Exploring the symbolic, embodied, and ethical dimensions of interaction between humans and intelligent systems. This theme examines the mutual shaping of humans and machines—how robotic and AI systems are interpreted, trusted, and engaged with by humans, and how those systems can be designed to accommodate subjectivity, ambiguity, and ethical asymmetry.
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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