Carter Brown
About Carter Brown
Carter Brown is a Machine Learning and Software Engineer with a background in physics and computer science. He has co-authored research papers and held various roles in academia and industry, including positions at Cornell University and Expedition Technology Inc.
Work at Expedition Technology
Carter Brown has been employed at Expedition Technology Inc as a Machine Learning and Software Engineer since 2019. In this role, he has contributed to various projects and initiatives focused on machine learning applications. He co-authored an article titled 'Agile Machine Learning: Taming the Wild West of ML Continuous Integration', which was published on the company's website. His work at Expedition Technology emphasizes the integration of machine learning techniques in practical applications.
Education and Expertise
Carter Brown studied at Cornell University, where he earned a Bachelor of Arts (B.A.) in Physics with a minor in Computer Science from 2013 to 2019. His academic background provides a solid foundation in both theoretical and practical aspects of machine learning and software engineering. He has also presented research at notable conferences, including a presentation on 'Complex-Valued Equivariant Neural Networks for Radio Frequency Fingerprinting' at the American Mathematical Society Joint Mathematics Meeting in January 2020.
Background
Carter Brown has a diverse professional background that includes various roles in academia and industry. He worked as a Teacher's Assistant for the Introduction to Data Science course at Cornell University in 2017. Additionally, he served as a Computer Vision Research Intern at SRI International from 2017 to 2018. His early experience includes programming and design work with Random Hacks of Kindness in 2015 and serving as Director of Analytics for the Cornell Consulting Club from 2016 to 2018.
Research Contributions
Carter Brown has made significant contributions to the field of machine learning through his research. He co-authored a paper titled 'ChaRRNets: Channel Robust Representation Networks for RF Fingerprinting', which was presented in May 2021. He also presented research on 'Open set recognition through unsupervised and class-distance learning' at the 2nd ACM Workshop on Wireless Security and Machine Learning in July 2020. His research focuses on innovative approaches to machine learning and its applications in wireless security.
Previous Work Experience
Carter Brown has held various positions prior to his current role at Expedition Technology. He worked as a Raft Guide at Mother Lode River Center from 2014 to 2016. His involvement in the Cornell Consulting Club as Director of Analytics lasted from 2016 to 2018. He also gained experience as a Computer Vision Research Intern at SRI International and as a Teacher's Assistant at Cornell University, showcasing his diverse skill set and adaptability in different environments.