MSR Thesis Presentation

Abstract: Imitation learning has emerged as a leading paradigm for teaching manipulation skills to robots, but its success depends on the costly endeavour of collecting robot demonstrations through teleoperation. Generalizing to novel objects, environments, and task variations typically requires massive datasets that are expensive to scale. This thesis investigates an alternative lever: hierarchy—explicitly factorizing manipulation [...]

Abstract: Personalizing exoskeleton control to individual preferences is crucial for real world deployment. Data-driven approaches have enabled user-generalizable controllers, yet conventional personalization methods optimize biomechanical cost functions over user preferences. Prior work shows that users can perceive and report their preferred parameters, yet no lightweight method maps user intent to quantitative control parameter changes in [...]

Abstract: Robotic manipulation policies are typically evaluated on curated, in-distribution test sets, which offer limited insight into how these policies behave under plausible variation. One important source of this variation is geometric in nature, arising from small changes in object geometry that quietly alter grasp affordances and contact dynamics. Rather than treating robustness as a [...]

Abstract: Graphical User Interface (GUI) agents need strong planning—what to do next—and grounding—where to click next—to solve user tasks. Yet these agents remain unreliable, and standard metrics such as task success or next-action accuracy often obscure why they fail. In this talk, I argue that reliable GUI agents require fine-grained diagnosis of core agentic capabilities, [...]

Abstract: Bio-inspired aquatic robots offer a promising route to agile and efficient locomotion in fluid environments, where conventional rigid systems remain limited. In bio-inspired aquatic systems, locomotion is not determined by actuation or control alone, but instead emerges from tightly coupled interactions among body morphology, distributed compliance, actuation, onboard sensing, and the surrounding flow, making [...]

Abstract: Embodied navigation asks an autonomous agent to move through unknown environments and accomplish tasks such as finding objects or following instructions. Reliable performance in real-world settings, from household assistance to warehouse logistics, requires the agent to tightly integrate perception, semantic reasoning, and long-horizon planning under cluttered layouts, ambiguous appearances, and robot-specific constraints. Vision-language models [...]

Abstract: An agent that performs well on its own may still struggle when working with others. In multi-agent environments, success depends not only on understanding the world but also on understanding what other agents know, intend, and conceal. Cooperative partners follow hidden conventions, while adversarial opponents deceive. This work argues that robust multi-agent behavior requires [...]

Abstract: Aviation safety analysis increasingly benefits from large-scale operational trajectory data, yet raw motion traces alone are insufficient for understanding safety-critical events on the airport surface. The significance of an aircraft’s motion depends on the structured operational environment in which it occurs, including runways, taxiways, hold-short lines, and interactions among multiple agents over time. This [...]

Abstract: Touch is the essential sensory modality through which animals and robots physically negotiate the world. While much of robotic touch focuses on the capabilities of currently available tactile hardware, this thesis asks a more general question: what forms of tactile processing and representation could allow robots to approach the dexterity of animals? This thesis [...]