Student Talks
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 [...]
Visual-Tactile Synthesis for Texture Generation
Abstract: Recent advances in generative models have enabled the creation of highly realistic visual content, yet they remain limited to visual perception alone. In contrast, human interaction with the physical world is inherently multimodal — we not only see textures but also feel them. This gap motivates the goal of my thesis: to build generative models [...]
Towards Modernization of Long-Range Image-Space Planning for Off-Road Navigation
Abstract: This thesis revisits long-range, image-space planning for off-road navigation and modernizes the classical first-person view (FPV) paradigm by building upon recent advances in perception. It introduces a lightweight depth calibration scheme, analytic configuration-space (C-space) transforms, interpretable frontier selection, and a pixel-space A* planner with validated heuristic soundness. Concretely, we (i) make monocular depth metrically [...]
Building Robot Hands and Teaching Dexterity
Abstract: Our human hands are masterpieces of power and precision, capable of typing, hammering, or delicately using chopsticks. Yet most robots today still rely on simple two-finger grippers in controlled settings because dexterous hands are costly and difficult to deploy. To close this gap, I will introduce my LEAP Hands, high-performance, low-cost, and easy-to-assemble robotic [...]
Grounded Task Axes: Zero-Shot Semantic Skill Generalization via Task-Axis Controllers and Visual Foundation Models
Abstract: Transferring skills between different objects remains one of the core challenges of open-world robot manipulation. Generalization needs to take into account the high-level structural differences between distinct objects while still maintaining similar low-level interaction control. In this paper, we propose an example-based zero-shot approach to skill transfer. Rather than treating skills as atomic, we [...]
Multi-View 4D Human Reconstruction under Interaction Scenarios
Abstract: Building large-scale human datasets from multi-view videos is essential for advancing research in human behavior understanding, virtual reality, animation, and robotics. Compared to traditional motion capture systems that rely on physical markers to track motion, vision-based reconstruction not only enables the capture of human motion in unconstrained environments but also avoids altering human appearance [...]
Vision-Based Multi-Wire Detection and Tracking for UAV Wire Approach
Abstract: Reliable detection and tracking of power lines is critical for enabling under-wire UAV approach and inductive power-line charging to extend UAV range. However, wires are thin, featureless, and visually ambiguous structures that challenge traditional computer vision methods and degrade depth estimation accuracy. To address these challenges, this thesis presents a fully passive, camera-only multi-wire [...]
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. [...]