Thomas Norris

Major: BBA MIS
Graduation: August 2021


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About Me

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I am a Fox Senior studying Management Information Systems and pursuing a minor in Computer Science. I am particularly interested in the fields of Machine Learning and Cybersecurity, largely for their shared traits of growing rapidly in both innovation and their importance to the world. My hometown is Wheaton, Maryland, where I first acquired a passion for computer science and information architecture.

Throughout my time at the Fox School of Business, I have spent time as a member of the Association for Information Systems (AIS), an MIS coding helpdesk student worker, and a member/founder of the MIS Hackathon team, the Lanterns. Some of my favorite projects I’ve taken part in while at Fox include creating a prototype app Recycle-Go to encourage green habits through their gamification, and the development of a prototype website for pharmaceutical distributor AmerisourceBergen to calculate and track the financial risk of IT decisions using the Factor Analysis of Information Risk (FAIR) model.

I have dedicated a large part of my academic career to learning programming languages and am now intermediate in Java, Python, C, and JavaScript, to name a few. I am especially interested in backend development but have a great deal of experience in frontend development including the creation of visualizations and dashboards. My programming experience, coupled with my work at the coding helpdesk, make me a valuable asset for work such as consultation and analysis. It is for this reason I have accepted an analyst position at Deloitte’s Government and Public Services sector, where I will be assisting clients with an array of technology-related issues starting October of 2021.

My most recent project has been the studying and development of a machine learning classifier model for an Independent Research Project with the Computer Science department at Temple’s CST. For an introduction to some of the important aspects of training a linear classification model, please see the presentation found below:

Learning Linear Classifiers from ThomasNorris16

Professional Achievements

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