Home Languages Developers Organizations Search You
Matthew Donaldson
I am a graduate student at Washington University in St. Louis, majoring in Mechanical Engineering and pursuing a Master's in Data Analytics and Statistics. I pl
No Language
Conduction, convection, radiation, heat exchangers, pump performance, pipe flow, lift force, boundary layers, turbulence, experimental design
RStudio: Implementation of time series models, Monte Carlo Simulations, Fitting multivariate data to copula and Multivariate nonparametric regression
HTML
Matlab: Topics range from convex unconstrained problems to constrained nonconvex problems. Algorithms discussed: gradient descent, subgradient descent, projected subgradient descent, proximal gradient method and alternating direction method of multipliers.
Matlab: Analytical methods in design. Topics include mathematical methods, linear and nonlinear programming, optimality criteria, fully stressed techniques for the design of structures and machine components, topological optimization, search techniques, genetic algorithms and multi objective optimization.
Jupyter Notebook
Introduction to the theory and practice of machine learning and pattern classification. Topics of this course cover several important supervised and unsupervised machine learning models and methods including linear model of regression and classification, Perceptron, logistic regression, Bayesian learning methods, neural networks, nearest neighbor method, support vector machines, clustering, and principal component analysis. Students will apply learnt models to solve pattern classification problems using Python
MATLAB
Analysis and design of advanced thermo-fluid systems, including phase change and gas power and refrigeration cycles, combustion reactions, gas mixtures, and thermodynamic relations. Students work on thermodynamic design projects, both individually and as groups. Topics include, for example, geothermal power generation, alternative transportation systems, jet turbines, and fuel combustion analysis.
This course is a study of modeling and control of physical systems. Topics include: block diagram representation of single and multi-loop systems, control system components, transient and steady-state performance, stability analysis, Nyquist, Bode, and root locus diagrams, compensation using lead, lag and lead-lag networks, design synthesis by Bode plots and root-locus diagrams, state-variable techniques, state-transition matrix, state- variable feedback.
Predicting the severity of asthma attacks based on a data set with ten features(gender, age, outdoor job, outdoor activity, if they smoke, humidity, temperature, pressure, UV index and wind speed). In this project we aim to go through the data analytics process to come up with a good model for predicting asthma attack severity. The dataset was taken from Haque, Radiah. “1191402606/Optimised-Deep-Neural-Network-Model: Dataset and Source Code.” Zenodo, 26 Aug. 2021, https://zenodo.org/record/5271780#.YgBQferMKUl. https://zenodo.org/record/5271780#.Yfr9bOrMKUk
Explored concepts ranging from convex constrained and unconstrained optimization problems. Topics discussed: gradient descent, Newton Method, proximal gradient descent, LaGrange multipliers and KKT conditions.
Introduction to Wind energy as renewable or sustainable energy source. Topics include wind turbines performance, design, aerodynamics, dynamics, materials fatigue, composite materials, and engineering economics
