PhD Thesis Defense
Generative Robotics: Self-Supervised Learning for Human-Robot Collaborative Creation
Abstract: Robotic automation is generally welcomed for tasks that are dirty, dull, or dangerous, but with expanding robotic capabilities, robots are entering domains that are safe and enjoyable, such as creative industries. Although there is a widespread rejection of automation in creative fields, many people, from amateurs to professionals, would welcome supportive or collaborative creative [...]
Embodied Artificial Intelligence for Emergency Care in Unstructured Environments
Abstract: In mass casualty events and resource-constrained scenarios, limited responder capacity leads to preventable deaths. Time is of the essence particularly in severe trauma: the sooner individuals receive care, the higher their chances of survival. Yet a single responder can only manage a few patients simultaneously, leaving others unattended. This thesis addresses this capacity constraint [...]
Title: Leveraging Geometric Priors for Robust Robotic Manipulation
Abstract: This thesis explores how explicit 3D geometric representations, trained at scale on synthetic data, can serve as priors to enhance robotic manipulation. Even with recent progress in geometric understanding, generalization to unseen objects and environments remains constrained by the scale and diversity of existing 3D training data. Although more large-scale 3D datasets have been [...]
Unifying Perception and Creation with Generative Models
Abstract: Recent advances in large-scale generative modeling have reshaped our understanding of visual intelligence. While models such as diffusion and autoregressive transformers have achieved remarkable success in image and video synthesis, their potential for visual perception and understanding remains underexplored. This thesis investigates how generative models can serve as powerful visual learners—bridging the long-standing divide [...]
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 [...]
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 [...]