Responsible, committed, passionate AI / ML researcher and engineer with more than a decade of experience including deep learning and evolutionary computation research as well as desktop and mobile applications development on multiple platforms. My most recent project involves improving CNNs with perturbations to parameters at initialization which leads to avoiding vanishing gradients thus improving training efficiency and resulting accuracy of networks.
GPA: 4.0
Relevant Coursework
Graduate Membership
GPA: 3.8
Relevant Coursework
GPA: 3.17
Relevant Coursework
GPA: 4.0
Relevant Coursework
Aside from Computer Science, I enjoy many hobbies both outdoors and indoors. Being from Mississippi, most of the year is very warm, and I enjoy going swimming, playing soccer, rock climbing, and kayaking (the latter two of which usually involve traveling).
When forced indoors, I play video games, board games, as well as spending a great deal of my free time creating software, completing online courses, and researching state-of-the-art advances in machine learning algorithms. My aspirations include continuing my education through perusing recent research papers, completing online coursework, continuing my formal education, and experimentinig with personal projects. Most recently, I have become very interested in Deep Learning as well as nature inspired machine learninig methods. I have spent much time reading about Neurevolution of Augmenting Topologies (NEAT) and its extensions and adaptations. I have also read papers regarding swarm algorithms, state-of-the-art image segmentation, and novelty search. I have completed several exercises in data science and machine learning over the past couple of years. These can be seen on my github page linked below.
