Zheng Chen

faculty

Zheng Chen, PhD

Assistant Professor

Mathematics

Curriculum Vitae

508-999-9236

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Liberal Arts 394C

Education

2014Brown UniversityPhD
2010Brown UniversityMS

Teaching

  • Numerical algorithms
  • Calculus

Teaching

Programs

Teaching

Courses

Research investigations of a fundamental and/or applied nature defining a topic area and preliminary results for the dissertation proposal undertaken before the student has qualified for EAS 701. With approval of the student's graduate committee, up to 15 credits of EAS 601 may be applied to the 30 credit requirement for dissertation research.

An introduction to the main concepts and techniques of college algebra. Topics include: linear, quadratic, exponential and logarithmic functions, as well as modeling of data using functions. This is the first semester of the college math sequence designed for students interested in Biology and Life Sciences. This course fulfills the general education core requirements for Biology and Life Sciences majors who matriculated prior to Fall 2012 and has been approved by University Studies Curriculum for students matriculating in Fall 2012 or later.

An introduction to constrained and unconstrained optimization. Numerical optimization is an essential tool in a wide variety of applications. The course covers fundamental topics in unconstrained optimization and also methods for solving linear and nonlinear constrained optimization problems.

An introduction to constrained and unconstrained optimization. Numerical optimization is an essential tool in a wide variety of applications. The course covers fundamental topics in unconstrained optimization and also methods for solving linear and nonlinear constrained optimization problems.

Research

Research awards

  • $ 13,000 awarded by Mathematical Association of America for Mixed Model Implicit and IMEX Runge-Kutta Methods
  • $ 438,284 awarded by Office of Naval Research for UMassD MUST IV: Learning Nonlinear Dynamical Systems from Sparse and Noisy Data: Applications to Signal Detection and Recovery

Research

Research interests

  • Numerical analysis, scientific computing, high performance computing
  • Machine learning, image processing, neural networks
  • Kinetic problems, multi-scale computational methods
  • Numerical methods for problems with singularities
  • Uncertainty quantification, fractional-order partial differential equations

    External links