RI Seminar
Dr. Michael Yip
Associate Professor
Dept. of Electrical and Computer Engineering, The University of California San Diego

Teaching a Robot to Perform Surgery: From 3D Image Understanding to Deformable Manipulation

1305 Newell Simon Hall

Abstract: Robot manipulation of rigid household objects and environments has made massive strides in the past few years due to the achievements in computer vision and reinforcement learning communities. One area that has taken off at a slower pace is in manipulating deformable objects. For example, surgical robotics are used today via teleoperation from a [...]

VASC Seminar
Yanxi Liu
Professor
Penn State University

Zeros for Data Science

Newell-Simon Hall 3305

Abstract: The world around us is neither totally regular nor completely random. Our and robots’ reliance on spatiotemporal patterns in daily life cannot be over-stressed, given the fact that most of us can function (perceive, recognize, navigate) effectively in chaotic and previously unseen physical, social and digital worlds. Data science has been promoted and practiced [...]

VASC Seminar
Agata Lapedriza
Principal Research Scientist/Professor
Northeastern University

Emotion perception: progress, challenges, and use cases

Newell-Simon Hall 3305

Abstract: One of the challenges Human-Centric AI systems face is understanding human behavior and emotions considering the context in which they take place. For example, current computer vision approaches for recognizing human emotions usually focus on facial movements and often ignore the context in which the facial movements take place. In this presentation, I will [...]

VASC Seminar
Yunzhu Li
Assistant Professor
University of Illinois Urbana-Champaign

Foundation Models for Robotic Manipulation: Opportunities and Challenges

Newell-Simon Hall 3305

Abstract: Foundation models, such as GPT-4 Vision, have marked significant achievements in the fields of natural language and vision, demonstrating exceptional abilities to adapt to new tasks and scenarios. However, physical interaction—such as cooking, cleaning, or caregiving—remains a frontier where foundation models and robotic systems have yet to achieve the desired level of adaptability and [...]

RI Seminar
Simon Lucey
Director, Australian Institute for Machine Learning (AIML)
Professor, University of Adelaide

Learning with Less

3305 Newell-Simon Hall

Abstract: The performance of an AI is nearly always associated with the amount of data you have at your disposal. Self-supervised machine learning can help – mitigating tedious human supervision – but the need for massive training datasets in modern AI seems unquenchable. Sometimes it is not the amount of data, but the mismatch of [...]

RI Seminar
Kim Baraka
Assistant Professor
Department of Computer Science, Vrije Universiteit Amsterdam

Why We Should Build Robot Apprentices And Why We Shouldn’t Do It Alone

1305 Newell Simon Hall

Abstract: For robots to be able to truly integrate human-populated, dynamic, and unpredictable environments, they will have to have strong adaptive capabilities. In this talk, I argue that these adaptive capabilities should leverage interaction with end users, who know how (they want) a robot to act in that environment. I will present an overview of [...]

RI Seminar
Jia Deng
Associate Professor
Department of Computer Science, Princeton University

Toward an ImageNet Moment for Synthetic Data

1305 Newell Simon Hall

Abstract:  Data, especially large-scale labeled data, has been a critical driver of progress in computer vision. However, many important tasks remain starved of high-quality data. Synthetic data from computer graphics is a promising solution to this challenge, but still remains in limited use. This talk will present our work on Infinigen, a procedural synthetic data [...]

VASC Seminar
Luca Weihs
Research Manager
Allen Institute for AI

Imitating Shortest Paths in Simulation Enables Effective Navigation and Manipulation in the Real World

Newell-Simon Hall 3305

Abstract: We show that imitating shortest-path planners in simulation produces Stretch RE-1 robotic agents that, given language instructions, can proficiently navigate, explore, and manipulate objects in both simulation and in the real world using only RGB sensors (no depth maps or GPS coordinates). This surprising result is enabled by our end-to-end, transformer-based, SPOC architecture, powerful [...]

SCS Distinguished Lecture
Jonathan Hurst
Co-Founder, Chief Robot Officer
Oregon State University, Agility Robotics

Teruko Yata Memorial Lecture

Human-Centric Robots and How Learning Enables Generality Abstract: Humans have dreamt of robot helpers forever. What's new is that this dream is becoming real. New developments in AI, building on foundations of hardware and passive dynamics, enable vastly improved generality. Robots can step out of highly structured environments and become more human-centric: operating in human [...]

VASC Seminar
Vishnu Lokhande
Assistant Professor
University at Buffalo, SUNY

Creating robust deep learning models involves effectively managing nuisance variables

Newell-Simon Hall 3305

Abstract: Over the past decade, we have witnessed significant advances in capabilities of deep neural network models in vision and machine learning. However, issues related to bias, discrimination, and fairness in general, have received a great deal of negative attention (e.g., mistakes in surveillance and animal-human confusion of vision models). But bias in AI models [...]