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 [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Towards a Robot Generalist through In-Context Learning and Abstractions

NSH 1305

Abstract: The goal of this thesis is to discover AI processes that enhance cross-domain and cross-task generalization in intelligent robot agents. Unlike the dominant approach in contemporary robot learning, which pursues generalization primarily through scaling laws (increasing data and model size), we focus on identifying the best abstractions and representations in both perception and policy [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Vision-based Human Motion Modeling and Analysis

NSH 4305

Abstract: Modern computer vision has achieved remarkable success in tasks such as detecting, segmenting, and estimating the pose of humans in images and videos, reaching or even surpassing human-level performance. However, they still face significant challenges in predicting and analyzing future human motion. This thesis explores how vision-based solutions can enhance the fidelity and accuracy [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Physical Process-Informed Mapping for Robotic Exploration

NSH 4305

Abstract: Mobile robots used for information gathering tasks rely on dense, predictive mapping of large-scale regions to determine where to take measurements. Current approaches to mapping commonly rely on Gaussian process regression to spatially correlate data, extrapolate from sparse samples, and estimate uncertainty. However, these approaches do not incorporate meaningful information about physical processes that [...]