PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Trustworthy Learning using Uncertain Interpretation of Data

GHC 6501

Abstract: Motivated by the potential of Artificial Intelligence (AI) in high-cost and safety-critical applications, and recently also by the increasing presence of AI in our everyday lives, Trustworthy AI has grown in prominence as a broad area of research encompassing topics such as interpretability, robustness, verifiable safety, fairness, privacy, accountability, and more. This has created [...]

RI Seminar
Anirudha Majumdar
Associate Professor
Mechanical and Aerospace Engineering, Princeton University

Robots That Know When They Don’t Know

1403 Tepper School Building

Abstract: Foundation models from machine learning have enabled rapid advances in perception, planning, and natural language understanding for robots. However, current systems lack any rigorous assurances when required to generalize to novel scenarios. For example, perception systems can fail to identify or localize unfamiliar objects, and large language model (LLM)-based planners can hallucinate outputs that [...]

VASC Seminar
Qitao Zhao
Master's Student
Computer Vision, Carnegie Mellon University

Sparse-view Pose Estimation and Reconstruction via Analysis by Generative Synthesis

3305 Newell-Simon Hall

Abstract:  This talk will present our approach for reconstructing objects from sparse-view images captured in unconstrained environments. In the absence of ground-truth camera poses, we will demonstrate how to utilize estimates from off-the-shelf systems and address two key challenges: refining noisy camera poses in sparse views and effectively handling outlier poses.   Bio:  Qitao is a second-year [...]

VASC Seminar
Vimal Mollyn
PhD Student
Human Computer Interaction Institute, Carnegie Mellon University

EgoTouch: On-Body Touch Input Using AR/VR Headset Cameras

3305 Newell-Simon Hall

Abstract:  In augmented and virtual reality (AR/VR) experiences, a user’s arms and hands can provide a convenient and tactile surface for touch input. Prior work has shown on-body input to have significant speed, accuracy, and ergonomic benefits over in-air interfaces, which are common today. In this work, we demonstrate high accuracy, bare hands (i.e., no special [...]

VASC Seminar
Hyunsung Cho
Ph.D. Student
Human-Computer Interaction Institute (HCII) , Carnegie Mellon University

Auptimize: Optimal Placement of Spatial Audio Cues for Extended Reality

3305 Newell-Simon Hall

Abstract:  Spatial audio in Extended Reality (XR) provides users with better awareness of where virtual elements are placed, and efficiently guides them to events such as notifications, system alerts from different windows, or approaching avatars. Humans, however, are inaccurate in localizing sound cues, especially with multiple sources due to limitations in human auditory perception such as [...]

MSR Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

VoxDet: Voxel Learning for Novel Instance Detection

NSH 3305

Abstract: Detecting unseen instances based on multi-view templates is a challenging problem due to its open-world nature. Traditional methodologies, which primarily rely on 2D representations and matching techniques, are often inadequate in handling pose variations and occlusions. To solve this, we introduce VoxDet, a pioneer 3D geometry-aware framework that fully utilizes the strong 3D voxel [...]

MSR Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Voxel Learning for Novel Instance Detection

Newell-Simon Hall 3305

Abstract: Detecting unseen instances based on multi-view templates is a challenging problem due to its open-world nature. Traditional methodologies, which primarily rely on 2D representations and matching techniques, are often inadequate in handling pose variations and occlusions. To solve this, we introduce VoxDet, a pioneer 3D geometry-aware framework that fully utilizes the strong 3D voxel [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Sensorimotor-Aligned Design for Pareto-Efficient Haptic Immersion in Extended Reality

GHC 4405

Abstract: A new category of computing devices is emerging: augmented and virtual reality headsets, collectively referred to as extended reality (XR). These devices can alter, augment, or even replace our reality. While these headsets have made impressive strides in audio-visual immersion over the past half-century, XR interactions remain almost completely absent of appropriately expressive tactile [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Evaluating and Improving Vision-Language Models Beyond Scaling Laws

GHC 6501

Abstract: In this talk, we present our work on advancing Vision-Language Models (VLMs) beyond scaling laws through improved evaluation and (post-)training strategies. Our contributions include VQAScore, a state-of-the-art alignment metric for text-to-visual generation. We show how VQAScore improves visual generation under real-world user prompts in GenAI-Bench. Additionally, we explore training methods that leverage the language [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Whisker-Inspired Sensors for Unstructured Environments

NSH 4305

Abstract: Robots lack the perception abilities of animals, which is one reason they can not achieve complex control in outdoor unstructured environments with the same ease as animals. One cause of the perception gap is the constraints researchers place on the environments in which they test new sensors so algorithms can correctly interpret data from [...]

RI Seminar
Nils Napp
Assistant Professor
Electrical and Computer Engineering, Cornell University

RI Seminar with Nils Napp

1403 Tepper School Building

RI Seminar
Axel Krieger
Associate Professor
Department of Mechanical Engineering, Johns Hopkins Whiting School of Engineering

RI Seminar with Axel Krieger

1403 Tepper School Building

Special Events

Robotics Institute Winter Party

All Robotics Institute Faculty. Staff, Students, and Visitors are invited to attend this event. Please join us for food, beverages, and casual conversation with colleagues. A calendar invite including details will be sent closer to the event.