Logan is a PhD student in electrical engineering and computer science. His research focuses on intersecting areas in traditional machine learning, deep learning, and statistical analysis. He is particularly interested in making machine learning more robust and reliable and in making AI more human aligned. Much of his research focuses on adversarial examples or imperceptibly changed inputs that can induce worst-case behavior in machine learning systems. He recently completed a statistical analysis with the help of MATLAB’s interface and toolboxes. In the future, he plans to use the simulation capabilities of MathWorks software (e.g., with Unreal Engine) to complete his domain adaptation and transfer learning research, and the Signal Processing Toolbox to better understand non-robust features. Logan earned an SB in computer science from MIT.