Backend engineer working on the Google Cloud Networking team

I joined Stephen McAleer, a UCI Computer Science PhD candidate, in working on the protein folding prediction problem which we intended to solve with Neural nets and reinforcement learning. My role included:• Helping to find a good representation for a protein in 2D and 3D space and worked on implementing this in python. • Building a class for the protein environment with methods for creating proteins, making protein folds, ensuring legal moves and methods to calculate or access all the other information which would be necessary for protein prediction. • Creating a script to generate the first random training samples. • Experimenting with various architectures for the Neural Net to see what could learn the protein structure well and implemented the designs for our policy/value network using Keras. • Experimenting with various methods of exploration for reinforcement learning such as e-greedy, bayesian(using dropout), and Boltzmann.

• Worked on projects dealing with organization and manipulation of extremely large datasets via python packages such as Numpy and Pandas. • Became familiar with Anaconda as a means of organizing packages and environments. • Used statistical packages such as scipy, sklearn, and matplotlib to write analysis functions which were tailored to my data. • Gained a deeper understanding of computer processing limitations by means of the python multiprocessing methods along with the terminal process viewer, top/htop. • Wrote functions with efficiency in mind by understanding the strengths and weaknesses of various python packages. • Developed and implemented a principle component analysis function to identify variables responsible for variance. • Designed filters to emphasis/eliminate various features within a signal.

• Responsible for ocean safety.• First responder for trauma injuries, medical injuries, and drowning victims.