RI Seminar
Hadas Kress-Gazit
Associate Professor
College of Engineering, Cornell University

Formal Synthesis for Robots

Abstract: In this talk I will describe how formal methods such as synthesis – automatically creating a system from a formal specification – can be leveraged to design robots, explain and provide guarantees for their behavior, and even identify skills they might be missing. I will discuss the benefits and challenges of synthesis techniques and [...]

VASC Seminar
Thiemo Alldieck
PhD Candidate
Facebook Reality Labs

Reconstructing 3D Human Avatars from Monocular Images

GHC 6501

Abstract:  Statistical 3D human body models have helped us to better understand human shape and motion and already enabled exciting new applications. However, if we want to learn detailed, personalized, and clothed models of human shape, motion, and dynamics, we require new approaches that learn from ubiquitous data such as plain RGB-images and video. I [...]

RI Seminar
Assistant Professor
Robotics Institute,
Carnegie Mellon University

Extreme Motions in Biological and Engineered Systems

1305 Newell Simon Hall

Abstract: Dr. Temel’s work mainly focuses on understanding the dynamics and energetics of extreme motions in small-scale natural and synthetic systems. Small-scale biological systems achieve extraordinary accelerations, speeds, and forces that can be repeated with minimal costs throughout the life of the organism. Zeynep uses analytical and computational models as well as physical prototypes to learn about these systems, test [...]

VASC Seminar
Adriana Kovashka
Assistant Professor
University of Pittsburgh

Reasoning about complex media from weak multi-modal supervision

GHC 6501

Abstract:  In a world of abundant information targeting multiple senses, and increasingly powerful media, we need new mechanisms to model content. Techniques for representing individual channels, such as visual data or textual data, have greatly improved, and some techniques exist to model the relationship between channels that are “mirror images” of each other and contain [...]

RI Seminar
Raquel Urtasun
Chief Scientist & Head
Uber Advanced Technologies Group Toronto

CANCELLED

CIC Building Room 1201

VASC Seminar
Benjamin Schmidt
President and Co-Founder
RoadBotics

Building Trust in Real World Applications of Vision Based Machine Learning

GHC 6501

Abstract:  In all machine learning problems, there is an explicit trade off between cost and benefit. In real world vision problems, this optimization becomes increasingly difficult since those trade offs directly impact technology and product development as well as business strategy. For any successful business case, it is critical that the cost/benefit trade offs in [...]

VASC Seminar
Partha Pratim Talukdar
Associate Professor
IIScBangalore / Founder, KENOME

Knowledge Infused Deep Learning

Newell-Simon Hall 4305

Abstract:  This talk is motivated by the following thesis: Background knowledge is key to intelligent decision making. While deep learning methods have made significant strides over the last few years, they often lack the context in which they operate. Knowledge Graphs (and more generally multi-relational graphs) provide a flexible framework to capture and represent knowledge [...]

RI Seminar
Sarjoun Skaff
Co-Founder & CTO
Bossa Nova Robotics

Yes, That’s a Robot in Your Grocery Store. Now what?

CIC Building Room 1201

Abstract: Retail stores are becoming ground zero for indoor robotics. Fleet of different robots have to coexist with each others and humans every day, navigating safely, coordinating missions, and interacting appropriately with people, all at large scale. For us roboticists, stores are giant labs where we're learning what doesn't work and iterating. If we get [...]

VASC Seminar
Georgios Pavlakos
PhD Student
University of Pennsylvania

Learning to Reconstruct 3D Humans

GHC 6501

Abstract:  Recent advances in 2D perception have led to very successful systems, able to estimate the 2D pose of humans with impressive robustness. However, our interactions with the world are fundamentally 3D, so to be able to understand, explain and predict these interactions, it is crucial to reconstruct people in 3D. In this talk, I [...]

RI Seminar
Scott Niekum
Assistant Professor
Department of Computer Science, University of Texas at Austin

CANCELLED

Abstract: Before learning robots can be deployed in the real world, it is critical that probabilistic guarantees can be made about the safety and performance of such systems.  In recent years, safe reinforcement learning algorithms have enjoyed success in application areas with high-quality models and plentiful data, but robotics remains a challenging domain for scaling [...]