Exploring the architectures and symbolic frameworks that underlie intelligent behavior in machines. This theme bridges classical and contemporary AI approaches—including logic, language models, and neural architectures—with a special focus on how AI systems represent knowledge, make decisions, and relate to human users. Psychoanalytic theory is used to interrogate assumptions about mind, subjectivity, and trust.
The Machine Learning Control Project explores how modern data-driven techniques can augment or replace traditional control design methodologies. While classical control theory depends heavily on first-principles modeling, many real-world systems …
View projectThe Subject of Robotics Project investigates the symbolic, structural, and material conditions under which human and artificial subjects emerge. Drawing from control systems, robotics, artificial intelligence, and Lacanian psychoanalysis, the …
View projectThe Dialectical Information Architecture Project develops a novel framework for organizing, navigating, and evolving complex information systems. Built on a synthesis of traditional information architectures—hierarchical, organic, and sequential—the project introduces …
View projectThe Metastimuli Project develops methods to augment human learning by transforming conventional educational content—text, audio, or video with dialogue—into metastimuli: signals dynamically correlated with the learner’s own personal information management …
View projectThis undergraduate research project was funded by Puget Sound Energy via the Independent Colleges of Washington to develop a smart thermostat device based on principles of lumped-parameter modeling and estimation.
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