
About
Angela Beasley serves as an Associate Professor of Instruction in the Computer Science department at The University of Texas at Austin, teaching core courses including Principles of Machine Learning (CS 363M) and Introduction to Data Mining (CS 363D) continuously from 2017 through Spring 2025. Her extensive teaching portfolio also includes Elements of Computers & Programming and Data Analytics courses.
Her academic foundation includes:
- MS in Computer Science with Machine Learning concentration from The George Washington University
- BS in Computer Science from The University of Texas at Austin
Beasley's research bridges theoretical computer science and real-world engineering applications, with primary focus on Machine Learning and Data Mining methodologies. She actively examines the societal implications of algorithmic decision-making, warning about potential increases in unfairness and inequity through her TEDx talks. Her work spans hardware-accelerated image processing, naval signal systems, and virtual collaboration environments, demonstrating interdisciplinary technical expertise.
Publication trends reveal an evolution from defense-focused engineering (2003-2012) toward data-centric applications, with early work on FPGA-based image processing and underwater acoustics transitioning to machine learning education and virtual collaboration frameworks by 2009.
Her recognition includes:
- CNS Teaching Excellence Award from UT
- Lockheed Martin Honored (2010)
- Lockheed Martin Special Recognition Award (2009)
- Multiple Lockheed Martin awards (2007 Special Recognition, Spot Award, and Honored)
With 15 years of prior industry experience developing US Navy systems—including submarine sonar, periscope systems, unmanned underwater vehicles, and satellite communications—Beasley brings substantial practical knowledge to her instructional role, though no current research grants or student advising details are documented. Her office operates from GDC 6.314 with regular student hours.
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