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Yanping Ma - Loyola Marymount University. Los Angeles, CA, US

Yanping Ma Yanping Ma

Associate Professor of Mathematics | Loyola Marymount University

Los Angeles, CA, UNITED STATES

Seaver College of Science and Engineering

Biography

Contact:
Phone: 310.338.5108
Email: Yanping.Ma@lmu.edu
Office: University Hall 2775

Dr. Ma's interests are in applied mathematics, especially in biomathematics. Dr. Ma received her Ph.D. in applied mathematics with a minor in statistics from Pennsylvania State University in 2011 and her B.S. from the University of Science and Technology of China in 2006. She joined the LMU faculty in 2011.

Education (3)

The Pennsylvania State University: Ph.D., Applied Mathematics 2011

The Pennsylvania State University: M.A., Mathematics 2009

University of Science and Technology of China: B.Sc., Mathmatics and Applied Mathematics 2006

Areas of Expertise (13)

Statistics Applied Mathematics Mathematics Mathematical Modeling Simulations Latex Matlab Mathematica Scientific Computing Numerical Analysis Modeling Differential Equations Data Analysis

Industry Expertise (2)

Education/Learning Research

Languages (2)

  • English
  • Chinese

Courses (13)

MATH 120 PreCalculus

Fall 2011

MATH 122 Calculus I for Life Science

Spring 2019, Spring 2018, Spring 2017, Fall 2016, Spring 2016, Fall 2015, Spring 2014, Fall 2013, Fall 2012, Spring 2012

MATH 131 Calculus I

Fall 2017, Summer 2012

MATH 234 Multivariable Calculus

Spring 2016

MATH 245 Ordinary Differential Equations

Spring 2018, Spring 2013

MATH 321 Real Variables

Fall 2016, Fall 2015

MATH 355 Methods of Applied Mathematics

Fall 2018, Summer 2014(Bonn, Germany)

MATH 357 Complex Variables

Fall 2018

MATH 360 Introduction to Probability and Statistics

Spring 2017

MATH 398 Real Variables I ( four unit Pilot)

Fall 2015

MATH/BIOL/HHSC 398 Ecology of Homelessness

Spring 2014

MATH 495 Mathematical Modeling

Spring 2019, Spring 2014

MATH 562 Numerical Analysis

Fall 2016

Articles (6)

Application of population dynamics to study heterotypic cell aggregations in the near-wall region of a shear flow Cellular and Molecular Bioengineering

Y. Ma, J. Wang, S. Liang, C. Dong and Q. Du

2010-02-28

Our research focused on the polymorphonuclear neutrophils (PMNs) tethering to the vascular endothelial cells (EC) and the subsequent melanoma cell emboli formation in a shear flow, an important process of tumor cell extravasation from the circulation during metastasis. We applied population balance model based on Smoluchowski coagulation equation to study the heterotypic aggregation between PMNs and melanoma cells in the near-wall region of an in vitro parallel-plate flow chamber, which simulates in vivo cell-substrate adhesion from the vasculatures by combining mathematical modeling and numerical simulations with experimental observations. To the best of our knowledge, a multiscale near-wall aggregation model was developed, for the first time, which incorporated the effects of both cell deformation and general ratios of heterotypic cells on the cell aggregation process. Quantitative agreement was found between numerical predictions and in vitro experiments. ...

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Injury-Initiated Clot Formation Under Flow: A Mathematical Model with Warfarin Treatment Applications of Dynamical Systems in Biology and Medicine, The IMA Volumes in Mathematics and its Applications 158

L. de Pillis, E. Graham, K. Hood, Y. Ma, A. Radunskaya and J. Simon

2015-02-28

The formation of a thrombus (commonly referred to as a blood clot) can potentially pose a severe health risk to an individual, particularly when a thrombus is large enough to impede blood flow. If an individual is considered to be at risk for forming a thrombus, he/she may be prophylactically treated with anticoagulant medication such as warfarin. When an individual is treated with warfarin, a blood test that measures clotting times must be performed. The test yields a number known as the International Normalized Ratio (INR). The INR test must be performed on an individual on a regular basis (e.g., monthly) to ensure that warfarin’s anticoagulation action is targeted appropriately. In this work, we explore the conditions under which an injury-induced thrombus may form in vivo even when the in vitro test shows the appropriate level of anticoagulation action by warfarin. We extend previous models to describe the in vitro clotting time test, as well as thrombus formation in vivo with warfarin treatments. We present numerical simulations that compare scenarios in which warfarin doses and flow rates are modified within biological ranges. Our results indicate that traditional INR measurements may not accurately reflect in vivo clotting times.

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A stochastic model for microbial fermentation process under Gaussian white noise environment Numerical Algebra, Control and Optimization (NACO)

Y. Wang, L. Wang, Y. Zhao, A. Song, and Y. Ma

2015-05-01

In this paper, we propose a stochastic model for the microbial fermentation process under the framework of white noise analysis, where Gaussian white noises are used to model the environmental noises and the specific growth rate is driven by Gaussian white noises. In order to keep the regularity of the terminal time, the adjustment factors are added in the volatility coefficients of the stochastic model. Then we prove some fundamental properties of the stochastic model: the regularity of the terminal time, the existence and uniqueness of a solution and the continuous dependence of the solution on the initial values.

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Generalized local and nonlocal master equations for some stochastic processes Computers & Mathematics with Applications

Y. Zhao, J. Wang, Y. Ma, and Q. Du

2016-06-01

In this paper, we present a study on generalized local and nonlocal equations for some stochastic processes. By considering the net flux change in a region determined by the transition probability, we derive the master equation to describe the evolution of the probability density function. Some examples, such as classical Fokker–Planck equations, models for Lévy process, and stochastic coagulation equations, are provided as illustrations. A particular application is a consistent derivation of coupled dynamical systems for spatially inhomogeneous stochastic coagulation processes.

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A Novel Fractional Microbial Batch Culture Process and Parameter Identification Differential Equations and Dynamical Systems

P. Mu, L. Wang, Y. An, and Y. Ma

2018-01-01

This paper considers the microbial batch culture for producing 1,3-propanediol(1,3-PD) via glycerol disproportionation. Due to the nature of the fractional order operations, a novel fractional order model, which is based upon the original ordinary differential dynamic system, is introduced to describe the complex bioprocess in a more accurate manner. Existence and uniqueness of solutions to the novel fractional order system and the continuity of solutions with respect to the parameters are discussed respectively. In addition, a parameter identification problem of the system is presented, and a particle swarm optimization algorithm is constructed to solve it. Finally, the conclusion is drawn by numerical simulations.

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Stochastic maximum principle for partial information optimal investment and dividend problem of an insurer Journal of industrial and management optimization

Y. Wang, Y. Zhao, L. Wang, A. Song and Y. Ma

2018-04-01

We study an optimal investment and dividend problem of an insurer, where the aggregate insurance claims process is modeled by a pure jump Lévy process. We allow the management of the dividend payment policy and the investment of surplus in a continuous-time financial market, which is composed of a risk free asset and a risky asset. The information available to the insurer is partial information. We generalize this problem as a partial information regular-singular stochastic control problem, where the control variable consists of regular control and singular control. Then maximum principles are established to give sufficient and necessary optimality conditions for the solutions of the regular-singular control problem. Finally we apply the maximum principles to solve the investment and dividend problem of an insurer.

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