BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Penn Engineering Events - ECPv6.15.18//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Penn Engineering Events X-ORIGINAL-URL:https://seasevents.nmsdev7.com X-WR-CALDESC:Events for Penn Engineering Events REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20210314T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20211107T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20220313T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20221106T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20230312T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20231105T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/New_York:20221108T100000 DTEND;TZID=America/New_York:20221108T113000 DTSTAMP:20260405T181019 CREATED:20221019T133310Z LAST-MODIFIED:20221019T133310Z UID:10007337-1667901600-1667907000@seasevents.nmsdev7.com SUMMARY:Tedori-Callinan Lecture: "Mixing of Granular Materials\, Inertial Suspensions\, and Cement" DESCRIPTION:Flows of particulate materials are ubiquitous in nature and industry. Predictions of flow rates and mixing times rely on an understanding of the rheological properties of the materials\, which can differ considerably from that associated with a single-phase fluid. This presentation highlights some unique features of granular materials and inertial suspensions and includes recent experimental results. In addition\, the seminar overviews new work related to the mixing and gaseous diffusion in cement. Cement production releases significant amount of carbon dioxide; carbon dioxide can be partially reabsorbed into cement by diffusion through the multiphase material. The ongoing research includes modeling of the carbon dioxide uptake and considers ways to accelerate the process\, such as mixing with the cement paste. URL:https://seasevents.nmsdev7.com/event/tedori-callinan-lecture-mixing-of-granular-materials-inertial-suspensions-and-cement/ LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States CATEGORIES:Distinguished Lecture ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20221107T153000 DTEND;TZID=America/New_York:20221107T163000 DTSTAMP:20260405T181019 CREATED:20221027T124316Z LAST-MODIFIED:20221027T124316Z UID:10007344-1667835000-1667838600@seasevents.nmsdev7.com SUMMARY:ESE Fall Colloquium - "On the Principles of Parsimony and Self-Consistency: Structured Compressive Closed-Loop Transcription" DESCRIPTION:Ten years into the revival of deep networks and artificial intelligence\, we propose a theoretical framework that sheds light on understanding deep networks within a bigger picture of intelligence in general. We introduce two fundamental principles\, Parsimony and Self-consistency\, that address two fundamental questions regarding Intelligence: what to learn and how to learn\, respectively. We argue that these two principles can be realized in entirely measurable and computable ways for an important family of structures and models\, known as a linear discriminative representation (LDR). The two principles naturally lead to an effective and efficient computational framework\, known as a compressive closed-loop transcription\, that unifies and explains the evolution of modern deep networks and modern practices of artificial intelligence. Within this framework\, we will see how fundamental ideas in information theory\, control theory\, game theory\, sparse coding\, and optimization are closely integrated in such a closed-loop system\, all as necessary ingredients to learn autonomously and correctly. We demonstrate the power of this framework for learning discriminative\, generative\, and autoencoding models for large-scale real-world visual data\, with entirely white-box deep networks\, under all settings (supervised\, incremental\, and unsupervised). We believe that these two principles are the cornerstones for the emergence of intelligence\, artificial or natural\, and the compressive closed-loop transcription is a universal learning engine that serves as the basic learning units for all autonomous intelligent systems\, including the brain. \nRelated papers can be found at: https://arxiv.org/abs/2207.04630 and https://www.mdpi.com/1099-4300/24/4/456/htm URL:https://seasevents.nmsdev7.com/event/ese-fall-colloquium-on-the-principles-of-parsimony-and-self-consistency-structured-compressive-closed-loop-transcription/ LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States CATEGORIES:Colloquium ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20221107T130000 DTEND;TZID=America/New_York:20221107T140000 DTSTAMP:20260405T181019 CREATED:20220901T141104Z LAST-MODIFIED:20220901T141104Z UID:10007244-1667826000-1667829600@seasevents.nmsdev7.com SUMMARY:PSOC Seminar: “Bioengineered human brain microvascular network to model brain tumor and mechanobiology of glioma invasion" (Guohao Dai\, Northeastern University) DESCRIPTION:Fall 2022 Hybrid-Seminar Series \nMondays 1.00-2.00 pm (EST) \nTowne 225 / Raisler Lounge   \nFor Zoom link\, please contact