This talk will provide an overview of the COSMOS testbed (www.cosmos-lab.org), that is being deployed as part of the NSF Platforms for Advanced Wireless Research (PAWR) program, and the supported experiments in advanced wireless, millimeter-wave (mmWave), optical networking, and edge cloud. COSMOS (Cloud-Enhanced Open Software-Defined Mobile-Wireless Testbed for City-Scale Deployment) is being deployed in West Harlem (New York City) by Rutgers, Columbia, and NYU in partnership with NYC, CCNY, U. Arizona, IBM, and Silicon Harlem.
As society continues to charge through a computational revolution, it is imperative that a diverse range of disciplines and groups shape and influence the future of computing and its applications. To date, however, much of computing design, development, and implementation has been dominated by technocentric fields which lack diversity with respect to identity.
Understanding the properties of nuclear matter and its emergence through the underlying partonic structure and dynamics of quarks and gluons requires a new experimental facility in hadronic physics known as the Electron-Ion Collider (EIC). The EIC will address some of the most profound questions concerning the emergence of nuclear properties by precisely imaging gluons and quarks inside protons and nuclei such as their distributions in space and momentum, their role in building the nucleon spin and the properties of gluons in nuclei at high energies.
High-throughput screening (HTS) is a technology that rapidly and efficiently screens thousands of chemicals for potential activity across different types of biological endpoints. Our goal is to derive posterior probabilities of activity for each chemical by assay endpoint pair, addressing the sparsity of HTS data. We propose a Bayesian hierarchical framework, which borrows information across different chemicals and assay endpoints and facilitates out-of-sample prediction of bioactivity potential for new chemicals.
Please register here: https://duke.is/c89ey
In honor of Data Privacy Day 2022, we will be discussing with Professor Neil Richards his recent book "Why Privacy Matters." We will talk about what privacy means and "what privacy isn't," and explore the implications of our country's legal approach to privacy for freedom, democracy, and consumer protection in this information age.
This talk will discuss the technical challenges and theoretical foundations of controlling systems subject to constraints on their inputs and outputs, with a focus on their practical application to real-world problems. The talk will begin with an overview of invariant sets and model predictive control, which are two fundamental tools in constrained control. These tools will be demonstrated through their application to autonomous driving, advanced manufacturing, and cancer treatment. We will then discuss algorithms for real-time optimization and their application to battery cell balancing.