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I am currently a graduate student at the Harvard John A. Paulson School for Engineering and Applied Sciences and the Harvard Institute for Applied Computational Science pursuing a Ph.D. in Applied Mathematics with a Masters of Science (S.M.) in Computational Science and Engineering. As a NSF-GRFP fellow, I am working in Prof. Katia Bertoldi's group on modeling bio-inspired optimized materials and applying generative parametric machine learning algorithms to control soft robotic actuators and classify objects based on embedded sensor data. In 2015, I earned a thesis-based Masters of Engineering (M.Eng.) in Engineering Sciences at Harvard University and worked with Prof. James R. Rice on modeling the physics of subglacial hydrology. In 2013, I graduated with a B.S. in Mechanical Engineering from Case Western Reserve University with a thesis titled "Design and Implementation of Wind Turbine Torque Measurement Device."

For more information, please visit my website at mcfernandes.com

You may also find more information in the following links:
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Curriculum Vitae

Resume

Current Projects

Spogne Structure Project: This is the reporsitory containing all of the codes and data necessary for reconstructing the models presented in the Natuer Materials paper: Mechanically robust lattices inspired by deep-sea glass sponges


Sponge Ridge Project: This is the reporsitory containing all of the codes and data necessary for reconstructing the models presented in the publication.
Incliend Metamaterials: This is the reporsitory containing all of the codes and data necessary for reconstructing the models presented in the publication.
Python For Abaqus: This is a repository outlining a step-by-step tutorial on everything you need to know about python to be able to efficiently use the python scripting interface.
Short Linker: (Decomissioned) Page created in GitHub to provide temporary short links that forward to a desired location. These short links can be as short as you want and expire within 30 days, so that a particluar name becomes available again.
Allegheny County Home Prices Interview Case: An exploratory case, this project explores creating a Machine Learning model using XGBoost to predict sale prices of homes in Allegheny County PA and create a Home Value Index for years ranging from the 1800s to 2021.

Work

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i = 0;

while (!deck.isInOrder()) {
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}

print 'It took ' + i + ' iterations to sort the deck.';

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