RI Seminar
Lining Yao
Assistant Professor
Human-Computer Interaction Institute (HCII), Carnegie Mellon University

Robotic Morphing Matter

1305 Newell Simon Hall

Abstract: Morphing matter harnesses the programmability in material structures and compositions to achieve transformative behaviors and integrates sensing, actuation, and computation to create adaptive and responsive material systems. These material systems can be leveraged to design soft robots, self-assembling furniture,  adaptive fabrics, and self-folding foods. In this talk, Lining presents the recent works in the [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Robust Active SLAM for Real-time Large-scale Indoor Dense 3D Reconstruction

GHC 4405

Abstract: Real-time dense 3D reconstruction of indoor environments has been a popular research field due to its wide application, such as inspection, virtual / augmented reality (VR/AR), and service robotics. While many state-of-the-art algorithms are capable of reconstructing accurate 3D dense models in general indoor scenes, robustness is still an unsolved problem for all of [...]

Faculty Candidate
Yuke Zhu
Ph.D. candidate
Department of Computer Science, Stanford University

Faculty Candidate: Yuke Zhu

Gates Hillman Center 6115

Talk: Closing the perception-action loop Abstract: Robots and autonomous systems have been playing a significant role in the modern economy. Custom-built robots have remarkably improved productivity, operational safety, and product quality. However, these robots are usually programmed for specific tasks in well-controlled environments, unable to perform diverse tasks in the real world. In this talk, I will [...]

RI Seminar
Robert J. Wood
Professor
School of Engineering & Applied Sciences, Harvard

The Mechanical Side of Artificial Intelligence

1305 Newell Simon Hall

Abstract: Artificial Intelligence typically focuses on perception, learning, and control methods to enable autonomous robots to make and act on decisions in real environments. On the contrary, our research is focused on the design, mechanics, materials, and manufacturing of novel robot platforms that make the perception, control, or action easier or more robust for natural, unstructured, and [...]

Faculty Candidate
Deepak Pathak
Ph.D. candidate
Computer Science, UC Berkeley

Self-Directed Learning

Newell-Simon Hall 3305

Abstract: Generalization, i.e., the ability to adapt to novel scenarios, is the hallmark of human intelligence. While we have systems that excel at recognizing objects, cleaning floors, playing complex games and occasionally beating humans, they are incredibly specific in that they only perform the tasks they are trained for and are miserable at generalization. In [...]

Faculty Candidate
Jiajun Wu
Ph.D. student
Electrical Engineering and Computer Science, Massachusetts Institute of Technology

Learning to see the physical world

Newell-Simon Hall 3305

Abstract: Human intelligence is beyond pattern recognition. From a single image, we're able to explain what we see, reconstruct the scene in 3D, predict what's going to happen, and plan our actions accordingly. In this talk, I will present our recent work on physical scene understanding---building versatile, data-efficient, and generalizable machines that learn to see, reason about, and interact [...]

Faculty Candidate
Jun-Yan Zhu
Postdoctoral Researcher
MIT CSAIL

Learning to Synthesize Images

Gates Hillman Center 6115

Abstract: People are avid consumers of visual content. Every day, we watch videos, play games, and share photos on social media. However, there is an asymmetry – while everybody is able to consume visual content, only a chosen few (e.g., painters, sculptors, film directors) are talented enough to express themselves visually. For example, in modern [...]