Special Events

Commencement Celebration

The Pittsburgh Golf Club 5280 Northumberland Street, Pittsburgh, PA, United States

Special Events

CMU Community Picnic

As shared during President Jahanian’s recent town hall discussions, the CMU Community Picnic is returning on May 18 (11:30 am to 1:30 pm). The Office of Human Resources, in partnership with Staff Council and the Office of the President, sponsors and organizes this yearly celebration as a thank you for the hard work and contributions [...]

Faculty Events
Raj Reddy Assistant Professor in Robotics
Robotics Institute,
Carnegie Mellon University

Generalization for Robot Learning In The Wild

Newell-Simon Hall 4305

Abstract: How can we train a robot that can generalize to perform thousands of tasks in thousands of environments? This question underscores the holy grail of robot learning, more generally machine learning, research. Current AI systems are incredibly specific in that they only perform the tasks they are trained for and are miserable at generalization. [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

On Sample-Efficient Reinforcement Learning for Nuclear Fusion

NSH 4305

Abstract: In many practical applications of reinforcement learning (RL), it is expensive to observe state transitions from the environment. For example, in the problem of plasma control for nuclear fusion, determining the next state for a given state-action pair requires querying an expensive transition function which can lead to many hours of computer simulation or [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Learning Strategies to Solve Real-World Physics Puzzles

Abstract: In this talk, I focus on efficient online learning for solving real-world physics puzzles. I discuss challenges associated with learning in this domain and how those challenges inform certain design decisions. In particular, learning from scratch in the real world would be difficult. I present a practical mixture of experts framework for learning strategies [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Towards Modular and Differentiable Autonomous Driving

NSH 4305

Abstract: The classical "modular and cascaded" autonomy stack (object detection, tracking, trajectory prediction, then planning and control) has been widely used for interactive autonomous systems such as self-driving cars due to its interpretability and fast development cycle. In this thesis, we advocate the use of such a modular stack but improve its accuracy and robustness [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Towards reconstructing non-rigidity from single camera

Abstract: In this proposal, we study how to infer 3D from images captured by a single camera, without assuming the target scenes / objects being static. The non-static setting makes our problem ill-posed and challenging to solve, but is vital in practical applications where target-of-interest is non-static. To solve ill-posed problems, the current trend in [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Control Input and Natural Gaze for Goal Prediction in Shared Control

GHC 4405

Abstract: Teleoperated systems are used widely in deployed robots today, for such tasks as space exploration, disaster recovery, or assisted manipulation. However, teleoperated systems are difficult to control, especially when performing high-dimensional, contact-rich tasks like manipulation. One approach to ease teleoperated manipulation is shared control; this strategy combines the user's direct control input with an [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Forecasting from LiDAR via Future Object Detection

NSH 3305

Abstract: Object detection and forecasting are fundamental components of embodied perception. These two problems, however, are largely studied in isolation by the community. In this paper, we propose an end-to-end approach for detection and motion forecasting based on raw sensor measurement as opposed to ground truth tracks. Instead of predicting the current frame locations and [...]