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Christopher S Brown, PhD

Christopher Brown is a Computer Scientist specializing in Machine Learning and other data-related topics.

His education is in Mathematics, and he has much background in Education. He recently graduated with his PhD in Computing, and is particularly interested in applied Machine Learning and statistical/mathematical modeling.

Professional Experience

  • U.S. Geological Survey, Computer Scientist: February 2022–Present

  • Georgia Tech Research Institute, Research Scientist II : June 2015–August 2017

  • Assistant Professor (Lecturing) Computer Science, University of Utah: Fall 2020–Spring 2022

Education and Certifications

  • University of South Alabama: PhD Computing 2020

Abstracts and Presentations

  • C. Scott Brown and Ryan G. Benton. Decision Surfaces of Localized Classifiers. In 2020 International Joint Conference on Neural Networks (IJCNN).

  • C. Scott Brown and Ryan G. Benton. Local Gaussian Process Features for Clinical Sensor Time- Series. IEEE BIBM 2019 Workshop on Machine Learning and Artificial Intelligence in Bioinformatics and Medical Informatics.

  • C. Scott Brown, Venu Garkiapati and Yi Hou. A Machine-Learning Decision-Support Tool for Travel-Demand Modeling. Presented at the Transportation Research Board annual meeting 2019.

  • C. Scott Brown, William Glisson, Ryan Benton, Jordan Shropshire, Thomas Watts, and Timothy Sullivan. Image segmentation stability: an empirical investigation. IEEE SoutheastCon 2018.

Science and Products

Non-USGS Publications**

C. Scott Brown. Local Model Feature Transformations. Dissertation. 2020.
Al Jadda, Khalifeh, Mohammed Korayem, Camilo Ortiz, Chris Russell, David Bernal, Lamar Payson, C. Scott Brown, and Trey Grainger. Augmenting recommendation systems using a model of semantically-related terms extracted from user behavior. arXiv preprint arXiv:1409.2530 (2014).

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

Science and Products

Non-USGS Publications**

C. Scott Brown. Local Model Feature Transformations. Dissertation. 2020.
Al Jadda, Khalifeh, Mohammed Korayem, Camilo Ortiz, Chris Russell, David Bernal, Lamar Payson, C. Scott Brown, and Trey Grainger. Augmenting recommendation systems using a model of semantically-related terms extracted from user behavior. arXiv preprint arXiv:1409.2530 (2014).

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.