Joseph Carmack is a Principal Scientist at BAE Systems with a decade of experience advancing AI and machine learning for radio-frequency systems. He has led algorithm development for DARPA RF ML programs, delivering RF fingerprinting, deep waveform synthesis, multi-agent deep reinforcement learning for RF waveform manipulation, and end-to-end LTE receivers with deep learning-based signal processing kernels for interference cancellation and offset correction. With a PhD in Computational Materials Science and Engineering and a broad foundation in physics, mathematics, business, and computer science, he combines rigorous numerical methods (MPI, HPC, GPUs, CUDA) with practical ML deployment at scale. He is actively developing explainable AI for RF and a rapid prototyping framework to translate DRL ideas from sandbox environments to massively parallel implementations. In addition to research, he teaches undergraduate numerical methods, mentors students and volunteers, and has organized GPU programming workshops, reflecting a commitment to education and community. Based in New Hampshire, he brings a rare blend of theoretical depth and hands-on leadership to transforming complex signal-processing challenges into robust, auditable systems.
10 years of coding experience
Doctor of Mechanical Engineering (PhD), Computational Material Science and Engineering, 4.0 GPA, Doctor of Mechanical Engineering (PhD), Computational Material Science and Engineering, 4.0 GPA at University of Arkansas at Fayetteville
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Joseph Carmack - Principal Scientist at BAE Systems, Inc.