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Past Events from September 29, 2020 - October 6, 2020 | Penn Engineering Events Page 179 Warning: session_start(): Session cannot be started after headers have already been sent in /home/seasevents/public_html/wp-content/themes/mast/functions/enqueue.php on line 27
Zoom - Email MEAM for Link
peterlit@seas.upenn.edu
Aluminum Nitride (AlN) is a well-established thin film piezoelectric material. AlN bulk acoustic wave (BAW) radio frequency (RF) filters were one of the key innovations that enabled the 3G and 4G smart phone revolution. Recently, the substitutional doping of scandium (Sc) for aluminum (Al) to form aluminum scandium nitride (AlScN) has been studied to significantly […]
A common theme among many models for spreading processes in networks is the assumption that the propagating object (e.g., a pathogen, in the context of infectious disease propagation, or a piece of information, in the context of information propagation) is transferred across network nodes without going through any modification. However, in real-life spreading processes, pathogens […]
Imagining a new Internet architecture enables us to explore new networking concepts without the constraints imposed by the current infrastructure. What are the benefits of a routing protocol that does not rely on convergence? What about a data plane without inter-domain forwarding tables on routers? How can we build secure systems if a router can […]
Orbital angular momentum (OAM) carried by structured vortex light establishes a new information dimension, thereby promising high capacity optical communication and high performance computation in both classical and quantum regimes. Meanwhile, laser is the key driver in the field of optics and photonics over other photonic components. Since its discovery, laser technology has demonstrated strong […]
Abstract Catalytic processes are central to the goal of a sustainable future. A promising approach in developing catalytic materials is represented by the design of catalytic sites based on the knowledge of reaction mechanisms and structure-property relationships and aided by computation, and in the precise synthesis of these sites at the atomic and molecular level. […]
To apply statistics and data science tools to aid computational designs of materials is under fast development. There are two unique aspects of the applications of these tools in materials science. First, the training sets are usually small. Second, physical mechanisms of material properties can be applied to facilitate the constructions of descriptors and statistics […]
This event will be held virtually on zoom. Check your email for the link and passcode or contact ksas@seas.upenn.edu. Systems biology approaches, including computational models, provide a framework to test biological hypotheses and optimize effective therapeutic strategies to treat human diseases. In this talk, I present recent work in modeling signaling in cancer-targeting immune cells, […]
Using the digital computer to simulate dynamic behavior of elastic and soft objects is a highly desired feature in many scientific and engineering areas: in computer animation, it provides realistic effects of soft characters; in surgical simulation, it delivers vivid visual experiences to the trainee; in digital fabrication, it couples geometry design and mechanical analysis. […]
Data-driven approaches match or outperform humans at a number of tasks, including pattern recognition in images and text or planning and strategy in rule-based games. The application of machine learning techniques is also promising for accelerating materials design. However, experimental data for training is typically scarce and sparse. The interplay between physics-based simulations and data-driven […]
“The DNA Damageome and Cancer” Physical Sciences in Oncology Center PSOC@Penn Fall 2020 Webinar Series Mondays @ Noon (EST) For webinar links, please contact manu@seas.upenn.edu
Zoom - Email MEAM for Link
peterlit@seas.upenn.edu
Wearable haptic devices have seen growing interest in recent years, but providing realistic tactile feedback is not a challenge that is soon to be solved. Daily interactions with physical objects elicit complex sensations at the fingertips. Furthermore, human fingertips exhibit a broad range of physical dimensions and perceptive abilities, adding increased complexity to the task […]
Zoom - Email MEAM for Link
peterlit@seas.upenn.edu
Model reduction methods have grown from the computational science community, with a focus on reducing high-dimensional models that arise from physics-based modeling, whereas machine learning has grown from the computer science community, with a focus on creating expressive models from black-box data streams. Yet recent years have seen an increased blending of the two perspectives […]