Current Schedule
Ottman TertulianoUniversity of Pennsylvania
“Learning from Bones to Build Better Alloys”
Every time you run or jump, your bones accumulate tiny cracks at the nanoscale. Most never become fractures, because bone is built as a hierarchy of structures, from nanoscale protein fibrils to cellular networks, each of which plays a role in slowing and redirecting damage. Using synchrotron X-rays capable of imaging structures a thousand times thinner than a human hair, we watch in real time how these structures interact with cracks before the body has a chance to repair them. It turns out the same hierarchical logic that makes bone tough can be borrowed to design better metals. We will discuss what bone has taught us about how structural materials fail, and how those lessons are showing up in next-generation 3D printed alloys.
Elizabeth RhoadesUniversity of Pennsylvania
“When Good Proteins Go Bad”
“Alzheimer’s and Parkinson’s diseases from the bottom up”
You may have heard about genetic factors that predispose people for developing neurodegenerative diseases like Alzheimer’s and Parkinson’s disease, but in the vast majority of cases there is not a known genetic cause. In fact, aging – which we are all doing – is the primary risk factor for developing these diseases. I will talk about what these diseases have in common, how they differ, and what we are doing to understand the very basic biology relevant to the diseases.
Andrea LiuUniversity of Pennsylvania
“AI without a Computer”
Artificial neural networks are everywhere now because they are so useful. They do everything from predicting the weather to writing essays and translating them into Urdu. Their abilities have exploded during the last dozen years because they have grown far bigger. Unfortunately, though, bigger neural networks require more energy to train and run. Our brains use only about a fifth of the calories we eat to learn and perform a far greater variety of tasks. How do the networks of neurons in our brains manage to do all this at low energy cost? The answer is that they doesn’t use a computer—they learn on their own. Neurons update their connections without knowing what all the other neurons are doing. We have developed an approach to learning that shares this key property. Our approach does not mimic the brain but exploits physics to learn and perform tasks for us. Using this approach, our collaborators have built physical systems that learn and perform AI tasks on their own. Our work establishes a new paradigm for scalable, energy-efficient learning.
Douglas DurianUniversity of Pennsylvania
“The Physics of Foam”
Everyone is familiar with a head of foam at the top of their beer glass, but do they understand the surprising properties of that foam? How can it be white and solid when it’s made mostly of gas and a little liquid, neither of which is white or solid? Douglas Durian will explain how foams change over time and some of the excitement they offer as a modern research topic in fundamental physics and mathematics.
Check out some past lectures on our Video Channel
