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Austin Garrett
AI software engineering and statistical computation, especially in probabilistic programming and computer vision.
Austin Garrett is a highly accomplished Master's graduate in Computer Science from the prestigious Massachusetts Institute of Technology (MIT). He has devoted himself to research specializing in Bayesian inference and probabilistic programming applied to neural networks. With extensive knowledge in data science frameworks such as Python, Julia, PyTorch, TensorFlow, and a cutting-edge language for probabilistic inference called Gen. Austin's expertise lies in complex engineering pipelines, stating graduate and undergraduate experiences as a researcher in the Computational Cognitive Science Group and the Computational Structure and Galaxy Formation Group at MIT.
His zeal for research continued as he became a graduate researcher and lab teaching assistant at MIT's Department of Electrical Engineering and Computer Science. He also worked as an undergraduate researcher at Arizona State University's Department of Physics.
