PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Learning to create 3D content

NSH 4305

Abstract: With the popularity of Virtual Reality (VR), Augmented Reality (AR), and other 3D applications, developing methods that let everyday users capture and create their own 3D content has become increasingly essential. Current 3D creation pipelines often require either tedious manual effort or specialized setups with densely captured views. Additionally, many resulting 3D models are [...]

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 [...]

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 [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Strategy and Skill Learning for Physics-based Table Tennis Animation

Abstract: Recent advancements in physics-based character animation leverage deep learning to generate agile and natural motion, enabling characters to execute movements such as backflips, boxing, and tennis. However, reproducing the selection and use of diverse motor skills in dynamic environments to solve complex tasks, as humans do, still remains a challenge. We present a strategy [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Getting Optimization layers to play well with Deep Networks: Numerical methods and Architectures

NSH 4305

Abstract: Many real-world challenges, from robotic control to resource management, can be effectively formulated as optimization problems. Recent advancements have focused on incorporating these optimization problems as layers within deep learning pipelines, enabling the explicit inclusion of auxiliary constraints or cost functions, which is crucial for applications such as enforcing physical laws, ensuring safety constraints, [...]