Garret Vo

About

Garret Vo is a computer scientist working at the intersection of optimization, machine learning, and signal processing. He has a PhD in industrial engineering from Florida State University, masters in mechanical engineering from Montana State University, and bachelor degree in physics from the same institution. Garret teaches Big Data Systems and Intelligence Analytics at Northeastern University. Prior to Northeastern University, he taught modeling and simulation, and programming for engineers and scientists in MATLAB at George Mason University. With his knowledge and experience in machine learning, and engineering, Garret is looking forward to work with students to educate the next generation of hybrid engineers with skills in machine learning.

Selected Publications

• P Rajaraman, GD Vo , G Hansen, JJ Heys. Comparison of continuous and discontinuous finite element methods for parabolic differential equations employing implicit time integration. International Journal for Computational Methods in Engineering Science and Mechanics (2017).
• Garret D. Vo . Comparision of continuous and discontinuous Galerkin finite element methods for parabolic partial differential equations with implicit time stepping. Master Thesis. Department of Mechanical and Industrial Engineering, Montana State University, 2012.
• Vo, G. D. , & Heys, J. (2011). Biofilm deformation in response to fluid flow in capillaries. Biotechnology and bioengineering, 108(8), 1893-1899.