Faculty Candidate
Alessandro Roncone
Postdoctoral Scholar
Social Robotics Lab, Yale University

Faculty Candidate: Designing interactive algorithms for human-robot collaboration

NSH 3305

Areas of Interest: Robot control, human-robot interaction, artificial intelligence Abstract:   We are on the cusp of a fundamental revolution in how robotics at large will be consumed by and assimilated into our everyday life. In the next decade, state of the art robot platforms will become easier to deploy, more accessible to purchase, and [...]

RI Seminar
Naomi Ehrich Leonard
Professor
Mechanical and Aerospace Engineering , Princeton University

Bio-inspired dynamics for multi-agent decision-making

1305 Newell Simon Hall

Abstract: I will present distributed decision-making dynamics for multi-agent systems, motivated by studies of animal groups, such as house-hunting honeybees, and their extraordinary ability to make collective decisions that are both robust to disturbance and adaptable to change. The dynamics derive from principles of symmetry, consensus, and bifurcation in networked systems, exploiting instability as a [...]

Faculty Candidate
Judy Hoffman
Computer Science Postdoctoral Researcher
UC Berkeley

Faculty Candidate Talk: Adaptive Adversarial Learning for a Diverse Visual World

Newell-Simon Hall 3305

Areas of Interest: Computer vision and machine learning Abstract Automated visual recognition is in increasingly high demand. However, despite tremendous performance improvement in recent years, state-of-the-art deep visual models learned using large-scale benchmark datasets still fail to generalize to the diverse visual world. In this talk I will discuss a general purpose semi-supervised learning algorithm, [...]

VASC Seminar
Albert Ali Salah
Associate Professor
Boğaziçi University, Turkey

Multimodal, multilevel analysis of human behavior

Newell-Simon Hall 3305

Abstract: Computer analysis of human behavior is an interdisciplinary endeavor combining sensing technology, theoretical and empirical models of human behavior, pattern recognition and machine learning algorithms, and interaction sciences. The applications in this area range widely, from robotics to healthcare, from smart environments to multimedia, from security to humanitarian response. While human behaviors span different [...]

Faculty Candidate
Cathy Wu
PhD candidate
EECS, BAIR Lab, BDD, UC Berkeley

Faculty Candidate: Mixed-autonomy mobility: scalable learning and optimization

Newell-Simon Hall 3305

Areas of Interest: Learning, optimization, and control for mixed-autonomy mobility Abstract: How will self-driving cars change urban mobility? This talk describes contributions in machine learning and optimization critical for enabling mixed-autonomy mobility, the gradual and complex integration of automated vehicles into the existing transportation system. The talk first explores and quantifies the potential impact of [...]

Faculty Candidate
Manolis Savva
Postdoctoral Research Associate
Graphics Lab, Vision Lab, CS Department, Princeton University

Faculty Candidate: Human-centric Understanding of 3D Environments

Newell-Simon Hall 3305

Areas of Interest: Human-centric 3D Scene Analysis, Scene synthesis for 3D content creation and learning through simulation, Data visualization   Abstract: Creating 3D environments is hard. Experts spend much time and effort using complex software to create virtual 3D interiors. This 3D content creation bottleneck limits the use of virtual environments for applications in entertainment, [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Towards Generalization and Efficiency of Reinforcement Learning

GHC 4405

Abstract In classic supervised machine learning, a learning agent behaves as a passive observer: it receives examples from some external environment which it has no control over and then makes predictions. The predictions the agent made will not affect any future examples it will see (i.e., examples are identically and independently sampled from some unknown [...]

Faculty Candidate
David Fouhey
Postdoctoral Fellow,
EECS Department,, UC Berkeley

Faculty Candidate: Recovering a Functional and Three Dimensional Understanding of Images

NSH 3305

Areas of Interest: 3D Vision Abstract: What does it mean to understand an image? One common answer in computer vision has been that understanding means naming things: this part of the image corresponds to a refrigerator and that to a person, for instance. While important, the ability to name is not enough: humans can effortlessly [...]

Special Events
Research Professor / Associate Director of Education
Robotics Institute,
Carnegie Mellon University

AI Will Help Feed A Growing Planet

SXSW Austin, TX JW MARRIOTT SALON C, Austin, TX, United States

Video will be via Facebook Live on the CMU Facebook page. After the event has passed, the video will be here. By the year 2040, there will be more people on the planet than food to feed them. Researchers want to change that: a sustainable solution to the emerging world food crisis is sprouting in [...]