PhD Thesis Proposal

Abstract: Touch is a powerful yet underused channel for learning. Prior research shows that haptic interaction can support both sensorimotor skill acquisition and the understanding of abstract concepts by grounding learning in bodily experience. However, most haptic devices remain expensive, technically complex, and difficult to reproduce, which keeps them largely confined to specialized laboratories. This limits [...]

Abstract: Agricultural specialists are actively turning to robotic and computer vision-based systems to reduce the manual labor required to inspect and manipulate crops. These tasks require robots to perceive and interact with plants from partial, localized observations, often in dense and cluttered environments. For perception, a central challenge is that crops are small, are easily [...]

Abstract: Simulation enables robots to learn and evaluate behaviors at scale before real-world deployment. Yet the mismatch between simulation and the physical world remains a fundamental obstacle. This is particularly challenging for dexterous manipulation, where contact-rich interactions and dynamics variations across objects and robot embodiments are difficult to model. In my thesis research, I explore [...]

Abstract: Vision-language models have become remarkably capable on images and short videos, yet they still struggle with two abilities central to embodied intelligence: spatial understanding and long-range temporal reasoning. A major reason is representational: today's models process videos as long sequences of 2D patches, so computation grows with observation length even when the underlying scene [...]