Student Talks
Towards Scaling Embodied Data for Robot Learning
Abstract: As artificial intelligence advances quickly in the digital domain, the next frontier lies in physical intelligence: systems that learn through acting and sensing in the real world. In this thesis, we explore practical ways of scaling such embodied data across three directions. AnyCar scales synthetic data through large-scale simulation, training a universal dynamics transformer [...]
Attractors and Their Applications in Heuristic Search
Abstract: Heuristic search provides a principled way to guide exploration in large state spaces, enabling efficient solution finding. As a result, it is widely used across domains such as robotics, games, and planning. However, its performance is often limited by memory consumption and computational overhead, which have motivated extensive research on improving both. This thesis [...]
Robotic System Design Principles for Human-Human Collaboration
Abstract: Robots possess unique affordances granted by combining software and hardware. Most existing research focuses on the impact of these affordances on human-robot collaboration, but the theory of how robots can facilitate human-human collaboration is underdeveloped. Such a theory would be beneficial in education. An educational device can afford collaboration in both assembly and use. [...]
Erica Weng – PhD Defense Info TBA
More info coming soon
Design Optimization of Modular Manipulators for Manipulation in Cluttered Agricultural Environments
Abstract: Although agriculture is a highly mechanized industry, essential and high-value subsectors such as horticulture and floriculture remain heavily reliant on manual labor because they require complex, contact-rich, and highly selective handling of both plants and produce. The variability and density of tree-canopy clutter further complicate the automation process, making robot performance difficult to quantify [...]
Examining Engagement and Motivation in a Conversational Robotic Exercise Coach for Older Adults
Abstract: Exercise is essential for healthy aging, but motivation and adherence to exercise often decline with age, leading to a more sedentary lifestyle. At the same time, the growing aging population continues to strain the availability of physical therapists and exercise coaches. In this thesis, we introduce a conversational robotic exercise coach system designed to support [...]
Examining Engagement and Motivation in a Conversational Robotic Exercise Coach for Older Adults
Abstract: Exercise is essential for healthy aging, but motivation and adherence to exercise often decline with age, leading to a more sedentary lifestyle. At the same time, the growing aging population continues to strain the availability of physical therapists and exercise coaches. In this thesis, we introduce a conversational robotic exercise coach system designed to support [...]
Modeling what Matters: Emergent Abstraction In Reinforcement Learning
Abstract: Real-world decision-making is rife with partial observability, long horizons, and complex multi-agent interactions. This thesis argues that abstraction—forming simplified representations of the task that retain relevant information—offers a unifying principle for tackling these challenges across model-free and model-based reinforcement learning (RL). We develop methods in which abstractions are not hand-designed but emerge from learning objectives, yielding representations that [...]
Self-supervised tactile perception for robot dexterity
Abstract: Humans are incredibly dexterous. We interact with and manipulate tools effortlessly, leveraging touch without a second thought. Yet, replicating this level of dexterity in robots is a major challenge. While the robotics community, recognizing the importance of touch in fine manipulation, has developed a wide variety of tactile sensors, how best to leverage these [...]
Efficient Visual Modeling with Adaptive Representations
Abstract: While image understanding, generation, and manipulation have matured rapidly in recent years, video remains challenging due to the significantly larger input size. As a result, tasks such as generating long videos or understanding extended video sequences remain out of reach for current models due to their computational cost. This talk presents a series of [...]