PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Understanding and acting in the 4D world

NSH 4305

Abstract: As humans, we are constantly interacting with and observing a three-dimensional dynamic world; where objects around us change state as they move or are moved, and we, ourselves, move for navigation and exploration. Such an interaction between a dynamic environment and a dynamic ego-agent is complex to model as an ego-agent's perception of the [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Learning Universal Humanoid Control

GHC 4405

Abstract: Since infancy, humans acquire motor skills, behavioral priors, and objectives by learning from their caregivers. Similarly, as we create humanoids in our own image, we aspire for them to learn from us and develop universal physical and cognitive capabilities that are comparable to, or even surpass, our own. In this thesis, we explore how [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Generative Robotics: Self-Supervised Learning for Human-Robot Collaborative Creation

GHC 7501

Abstract: While Generative AI has shown breakthroughs in recent years in generating new digital contents such as images or 3D models from high-level goal inputs like text, Robotics technologies have not, instead focusing on low-level goal inputs. We propose Generative Robotics, as a new field of robotics which combines the high-level goal input abilities of [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

3D Video Models through Point Tracking, Reconstructing and Forecasting

NSH 3305

Abstract: 3D scene understanding from 2D video is essential for enabling advanced applications such as autonomous driving, robotics, virtual reality, and augmented reality. These fields rely on accurate 3D spatial awareness and dynamic interaction modeling to navigate complex environments, manipulate objects, and provide immersive experiences. Unlike 2D, 3D training data is much less abundant, which [...]