The followings are some courses that I have taken for credits in my PhD study.

CS2110 Object Oriented Programming & Data Structure

          • used Java primarily for objected-oriented programming (classes, objects, subclasses, types),
          • deal with different data structures (lists, trees, stacks, queues, heaps, search trees, hash tables),
          • developed user interfaces,
          • algorithm analysis (graph algorithm, asymptotic complexity)

CS4820 Introduction To Analysis Of Algorithms

          • covers four major algorithm design techniques (greedy algorithms, divide-and-conquer, dynamic programming and network flow)
          • covers classical algorithm: Gale Shapley Algorithm, interval scheduling and weighted interval scheduling, the Knapsack Problem, Bellman-Ford in DAG (directed acyclic graph), Ford-Fulkerson Algorithm, Max-Flow Min-Cut, Bipartite matching, Edmonds-Karp Algorithm
          • undecidability and NP-completeness

MAE6810 Methods of Applied Math I

          • Cartesian tensor
          • Linear algebra
          • Complex variable

MAE6820 Methods of Applied Math II

          • Partial differential equation
          • Tensor analysis
          • Calculus of variations

CEE6790 Time Series Data Analysis

          • Data processing tools and techniques: Fourier transforms, convolution, filtering, autoregressive moving average (ARMA) models

CHEME6800 Computational Optimization

          • Systems optimization modeling including theory and algorithms of linear, nonlinear, mixed-integer linear, mixed-integer nonlinear optimization;
          • Stochastic programming, robust optimization, optimization methods for big-data analysis

PHYS6780 Computational Physics

          • Numerical methods for ordinary and partial differntial equations
          • Linear algebra and eigenvalue problems, numerical integration
          • Fast Fourier transforms and spectral method

CS6820 Matrix Computations

          • Linear systems and Gaussian elimination, structured linear system
          • Least squares problems
          • Unsymmetric eigenvalue problems
          • Symmetric eigenvalue problems
          • Iterative methods for linear systems and eigenvalue problem

MAE6140 State Variable Modeling

          • Introduce to the state variable modeling framework, which is used for the representation of a broad range of material behaviors and material systems, including metals, polymers and composites

MAE5730 Intermediate Dynamics and vibration

          • Used three approaches: Newton Euler method, Lagrangian method and differential algebraic equations (DAE) approach to solve classical dynamics of single- and multi-degree-of-freedom systems, which is made up of particles, rigid-objects in 2 and 3 spatial dimensions

MAE7160 Fracture Mechanics

          • Mechanics of fracture, including linear elastic and elastic-plastic fracture theory, energy release rate, J integral, experimental methods, computational fracture mechanics and applications;
          • solving partial differential equation using MATLAB PDE Toolbox

MAE6110 Foundations of Solid Mechanics I

          • fundamentals of kinematics of deformation, traction and stress, and balance of momentum;
          • Constitutive theory for linear and nonlinear elastic bodies, including isotropic and orthotropic behaviors;
          • Boundary conditions, requirements for well-posed problems, and uniqueness.

MAE6120 Foundations of Solid Mechanics II

          • Dimensional analysis and normalization,Nonlinear beam theory (large deflection and buckling),Linear and von-karman plate theory, buckling of plates, Indentation problems (Hertz and Johnson-Kendall-Roberts theory), Thin film mechanics, Thermal stress and 2D elasticity problems

CEE7780 Continuum Mechanics & Thermodynmaics

          • kinematics; conservation laws; the entropy inequality; constitutive relations: frame indifference, material symmetry; and finite elasticity, rate-dependent materials, and materials with internal state variables