Nikki Meshkat

Ph.D. in Mathematics, UCLA

Office: Math Sciences 6322

Email me at nmeshkat "at" math.ucla.edu

Courses Taught

As Instructor:

Math 32B: Calculus of Several Variables

Math 142: Mathematical Modeling

Math 31B: Integration and Infinite Series

As Teaching Assistant:

Math 1: Precalculus

Math 3A, 3B: Calculus for Life Sciences Students

Math 3C: Probability for Life Sciences Students

Math 31A: Differential and Integral Calculus

Math 32A: Calculus of Several Variables

Math 33A: Linear Algebra and Applications

Math 33B: Differential Equations

Math 106: History of Mathematics

Math 115A: Linear Algebra

Math 135: Ordinary Differential Equations

Math 151A, 151B: Applied Numerical Methods

Math 170A: Probability Theory

Research

I study parameter identifiability, which concerns finding which unknown parameters of a model can be quantified from given input-output data. Many biological models are unidentifiable, which means that the parameters can take on an infinite number of values, yet yield the same input-output data. The goal is then to find identifiable parameter combinations to reparameterize the model. My work has been focused on the differential algebra approach to identifiability and on an algorithm I wrote for finding identifiable parameter combinations using Groebner Bases.

Publications:

N. Meshkat, M. Eisenberg, and J. J. DiStefano III, An algorithm for finding globally identifiable parameter combinations of nonlinear ODE models using Groebner Bases, Math. Biosci. 222 (2009) 61-72. PDF

N. Meshkat, C. R. Anderson, and J. J. DiStefano III, Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations, Submitted to Math. Biosci. (Accepted for publication).