Lauren Wang will present her General Exam "Explainable and Controllable Augmented Reality Interfaces through Embodied Interaction and Situated Visualization" on Monday, April 27, 2026 at 10:30 AM in CS 401. Committee Members: Parastoo Abtahi (advisor), Andrés Monroy-Hernández, Tom Griffiths Abstract: As technologies become more sophisticated, users are expected to interact with intelligent systems whose reasoning, capabilities, and limitations are opaque. I identify two shortcomings in such human-computer interfaces: a gulf of execution[1], where users struggle to communicate abstract, multimodal, or spatial intent, and a gulf of evaluation[1], where limited feedback makes it difficult to understand how inputs influence outcomes. Current language-based interfaces lack the bandwidth to convey non-textual information and are ambiguous in spatial contexts. My work investigates augmented reality (AR) as a unifying interaction paradigm to bridge both gaps by enabling embodied multimodal input (voice, gesture, gaze) to better capture user intent, and by providing in-situ, spatially grounded visualizations that help establish shared mental models. I demonstrate this approach across real-world applications. In human-robot interaction, failures arise when users do not understand what robots can and cannot do. I develop Explainable OOHRI[2] to expose robot constraints and action possibilities through AR visualizations, and enable users to issue personalized instructions via direct manipulation of GhostObjects[3] —life-size, world-aligned virtual twins. Extending this paradigm to interaction with generative AI, I explore embodied 3D/4D scene editing for content creation and enhancing human-human communication. I study methods that fuse multimodal inputs to infer user intent across multiple levels of abstraction, while producing immediate, interpretable outputs that support counterfactual exploration and maintain controllability throughout iterative design processes. Taken together, my research aims to advance AR interfaces that make intelligent systems more explainable, controllable, and aligned with human intent, grounded in cognitive theories and designed to drive impacts in real-world settings. Reading List: https://docs.google.com/document/d/1RLaQ7eUAq7MStWIkt8QvtzNj-UkaHyJQJboRh7n7... Everyone is invited to attend the talk, and those faculty wishing to remain for the oral exam following are welcome to do so.