The PICS alumni Spotlight is an opportunity for students to learn from and network with alumni.
Abstract Engineering pathways across biological barriers is entering a new era with the rapid advancement of computational resources. My research group focuses on developing multi-scale simulation methods to elucidate the interfacial phenomena associated with biological barriers that play a role in life-threatening diseases, such as Alzheimer’s, cancer, and chronic infections. Our goal is to influence […]
The Materials Genome Initiative (MGI) has heralded a sea change in the philosophy of materials design. In an increasing number of applications, the successful deployment of novel materials has benefited from the use of computational, experimental and informatics methodologies. Here, we describe the role played by computational and experimental data generation and capture, polymer fingerprinting, […]
We shall examine in our talk concepts and tools for the analysis of social networks. We shall present in particular YouTube and Twitter. For YouTube, we point at shortcomings in ways to measure audience retention and propose new concepts to better quantify desirable properties. We then present a geo-linguistic analysis of Twitter based on daily […]
This event will be held virtually on zoom. Check email for zoom link or email ksas@seas.upenn.edu. CAR T cells—T cells engineered to express a chimeric antigen receptor that redirects their function to a specific antigen—have proven to be an effective therapy for certain B cell cancers, but many issues remain in order to apply CAR […]
Pixar's films rely heavily on physically simulated effects such as the motion of hairs, cloth, and water, to cite a few. Whereas physical accuracy is of paramount importance in engineering applications, the most important aspects of feature film productions are directability and speed. In this talk, I'll survey our recent work in this area, including […]
Many complex nonequilibrium systems, including turbulent flows, are characterized by chaotic dynamics, a large number of degrees of freedom, and hierarchical, multiscale structure in space and time. In two vignettes, we describe some recent work aimed at developing and applying machine learning and data science tools for systems displaying these characteristics. The first vignette builds […]
Abstract: Fluids and solids tend to be addressed using distinct computational perspectives. Solid deformation is most commonly simulated with Lagrangian finite-element methods, whereas fluid flow is amenable to Eulerian-frame approaches such as finite difference and finite volume methods. Problems that mix fluid and solid behaviors simultaneously present interesting numerical challenges. Here we focus on […]
Talk title TBC Physical Sciences in Oncology Center PSOC@Penn Fall 2020 Webinar Series Mondays @ Noon (EST) For webinar links, please contact manu@seas.upenn.edu
In this talk I will provide an overview of our recent work in data-driven methods---mainly machine learning---to enhance computational materials physics models. This body of work has proceeded along two main fronts. The first is system inference, where we seek to identify physical mechanisms via their mathematical signatures as differential or algebraic operators. Our approach […]
With the commercialization of wide-bandgap power semiconductors, multi-MHz switching frequencies are more compelling and critical to meet new applications demanding leaps in power density and efficiency. In the past, studies of these converters reported significant gaps between measured and modeled performance, often attributed to dynamic RDS,ON in GaN HEMTs. In particular, the power semiconductors – […]
A long-standing grand challenge in computing is to enable machines to act autonomously and intelligently: to rapidly and repeatedly take appropriate actions based on information in the world around them. Driven by trends in the data economy, rapid progress in AI, and an increasingly programmable physical world we are at an inflection point that demands […]