PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Contrastive View Predictive Learning with 3D-Bottlenecked RNNs

GHC 6115

Abstract: In this talk, I will describe our recent work on neural architectures for visual recognition, which use 3D not as input nor as the desired output space, but rather as the bottleneck of the learned representations. We consider embodied agents moving in otherwise static worlds equipped with these architectures; they learn 3D visual feature [...]

MSR Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Chao Cao – MSR Thesis Talk

Newell-Simon Hall 4305

Title: Topological Path Planning for Mobile Robot Applications   Abstract: Many path planning problems in mobile robot applications can be solved more efficiently in the topological space. By using the language of topology, the richer spatial information failed to captured by graph/grid-based map representations can be explicitly expressed and exploited. With that, it is possible [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk – Tao Chen

NSH 1109

Title: Deep Reinforcement Learning with Prior Knowledge   Abstract: Deep reinforcement learning has been applied to many domains from computer games, natural language processing, recommendation systems to robotics.  While model-free reinforcement learning algorithms are promising approaches to learning policies without knowledge of the system dynamics, they usually require much more data. In this thesis, we [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Towards Understanding and Mitigating Biases

NSH 3305

Abstract: There are many problems in real life that involve collecting and aggregating evaluation from people, such as conference peer review and peer grading. In this thesis, we consider multiple sources of biases that may arise in this process: (1) human bias -- the data collected from people are noisy and reflect people's calibration criteria [...]

PhD Speaking Qualifier
Extern
Robotics Institute,
Carnegie Mellon University

Toward Intent Recognition through Nonverbal Behaviors in Assistive Co-Manipulation

NSH 1109

Abstract: Robots are becoming more versatile, increasing the available opportunities to use them in situations that aid people in everyday tasks. For example, recent research has investigated robot manipulators for assisting people with motor impairments in activities of daily living such as eating a meal. To form successful collaborations in these interactions, researchers need to [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Anqi Yang – MSR Thesis Talk

NSH 4305

Title: 3D Object Detection from CT Scans using a Slice-and-fuse Approach   Abstract: Automatic object detection in 3D X-ray Computed Tomography imagery has recently gained research attention due to its promising applications in aviation baggage screening. The huge dimension of an individual 3D scan, however, poses formidable computational challenges when coupled with deep 3D convolutional [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Tian Ye – MSR Thesis Talk

NSH 4305

Title: Interpretable Intuitive Physics Model   Abstract: Humans have a remarkable ability to use physical commonsense and predict the effect of collisions. But do they understand the underlying factors? Can they predict if the underlying factors have changed? Interestingly, in most cases humans can predict the effects of similar collisions with different conditions such as changes [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Rotational Distributions for Pose Estimation

NSH 4305

Abstract: For robots to operate robustly in the real world, they should be aware of their uncertainty, particularly when estimating the position and orientation, or pose, of objects. This uncertainty can be caused by many factors, such as occlusions, poor lighting, or object symmetry. These factors can naturally induce an inherent ambiguity in terms of [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Hunter Goforth – MSR Thesis Talk

NSH 4305

Title: Learning for Registration in 2D and 3D   Abstract: We explore the application of deep learning to 2D (image) and 3D (point cloud) registration, especially in scenarios where traditional methods can fail.   In the 2D case, we apply a recently-proposed learning method to the problem of aligning outdoor imagery taken across different seasons or [...]