Upcoming Seminars

A new seminar hosted jointly between Physics and ORFE focusing on interdisciplinary work at the intersection of physics and machine learning.
What? A seminar series highlighting research on both physics-inspired approaches to understanding ML and the use of ML for physics applications
- AffiliationCCA, Flatiron Institute
- AffiliationVector Institute for Artificial Intelligence
- AffiliationUniversity of California San Diego
- AffiliationMIT Physics
- AffiliationPrinceton Physics and Neuroscience

A new seminar hosted jointly between Physics and ORFE focusing on interdisciplinary work at the intersection of physics and machine learning.
What? A seminar series highlighting research on both physics-inspired approaches to understanding ML and the use of ML for physics applications
- AffiliationCCA, Flatiron Institute
- AffiliationVector Institute for Artificial Intelligence
- AffiliationUniversity of California San Diego
- AffiliationMIT Physics
- AffiliationPrinceton Physics and Neuroscience

A new seminar hosted jointly between Physics and ORFE focusing on interdisciplinary work at the intersection of physics and machine learning.
What? A seminar series highlighting research on both physics-inspired approaches to understanding ML and the use of ML for physics applications
- AffiliationCCA, Flatiron Institute
- AffiliationVector Institute for Artificial Intelligence
- AffiliationUniversity of California San Diego
- AffiliationMIT Physics
- AffiliationPrinceton Physics and Neuroscience

A new seminar hosted jointly between Physics and ORFE focusing on interdisciplinary work at the intersection of physics and machine learning.
What? A seminar series highlighting research on both physics-inspired approaches to understanding ML and the use of ML for physics applications
- AffiliationCCA, Flatiron Institute
- AffiliationVector Institute for Artificial Intelligence
- AffiliationUniversity of California San Diego
- AffiliationMIT Physics
- AffiliationPrinceton Physics and Neuroscience

A new seminar hosted jointly between Physics and ORFE focusing on interdisciplinary work at the intersection of physics and machine learning.
What? A seminar series highlighting research on both physics-inspired approaches to understanding ML and the use of ML for physics applications
- AffiliationCCA, Flatiron Institute
- AffiliationVector Institute for Artificial Intelligence
- AffiliationUniversity of California San Diego
- AffiliationMIT Physics
- AffiliationPrinceton Physics and Neuroscience
Previous Seminars

Vladlen Koltun received his PhD in 2002 and has worked across multiple fields of computer science. He has mentored more than 50 PhD students, postdocs, research scientists, and PhD student interns, many of whom are now successful research leaders. Until 2021, he had served as the Chief Scientist for Intelligent Systems at Intel, where he built…

In the 1600s, Christiaan Hyugens realized that two pendulum clocks (an invention of his!) placed in the same wooden table eventually fall into synchrony. Since then, synchronization of coupled oscillators has been an important subject of study in classical mechanics and nonlinear dynamics. The Kuramoto model, proposed in the 1970s,…

Foundation models (ChatGPT, StableDiffusion) are transforming society: remarkable capabilities, serious risks, rampant deployment, unprecedented adoption, overflowing funding, and unending controversy. In this talk, we will center our attention on their societal impact. In the first half, we will discuss two efforts (HELM, Ecosystem Graphs) to…

Machine learning (ML) is being deployed to a vast array of real-world applications with profound impacts on society. ML can have positive impacts, such as aiding in the discovery of new cures for diseases and improving government transparency and efficiency. But it can also be harmful: reinforcing authoritarian regimes, scaling the spread of…

Machine learning algorithms are widely used for decision making in societally high-stakes settings from child welfare and criminal justice to healthcare and consumer lending. Recent history has illuminated numerous examples where these algorithms proved unreliable or inequitable. This talk will show how causal inference enables us to more…

Co-sponsored by the Department of Computer Science and the Department of Electrical and Computer Engineering
Users who wish to exercise privacy rights or make privacy choices must often rely on website or app user interfaces. However, too often, these user interfaces suffer from usability deficiencies ranging from being…

Rose Yu is an assistant professor at the University of California San Diego, Department of Computer Science and Engineering. Her research focuses on advancing machine learning techniques for large-scale spatiotemporal data analysis, with applications to sustainability, health, and physical sciences.
Lunch available at 12:00 p.m. Please RSVP to [email protected]

Co-sponsored by the Department of Computer Science and the Department of Electrical and Computer Engineering
The Arbitrum blockchain protocol started as a Princeton University research project, and has grown into a robust community hosting hundred of applications and over 600,000 monthly users. Along the way, the system has…

Co-sponsored by the Department of Computer Science and the Department of Electrical and Computer Engineering
Details: TBA
Bio:
Alessandro Acquisti is the Trustees Professor of Information Technology and Public Policy at the Heinz College, Carnegie Mellon University…

Please register here to attend in person.
Co-sponsored by the Department of Computer Science and the Department of Electrical and Computer Engineering
Computer security is traditionally about the protection of technology, whereas trust and safety…