Interactive Resume
Education
MS Computer Science - Texas A&M University (expected graduation May 2023)
Concentration in artificial intelligence and deep learning. Research interests include neuromorphic computing, self-supervised learning, reinforcement learning, super-resolution, computer vision, graph neural networks, data
visualization, memory compression, extended reality, and 3d graphics.
Notable Courses: Artificial Intelligence, Deep Learning, Machine Learning.
BS Computer Science - Oregon State University (March 2021)
Led research using adversarial machine learning on facial recognition systems in collaboration with McAfee ATR. Captain of Oregon State Men’s Lacrosse team.
Notable Courses: Deep Learning, Parallel Programming, Networks in Computational Biology.
Additional Projects: Used ResNet based autoencoders to predict tree growth regions from climate data, Predicting RNA-protein binding sites with CNNs.
Employment Experience
Led validation testing and debugging of Intel optimized AI workloads for release to early access customers. Analyzed AI workloads on next-gen data center architectures for several frameworks including TensorFlow and Pytorch. Collaborated with senior architects to optimize power and performance on AI workloads. (Python, Bash, TensorFlow, Pytorch, Linux, Docker).
Led development of an automation framework designed to launch and execute benchmarks on dozens of virtual machines across several nodes. Optimized power and performance in collaboration with senior architects for next generation data center workloads. Collected, analyzed, and presented workload performance data on both Intel and competitor hardware. (Python, Bash, Linux, virtual machines).
Named 2019 SC Awards Cybersecurity Student of the Year for work. Led research accepted for McAfee 2018 MPOWER Cybersecurity Summit. Used adversarial machine learning to attack convolutional neural networks in autonomous vehicles. Showcased the capabilities of both digital and physical attacks to McAfee executives and senior technical staff. Created and delivered a comprehensive presentation of findings to media, industry partners, and academic representatives. Performed software reversing, vulnerability, and exploitation training. (Python, Keras, Tensorflow, Linux)
Tasked with facilitating player growth and success, both on and off the field. Developed the offensive scheme for the 2020 and 2021 seasons.
Technical Skills
Programming Languages: Python, Bash, C, C++, HTML, CSS
Software Frameworks: Keras, Pytorch, Tensorflow, Numpy, Pytorch Lightning
Concepts: Linux, virtual machines, parallel programming, performance profiling
Tools: Weights and Biases, Docker, Jupyter Notebooks, Anaconda, Git/GitHub
Achievements
2019 SC Awards Cybersecurity Student of the Year. Research selected for McAfee 2018 MPOWER Cybersecurity
Summit. OSU Lacrosse Team Captain. MCLA All-Conference Lacrosse Player 2016-2019.