. 3 (1998), pp. 597-607

Recent Grant Support

• Duke CBCBGT Postdoctoral Fellowship Grant, 2001/07.      
• Scientific Computing Research Environments for the Mathematical Sciences, NSF DMS SCREMS program, 2001/07.