Magnetic Resonance Imaging (MRI) can be accelerated by sampling below the Shannon-Nyquist rate via compressed sensing techniques. In this talk, I will consider the problem of optimizing the under-sampling pattern in a data-driven fashion, which has been an open problem for over a decade. For a given sparsity constraint, our method optimizes the under-sampling pattern […]
Classical and quantum photonics with superior properties can be implemented in a variety of old (silicon, silicon nitride) and new (silicon carbide, diamond) photonic materials by combining state of the art optimization and machine learning techniques (photonics inverse design) with new fabrication approaches. In addition to making photonics more robust to errors in fabrication and […]
Open-source software has been a critical enabler for tremendous innovation in the software ecosystem over the past two decades. Inspired by this success, open-source hardware involves making the high-level description of hardware components freely available for others to study, change, distribute, and ultimately use in fabricating their own hardware components. Unfortunately, open-source hardware has had […]
This event is part of the Penn Institute for Immunology Colloquium seminar series and is co-hosted by the Department of Bioengineering. This virtual event will be held on Bluejeans. Attend the live seminar via this link. Or download the Bluejeans app and and enter ID: wxbzgity Contact ifiadmin@pennmedicine.upenn.edu with any questions. The adoptive transfer of […]
Abstract: Accurate atomistic computations of transport and reaction dynamics are an important challenge and an opportunity for designing materials for energy conversion and storage. In the context of thermoelectric materials, we develop new automatable computational methods for describing electron-phonon scattering dynamics. By predicting electrical transport properties, we computationally discovered several new low-cost thermoelectric alloys with […]
Miniaturized light sources are critical for next-generation on-chip photonic devices. Plasmon-based lasers and surface plasmon amplified spontaneous emission of radiation (spasers) have received significant attention since their prediction over a decay over a decade ago. Major advances have included subwavelength footprint sizes, room-temperature operation, far-field emission directionality, and understanding of the lasing mechanism. Notably, one […]
Abstract: Flagellated and motile bacteria, in isolation or in coexistence with fungi, are implicated in about two-thirds of human infections. During infection, and generally even in relatively benign situations, bacteria may colonize surfaces via a process called swarming – a form of rapid translocation associated with changes in cell phenotype. As swarmer cells move rapidly, they interact […]
Overparameterized neural networks have proved to be remarkably successful in many complex tasks such as image classification and deep reinforcement learning. In this talk, we will consider the role of explicit regularization in training overparameterized neural networks. Specifically, we consider ReLU networks and show that the landscape of commonly used regularized loss functions have the […]
The strong lottery ticket hypothesis (LTH) postulates that any neural network can be approximated by simply pruning a sufficiently larger network of random weights. Recent work establishes that the strong LTH is true if the random network to be pruned is a large poly-factor wider than the target one. This polynomial over-parameterization is at odds with […]
Abstract: Many tasks in fluid mechanics, such as design optimization and control, are challenging because fluids are nonlinear and exhibit a large range of scales in both space and time. This range of scales necessitates exceedingly high-dimensional measurements and computational discretization to resolve all relevant features, resulting in vast data sets and time-intensive computations. Indeed, […]
