Student Talks
Accessible Dexterous Manipulation with Soft Hands: Designs, Methods, Models, and the DexKit Platform
Abstract: Robot dexterity remains an open challenge in robotics that has the potential to transform manufacturing, healthcare, and daily life. Robots that safely and robustly interact with unstructured environments must combine compliant hardware with models and planners that tolerate uncertainty. Additionally, if robust robot dexterity is to be realized outside of research labs, it must [...]
Unlock Robust Spatial Perception: Towards Resilient State Estimation and Mapping for Long-Term Autonomy
Abstract Autonomous robots should maintain resilient spatial perception despite sensor degradation. Humans preserve spatial awareness when moving between well-lit and dark spaces or when vision is partially occluded. Neuroscience studies suggest this robustness relies in part on a proprioception-first sensory hierarchy: the vestibular system provides continuous inertial reference signals, while vision supplies corrective updates that [...]
Bring a Hand to The Sky: Towards Universal Aerial Manipulation
Abstract: Uncrewed Aerial Vehicles (UAVs) have attracted significant attention in applications such as inspection and maintenance. Many of these tasks require aerial robots to physically interact with the environment, motivating the emerging field of aerial manipulation. However, most existing approaches focus on a single task with specialized hardware and control strategies, limiting their ability to [...]
Robust, Reliable Robot Odometry and its Certification
Abstract: Robot odometry is the backbone of nearly all modern autonomous systems including, but not limited to, unmanned aerial vehicles, autonomous underwater vehicles, and autonomous ground vehicles. Most downstream tasks such as path planning, perception, and control require accurate knowledge of the vehicle position and orientation at any given moment. While odometry is well-studied and [...]
Human-System Communications for Expectation Mismatch
Abstract: Robots, and autonomous systems in general, are becoming increasingly advancing beyond traditional functions. This can potentially facilitate the mismatch between human expectations of system behaviors during interaction, especially when the systems behave unexpectedly. Unexpected system behaviors could induce negative emotional responses in humans, which not all systems have the capability of recognizing and detecting [...]
RI PhD Thesis Defense – Brian Yang
Date: 30th March 2026 Time: 10:00 a.m. (ET) Location: NSH 3305 Zoom: Link Type: Ph.D. Thesis Defense Who: Brian Yang Title: A Language-Guided Generative Data Engine for Autonomous Driving Abstract: Autonomous driving systems struggle with the long tail of rare and safety-critical scenarios that are sparsely represented in real-world data. While recent learning-based planners perform well on common situations, their reliability [...]
Regression-based Multi-view Face Synthesis
Abstract: Synthesizing photorealistic human faces from novel viewpoints using only a single frontal image remains a challenging problem in computer vision. Large viewpoint changes introduce geometric distortions, self-occlusions, and missing visual information, making identity preservation and high-frequency detail reconstruction particularly difficult. While recent generative approaches such as diffusion models and 3D-aware neural representations produce visually [...]
RI PhD Thesis Defense – Ananya Rao
Who: Ananya Rao Date: Friday, April 3rd Time: 10 AM ET Location: NSH 3305 Zoom Link Meeting ID: 949 1271 6317 Passcode: 809985 Title: Spectral-Based Coordination of Heterogeneous Multi-Agent Teams for Information Gathering Abstract: Extreme environments, such as those encountered in planetary exploration or disaster response, present complex, time-sensitive tasks with significant uncertainty. In such settings, heterogeneous [...]
RI Ph.D. Thesis Defense – Mrinal Verghese
Date: 7th April 2026 Time: 10:00 a.m. (ET) Location: NSH 3305 Zoom: Link Type: Ph.D. Thesis Defense Who: Mrinal Verghese Title: Strategies for Robot Learning from Human Data Abstract: Robot learning is fundamentally data-constrained. Internet-scale human data is a promising source of additional data about human environments, tasks, and common skills. This data comes in diverse representations, such as human videos [...]
RI PhD Defense – Neehar Peri
Date: April 7th, 2026 Time: 3:30 PM (ET) Location: NSH 3305 Zoom Link Type: Ph.D. Thesis Defense Who: Neehar Peri Title: Towards Scalable Open-World 3D Perception Abstract: State estimation is a fundamental component of embodied perception. For safe navigation, we argue that robots (and autonomous vehicles (AVs) specifically) must detect, track, and forecast all object categories, not just those [...]