The investigator studies combinatorial, probabilistic and analytic concepts, theorems and algorithms for analyzing stochastic models coming from social choice theory, from the theory of biological networks and from theoretical computer science.

The proposal aims to provide rigorous models answering questions from molecular biology, from the theory of voting and from theoretical computer science. Some of the biologically motivated problems we study include: Which biological networks can be reconstructed from genetic data? How can they be efficiently reconstructed? What genealogical relations between individuals can be recovered from their genomes in an efficient manner? In the theory of voting the questions we address focus on minimizing the ability to manipulate voting and ranking methods and to increase their robustness against voting errors.

Agency
National Science Foundation (NSF)
Institute
Division of Mathematical Sciences (DMS)
Application #
1106999
Program Officer
Tomek Bartoszynski
Project Start
Project End
Budget Start
2011-09-15
Budget End
2014-08-31
Support Year
Fiscal Year
2011
Total Cost
$329,804
Indirect Cost
Name
University of California Berkeley
Department
Type
DUNS #
City
Berkeley
State
CA
Country
United States
Zip Code
94704