PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Bring Hand to The Air: Towards Universal Aerial Manipulation

NSH 4305

Abstract: Uncrewed Aerial Vehicles (UAVs) have attracted the interest of researchers, industry, and the general public in many applications. Noticing that high-altitude tasks sometimes require active interaction with the environment, there have been more and more works focusing on aerial manipulation recently. Each of them has demonstrated the ability to use a specific aerial manipulator [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Spatial Reasoning and Semantic Representations for Intelligent Multi-Robot Exploration and Navigation

NSH 4305

Abstract: Autonomous robot exploration is widely applied in areas such as search and rescue, environmental monitoring, and structural inspection. Multi-robot exploration has garnered significant attention in the robotics research community, as it enables faster task completion and greater coverage than a single robot can achieve. However, it presents unique challenges: behavior coordination is complex, communication [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Leveraging Sense of Agency to Improve the Experience of Control Over Assistive Robots

GHC 6121

Abstract: In an age of autonomous driving and robotics, we are increasingly engaging with robots that deploy autonomous assistance. Cognitive science and human-computer interaction literature tells us that, when we apply autonomy in assistive settings, we are often augmenting the user's sense of agency over the system. Sense of agency is a phenomenon from cognitive [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Efficient Synthetic Data Generation and Utilization for Action Recognition and Universal Avatar Generation

NSH 3305

Abstract: Human-centered computer vision technology relies heavily on large, diverse datasets, but collecting data from human subjects is time-consuming, labor-intensive, and raises privacy concerns. To address these challenges, researchers are increasingly using synthetic data to augment real-world datasets. This thesis explores efficient methods for generating and utilizing synthetic data to train human-based computer vision models. [...]