MSE Seminar: “Compressibility of Nanoconfined Fluids: Relating Atomistic Modeling to Ultrasonic Experiments”
2022-12-08 10:30 - 11:30 (America/New_York) | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Fluids confined in nanopores are ubiquitous in nature and technology. In recent years, the interest in confined fluids has grown, driven by research on unconventional hydrocarbon resources — shale gas and shale oil, much of which are confined in nanopores. When fluids are confined in nanopores, many of their properties differ from those of the same fluid in the bulk. These properties include density, freezing point, transport coefficients, thermal expansion coefficient, and, as it was shown recently [1], elastic properties.
The elastic modulus of a fluid confined in the pores contribute to the overall elasticity of the fluid-saturated porous medium and determine the speed at which elastic waves traverse through the medium. In this talk I will show how elastic modulus of a confined fluid in a nanopore can be calculated based on Monte Carlo and molecular dynamics simulations and illustrate it with calculations for various fluids [2]. Additionally, I will present our recent experimental measurements of elastic properties of water confined in nanoporous glass samples. Our results suggest that some of the models widely used for describing elasticity of fluid-saturated porous solids need to be revised [3].
[1] Dobrzanski, C. D.; Gurevich, B.; Gor, G. Y. “Elastic Properties of Confined Fluids from Molecular Modeling to Ultrasonic Experiments on Porous Solids” Appl. Phys. Rev. 2021, 8, 021317, DOI: 10.1063/5.0024114
[2] Maximov, M. A.; Gor, G. Y. “Molecular Simulations Shed Light on Potential Uses of Ultrasound in Nitrogen Adsorption Experiments” Langmuir 2018, 34(51), 15650-15657, DOI: 10.1021/acs.langmuir.8b02909
[3] Gor, G. Y.; Gurevich, B. “Gassmann Theory Applies to Nanoporous Media” Geophys. Res. Lett., 2018, 45(1), 146-155, DOI: 10.1002/2017GL075321

ESE Fall Colloquium - "On compression of, for, and with neural networks"
2022-12-08 12:30 - 13:30 | Zoom – Meeting ID 971 2264 9281
Data compression is enjoying a renaissance fueled by an unprecedented growth in both the amount of data being generated and our reliance on powerful computation. At its heart is an increasingly intricate interplay between compression, artificial neural networks, and (our) biological neural networks. I will survey some related research in which I have been involved, and conclude with thoughts about future research.

MEAM Ph.D. Thesis Defense: "An Aquatic Underactuated Modular Self-Reconfigurable Robotic System for Information-Limited Navigation in Gyre-Like Flows"
2022-12-08 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Aquatic modular self-reconfigurable robotic systems (MSRRs) have incredible potential for bringing practical, flexible, and adaptable robotic tools to challenging environments. They could build mobile ocean platforms or bridges for larger vehicles, act as ocean-going manipulators to perform repairs on infrastructure, or function as oceanographic research platforms, using reconfiguration to achieve precise spatial resolution when sensing or to improve energy efficiency when traveling over large distances.
Development of aquatic MSRRs, however, is limited by the assumption that modules need to be capable of holonomic actuation, which makes them complex and expensive. This work challenges this limitation, presenting a novel underactuated aquatic robot called the Modboat that uses a single motor and passive flippers for propulsion and steering, and developing a capable aquatic MSRR that can dock, undock, reconfigure, and move as a collective using Modboats as its modules.
Aquatic systems are further limited because conventional techniques assume that full flow models are needed to use ocean currents for navigation. Such flow models are rarely available, so practical deployments are limited to high thrust and energy-capacity systems. This dissertation challenges this assumption, demonstrating that limited knowledge of ocean gyres can be used for energy-efficient navigation even by low-thrust systems, and that this navigation can significantly expand the operational range of energy-limited robotic systems. Modboat modules are used to verify these results as an example underactuated and low-power robot.

Grace Hopper Distinguished Lecture: "How Memory Guides Value-Based Decisions" (Daphna Shohamy, Columbia University)
2022-12-08 15:30 - 16:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
This distinguished lecture will be a hybrid event held in the Glandt Forum (Singh Center) and via Zoom. A light reception will follow the live lecture.
Zoom link
Passcode: [REDACTED]
“How Memory Guides Value-Based Decisions”
From robots to humans, the ability to learn from experience turns a rigid response system into a flexible, adaptive one. In the past several decades, major advances have been made in understanding how humans and other animals learn from experience to make decisions. However, most of this progress has focused on rather simple forms of stimulus-response learning, such as automatic responses or habits. In this talk, I will turn to consider how past experience guides more complex decisions, such as those requiring flexible reasoning, inference, and deliberation. Across a range of behavioral contexts, I will demonstrate a critical role for memory in such decisions and will discuss how multiple brain regions interact to support learning, what this means for how memories are used, and the consequences for how decisions are made. Uncovering the pervasive role of memory in decision-making challenges the way we think about what memory is for, suggesting that memory’s primary purpose may be to guide future behavior and that storing a record of the past is just one way to do so.
In support of its educational mission of promoting the role of all engineers in society, the School of Engineering and Applied Science presents the Grace Hopper Lecture Series. This series is intended to serve the dual purpose of recognizing successful women in engineering and of inspiring students to achieve at the highest level. Grace Hopper is a wonderful example of a visionary in her field who exhibited the type of pioneering spirit that is an inspiration to all of us.
In support of the accomplishments of women in engineering, departments within the School invite a prominent speaker to campus for a visit that incorporates a public lecture, various mini-talks and opportunities to interact with students and faculty. This series provides another avenue for recognition of distinguished leaders in engineering and presents role models that help remind all of us why we chose this profession.

CIS Seminar: " Exploring the role of scientific machine learning in electric power system decarbonization"
2022-12-08 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Electric power systems lie at the heart of efforts to mitigate and adapt to the effects of climate change. Mitigation requires shifting electricity generation away from carbon-emitting technologies toward zero carbon sources such as wind and solar generation, and converting energy end uses like transportation and space conditioning to use that electricity. Adaptation requires designing electricity infrastructure to withstand extreme weather conditions, including heat waves, hurricanes, and wildfire. Computing and data sit at the heart of planning for these changes so that they are cost effective and reliable. This talk will survey three challenges in this space, namely, (i) ensuring power system stability in the face of massive changes in generation infrastructure, (ii) exploring the scope of infrastructure change required to reliably serve millions of electrified cars and buildings and (iii) quantifying the risk of wildfire caused by millions of pieces of electricity infrastructure, and the risk reduction achieved by a suite of possible upgrades to that infrastructure. In the course of the survey, the talk will discuss how machine learning tools — including state of the art scientific machine learning principles — can be brought to bear on these problems.

Fall 2022 GRASP on Robotics: David Fouhey, University of Michigan, "Understanding the Physical World from Images"
2022-12-09 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom.

ABSTRACT
If I show you a photo of a place you have never been to, you can easily imagine what you could do in that picture. Your understanding goes from the surfaces you see to the ones you do not, like parts that are hidden behind furniture. Your understanding even enables reasoning about how the scene could be if someone interacted with it, for instance by opening a cabinet. My research aims to give computers this same level of physical understanding. I believe that this physical understanding will be critical for autonomous agents, as well as for enabling new insights in research fields that vision does not often interact with: progress on many problems across the sciences and humanities can be accelerated by being able to robustly measure some quantity at scale.

My talk will show my research group’s work towards the goal of understanding the physical world from images. I will first show how we can reconstruct 3D scenes, including invisible surfaces, from a single RGB image. We have developed an approach that learns to predict a scene-scale implicit function using realistic 3D supervision that can be gathered by consumers or robots instead of by using artist-created watertight 3D assets. After showing reconstructions of our system in everyday scenarios, I will talk about how measuring the world can unlock new insights in science, from millimeter-sized bird bones to solar physics data where a pixel is a few hundred miles wide. I will conclude by showing work towards understanding how humans can interact with objects, including work on understanding hands and the objects they hold.

PICS Colloquium: "From Molecular Vibrations to Solvation, Protein Dynamics and Models of the Cytoplasm"
2022-12-09 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Abstract: Vibrational spectroscopies at mid-infrared frequencies provide excellent probes to characterize functional groups and their immediate chemical environment. However, from a thermodynamic and dynamic point of view, only the ground state of these vibrations is significantly populated. Most of the “jiggling and wiggling” of atoms and molecules (referred to in the famous quote by Feynman) happens at lower frequencies in the far-infrared, where vibrations are easily excited by thermal collisions.
The Heyden research group develops methods to characterize and extract information from far-infrared vibrations in molecular dynamics simulations of biomolecular systems: 1) We develop methods that eliminate the need for harmonic and quasi-harmonic approximations in the analysis of collective vibrational modes and their contributions to vibrational spectra. 2) We use intermolecular vibrations of the water-hydrogen bond network to generate detailed 3D maps of protein hydration free energies and water-mediated interactions. 3) We use such 3D maps to generate implicit solvation models that enable realistic simulations of large biomolecular systems including many interacting proteins.
Each of these methods has its own applications, but combined they allow us to develop computationally efficient models of complex biomolecular environments such as the cytoplasm. We developed a multi-conformation Monte Carlo algorithm that uses input from existing molecular dynamics simulation trajectories to generate new simulation models of systems containing 100’s of interacting flexible proteins at very low computational cost. This allows us to analyze consequences of biomolecular crowding in a multitude of scenarios, which remain inaccessible to direct molecular dynamics simulations.

Fall 2022 MEAM 5200: Block Stacking Challenge!
2022-12-11 12:00 - 16:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom.

ABSTRACT

Teams of 3-4 students will compete head-to-head in a block stacking challenge as their class final project for MEAM 5200: Introduction to Robotics. Each team controls one 7 DOF Franka-Emika Panda manipulator arm using their modeling/planning skills and gaming strategy. The team that stacks the most blocks wins!
Come cheer on your classmates at the MEAM 5200 stacking competition in person or via zoom!
12:00pm-2pm (Qualifiers)

2:30pm-4pm (Knock-outs)

PSOC Seminar: “Validation of a bicistronic CAR to overcome intratumoral heterogeneity in GBM” (Zev Binder, PSOM)
2022-12-12 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Fall 2022 Hybrid-Seminar Series
Mondays 1.00-2.00 pm (EST)
Towne 225 / Raisler Lounge
For Zoom link, please contact <manu@seas.upenn.edu

Fall 2022 GRASP Seminar: Nare Karapetyan, University of Maryland, "Area Coverage Path Planning: From Graphs to Field Deployments"
2022-12-14 11:00 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Levine 307 and virtual attendance via Zoom.

ABSTRACT
Area coverage path planning is the problem of finding an efficient path that traverses the region of interest while avoiding existing obstacles. When dealing with real systems, the dynamic changes and uncertainties of the environments increase the state space exponentially and make these problems intractable. As such, exploiting the inherent geometric properties of the areas allows for redefining planning as a combinatorial optimization task. This helps to reduce the overhead complexity of the problem and break it into manageable subproblems for handling uncertainties.
In this talk, we will discuss a two-phase approach for generating a complete pipeline of robust exploration/coverage plans: (i) generate a global coverage plan and (ii) incorporate dynamic changes to adjust the plan. We will specifically discuss different coverage strategies for single and multi-robot systems that take into account obstacles and implicit geological properties of the environment and perform effective data collection suitable to the deployed sensors. We will also discuss how to incorporate uncertainties within these plans. Moreover, we will also see these methods deployed in the real world, automating scientific sampling operations.

ASSET Seminar: ML for Causal Inference, Konrad Kording, University of Pennsylvania
2022-12-14 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT
Machine learning traditionally does not get at causality and causality research traditionally treats machine learning as a dangerous set of highly biased estimators. In my talk I will talk about our lab’s efforts to use machine learning as a component of more traditional quasi-experimental techniques. I will also discuss meta-learning approaches to causal inference, approaches where the estimators themselves are learned. I will lament the relative lack of interactions between the various subfields of the causal inference space.

ESE Fall Colloquium: "Electronics 5.0: New Materials and Devices for Edge Intelligence"
2022-12-14 12:30 - 13:30 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The end of traditional transistor scaling brings unprecedented new opportunities to semiconductor devices and electronics. We are at the onset of a new technology revolution, which will focus on distributed intelligence and will be pushing the limits of sensing and computing at the edge of the cloud. This seminar will describe some of our work on new materials and devices to enable this vision, including 1. Gallium Nitride CMOS FinFET amplifiers for much more efficient communications; 2. One-layer-thick molybdenum disulfide wi-fi energy harvesters to enable ubiquitous electronics; and 3. A new generation of cell-sized autonomous electronic microsystems to revolutionize invisible sensing. The seminar will conclude with a reflection on how the democratization of heterogeneous integration, the unique properties of extreme materials and the opportunities of distributed intelligence will transform our society just as Moore’s law has done for the last 50 years.

ESE Fall Colloquium - "From Brains to Bandgaps: How Novel Materials Synthesis can provide New Semiconductor Platforms for Optoelectronics, Acoustics, Electronics and Neuromorphic Computation"
2022-12-15 12:30 - 13:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Since the first discovery of semiconductors, materials synthesis has been the driving force for new devices, new applications, and new markets. In this presentation, Professor Doolittle will provide two examples of “counterculture synthesis methods”, methods that buck literature tradition, that enable new devices, applications, and potentially vast new markets. Emphasis will be given to non-standard methods that have more sound physical reasoning than commonly practiced methods. The first example will be the recent advances in AlN and AlScN semiconductor synthesis. Aluminum Nitride (AlN) is an over 80-year-old insulator that has to date, shown little promise to be converted to a semiconductor via doping because of well-known compensation and defect formation. By using low temperature crystal synthesis methods that run counter to common practice and by using new dopant elements, we demonstrate: a) for the first time well behaved bulk semiconducting functionality in AlN making it the largest direct bandgap semiconductor demonstrated; b) substantial bulk p-type conduction (first-time demonstration, holes=3.1×1018 cm-3); c) dramatic improvement in n-type conduction (electrons=6×1018 cm-3, nearly 6000 times the state-of-the-art); d) the first PN AlN diode with a nearly ideal turn-on voltage of ~6 V for a 6.1 eV bandgap semiconductor and ~six decades of current rectification. Likewise, low temperature AlScN synthesis methods produce high quality structures that could transform RF and power switching electronics as well as have impact for acoustic devices. The understanding of this advance is in its infancy and present limitations will be discussed. A wide variety of AlN-based applications should be enabled that will revolutionize deep ultraviolet light-based viral and bacterial sterilization, lithography, laser machining, high-temperature, high-voltage, and high-power electronics. The second example is a new neuromorphic computing platform that offers engineering solutions not afforded in competing platforms. By dynamically changing the density of states of materials by intercalation of dopants, bio realistic computation and memory are enabled via a diverse family of new, scalable devices. Moving beyond simple resistance changes industry has perfected, demonstrations will be given on how an engineer can design chrono-memristance devices with volatile, non-volatile, and mixed volatility, tunable resistance and tunable temporal responses, analog resistance changes exceeding the state of the art and remarkably low programing voltage/energy (below 100 mV) that compute without the need for individual device addressing – just as the brain computes.

BE Doctoral Dissertation Defense of Christopher Olm: "In vivo MRI perfusion and structural correlates of pathology in frontotemporal lobar degeneration"
2022-12-16 10:00 - 12:00 | PA
The Department of Bioengineering at the University of Pennsylvania and Drs. Murray Grossman and Jim Gee are pleased to announce the Doctoral Dissertation Defense of Christopher Olm.

Title: In vivo MRI perfusion and structural correlates of pathology in frontotemporal lobar degeneration
Date: December 16, 2022
Time: 10:00 AM – 12:00 PM
Location: TBD
Zoom: https://upenn.zoom.us/j/7372154022

The public is welcome to attend.

Fall 2022 Robotics Master's Thesis Presentation
2022-12-16 10:30 - 11:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Levine 307 and virtual attendance via Zoom.

Welcome Remarks
Dr. Ani Hsieh – ROBO Program Graduate Chair
Arjun Nanda
Advised by Dr. Pratik Chaudhari
“Vision based object aware radiance field priors for single shot 3D reconstruction”
Shaoming Zheng
Advised by Dr. Jianbo Shi
“2D-Supervised Single-View 3D Reconstruction with Latent Diffusion“

BE Doctoral Dissertation Defense of Margaret Billingsley: "Ionizable Lipid Nanoparticles for mRNA CAR T Cell Engineering"
2022-12-16 14:00 - 16:00 | Towne 337
The Department of Bioengineering at the University of Pennsylvania and Dr. Mike Mitchell are pleased to announce the Doctoral Dissertation Defense of Margaret Billingsley.

Title: Ionizable Lipid Nanoparticles for mRNA CAR T Cell Engineering
Date: December 16, 2022
Time: 2:00 PM
Location: Towne 337
Zoom option: https://upenn.zoom.us/j/95255561059?pwd=[REDACTED]
Meeting ID: 952 5556 1059
Passcode: [REDACTED]

The public is welcome to attend.

Fall 2022 MEAM 5100: Grand Theft Autonomous Challenge - Day 1
2022-12-17 12:00 - 16:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom.
Please join us live on YouTube, on Zoom, or in Wu and Chen to see the MEAM 5100: Mechatronics class compete in the Grand Theft Autonomous Challenge. Teams are tasked with building a robot which: senses, navigates to, and maneuvers different game pieces to score points. This multi-day event will push each team’s design, software, and electronics stack to the limit. Come and see which robots are left standing!
Day 1: Seed Rounds

Fall 2022 MEAM 5100: Grand Theft Autonomous Challenge - Day 2
2022-12-18 12:00 - 16:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom.
Please join us live on YouTube, on Zoom, or in Wu and Chen to see the MEAM 5100: Mechatronics class compete in the Grand Theft Autonomous Challenge. Teams are tasked with building a robot which: senses, navigates to, and maneuvers different game pieces to score points. This multi-day event will push each team’s design, software, and electronics stack to the limit. Come and see which robots are left standing!
Day 2: Knockout Rounds

ESE PhD Thesis Defense: "Integrated photonic-assisted electronics for phased array beamforming and delay control"
2022-12-20 13:00 - 14:30 | Towne 337
In recent years, electronic-photonic co-design and co-integration has emerged as a disruptive technology to augment the power of integrated circuits and deliver enhanced chip scale solutions for a variety of applications ranging from communication and sensing to imaging and computation. Coupled with the versatility of electronics, integrated photonic techniques may be employed to assist in the generation, distribution and or processing of electrical signals. Benefitting from the advancements in CMOS-compatible silicon photonics, this dissertation presents system architectures, design details, analysis, and measurement results for three integrated photonic-assisted electronic systems. The first system presented is a delay controlled optoelectronic oscillator comprised of an integrated, rapidly tunable, optical delay line. The oscillator exhibits a relatively flat modulation response at high frequencies accommodating wideband fast frequency chirp generation pertinent to frequency modulated continuous-wave radar systems and imagers. The second system presented is a photonic assisted integrated phased array transmitter applicable for low-power, compact radio heads in fiber to mm-wave fronthaul links. Without the use of any mm-wave active components, data streams with bitrates as high as 2.5Gb/s are transmitted over 3.6km of optical fiber, directly placed on an mm-wave carrier, and wirelessly transmitted attaining bit-error rates better than 10-11. The third system presented is a mm-wave phased array transmitter utilizing free-space optics and integrated photonics for the distribution of a 28GHz RF signal eliminating lossy board-level mm-wave distribution networks and complex packaging requirements. With this scheme, a low-cost phased array capable of scanning in azimuth and elevation with more than 60° steering range is developed and demonstrated.

ESE PhD Thesis Defense: "Compositional Methods for Agile Quadrupedal Behaviors"
2023-01-06 15:00 - 17:00 | PERCH 303, Pennovation 3rd Floor, 3401 Grays Ferry Avenue, Bldg 6176, Philadelphia, PA, 19146, United States
The last decade has witnessed a proliferation of legged machines with high power and force densities, as well as a commensurate development of locomotion controllers which achieve impressive empirical demonstrations. Yet, despite showing promise as a means of navigating rough terrain, these machines – and the locomotion controllers which animate them – are still restricted to practical applications where interactions with complex and broken terrain can be avoided or where such features are absent altogether, in spite of the fact these interactions are what distinguish legged platforms from their tracked and wheeled counterparts. Indeed, mastering locomotion over difficult terrain has long been the aim of legged robotics research, and requires the development of controllers which enable a specific machine to interact with and overcome obstacles in a given environment. Recently, state-of-the-art design methods for locomotion controllers have sought to meet this challenge by relying on accurate modeling of the platform, detailed descriptions of the environment, and a preconceived plan as to how the obstacles will be overcome. Often, many of these required data are acquired during design time, and therefore may not be readily applicable to experimental settings which can vary greatly from a designer’s anticipated description. To obtain locomotion behaviors which are broadly applicable across platform, task, and environment, the controllers which constitute them must be synthesized at run time; both to directly utilize environmental features, as well as respond to stimuli and disturbances – all of which are unknown a priori. A much more general framework for producing locomotion behavior is therefore required; one that can be applied to a broad range of machines and in a broad range of environments, and must possess metrics which allow for the evaluation of the applicability of the behavior in nearly real-time.
This thesis work begins the development of behavioral synthesis tools that are generalizable, and that enable the generation of agile and flexible behaviors from a predefined set of composable constituent “symbols”. In turn, these symbols can be tuned and adapted to suit a wide variety of platforms, environments, and tasks. By taking well-established notions of template dynamics Full and Koditschek (1999), sequential compositional techniques Burridge et al. (1999), and parallel compositional techniques pioneered by De and Koditschek (2015), a set of template “letters” which can be composed in parallel are identified, and then combined to form parallel composition “syllables”. These syllables are then assembled sequentially to form behavior “words”, which can be flexibly applied in a wide variety of situations. The utility of these synthesized behaviors is augmented further by making use of an “Extended Ground Reaction Complex” (EGRC) Topping et al. (2017) which provides a simplified representation of the salient features in an environment so that they can be explicitly targeted during behavior design and incorporated into the synthesized actions.
In all, this thesis seeks to offer a valuable and flexible set of tools to the robotic behavior designer. The empirical evidence and conceptual insight presented here offers a companion to the state-of-the-art used in legged locomotion today; offering a simple, flexible, and reusable option to aid in locomotion controller design, and beginning to lay the foundation of a symbolic representation of legged behaviors.

MEAM Seminar: "Role of Water in the Mechanics of Cells and Tissues"
2023-01-12 10:00 - 11:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
A large fraction of cell and tissue mass is made of water. The flow of water across the cell surface follows osmotic and hydraulic pressure gradients, and is actively controlled by the cell. This physical fact suggests that the mechanical behavior of cells is intimately connected with cell ionic homeostasis and osmotic control. In this talk, we will describe some of our recent experimental and modeling work on water dynamics in cells. We explore how cells control their cytoplasm water content and therefore the cell size. We will describe how cells can use directional flow of water to propel themselves and migrate, and in the case of epithelia, pump fluid between tissue compartments. In the later case, epithelial pumping of water can strongly influence tissue shape and morphogenesis.

MSE Seminar: “Building With Fluids: A Lazy Approach to Fabrication”
2023-01-12 10:30 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
In nature, organized arrays of elements arise spontaneously from the interactions between their component parts, e.g. reaction-diffusion problems, clustering colloidal particles and granular media, wrinkling surfaces, propagating cracks and flowing liquids. In the wake of biomimicry, I will discuss several strategies aiming to harness mechanical instabilities in flowing liquids, e.g. coiling, droplet formation, digitation, drainage, capillary suction, and use the regular shapes and universally self-organized patterns they naturally produce as templates for materials design. These flows are “frozen” as the liquids we use solidify into solids, e.g., through curing, cooling or evaporation. The shapes and patterns they form are universal and transcend the traditional divisions between scientific fields or even between living and inert matter. I will show that these similarities result from the mathematical analogies in the rules that govern pattern formation. In turn, I will demonstrate how to compose with these rules to augment our manufacturing capabilities, e.g. in soft robotics.

P.E.S.T.L.E. - MLK, Jr. Day of Service Information Session
2023-01-16 16:00 - 17:00 | Heilmeier Hall (Room 100), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Join us on Monday, January 16 at 4:00 pm in Towne Heilmeier Hall (Room 100) to discuss the impact community engagement has on the Philadelphia community and its long-lasting effect in our daily lives! Panelists include:
Chanda Jefferson- Director of Community Engagement & Outreach in the Office of Diversity Equity and Inclusion
Emylee Fleshman- Program Coordinator at Penn Foods and Wellness Collaborative
Joel Wilson- Founder & Executive Director of TechCORE2
Ruben Jones, MHS- Executive Director of Frontline Dads
For any questions, email pestle@seas.upenn.edu.

MEAM Seminar: "Multifunctional Soft Materials for Electronics, Robots, and Adhesives"
2023-01-17 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Multifunctional soft materials and interfaces create intriguing new opportunities to enhance performance through programmable and adaptable properties. I will discuss: 1) Novel material architectures of solid-liquid soft composites for electronics, 2) Switchable and programmable materials for adhesion control, and 3) Morphing materials for soft robotics. For soft composites, I will show how liquid metal droplets incorporated into elastomers enables exceptional combinations of soft elasticity and electrical and thermal properties for self-healing and recyclable circuits. For adhesives, I will discuss how we couple switchable, octopus-inspired adhesives with embedded sensing, processing, and control for robust underwater manipulation. This enables a wearable glove where an array of adhesives and sensors creates a biomimetic adhesive skin to manipulate diverse underwater objects. Metamaterial adhesives are also created that exhibit strong and reversible adhesion with spatially selective adhesion strength through programmed cut architectures in adhesive films. These properties are achieved by using cuts to trap adhesive cracks at predetermined locations and then forcing the crack to reverse direction and propagate backwards to separate. By combining active materials with programmed geometry, I will then introduce multifunctional morphing materials with reversible, rapid, and lockable polymorphic reconfigurability. By integrating these materials with onboard control, motors, and power, we can create a soft robotic morphing drone which autonomously transforms from a ground to air vehicle for multiple locomotion modes. These approaches provide model systems to study fundamental material properties while enabling electronic skins, soft robots, and advanced adhesives for a variety of soft matter systems.

ASSET Seminar: Domain Adaptation Under Causally Structured Distribution Shifts, Zachary Lipton (Carnegie Mellon University)
2023-01-18 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Presentation Abstract:
Faced with unlabeled data in deployment that is sampled from a different distribution than that which generated the training data, all bets are off. Moreover, while numerous heuristics have been proposed for this vague setting, it remains unclear when any among them are applicable. One way to render these problems identifiable is to impose some (assumed) causal structure, both over how the variables are related to each other, which factors are potentially manipulable (and, complementarily, which are domain-invariant). Unlike conventional problems in causality, where the goal is to estimate the effect of a manipulation (a change in the policy for prescribing the treatment), here the manipulation has already happened, and our goal is to leverage the causal structure to adapt our predictors appropriately. In this talk, I will discuss some structures under which these problems are identifiable and some of the challenges (and solutions) for applying these ideas in deep learning settings.

Spring 2023 GRASP SFI: Michael Johnson, Philadelphia Robotics Coalition "Building STEM Equity through Robotics"
2023-01-18 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Levine 307 and virtual attendance via Zoom.
ABSTRACT
Philadelphia Robotics Coalition founder, and School District of Philadelphia engineering teacher Michael Johnson discusses how Philadelphia public schools are using the competitive FIRST robotics programs to build STEM equity in our city. With the goal to inspire and prepare the next generation of STEM leaders in Philadelphia, the Coalition provides training, support, and resources for 180 robotics teams so that students in any neighborhood can access the learning, experiences, and networks surrounding them in the Philadelphia STEM community. Michael will also explain ways that GRASP students and researchers can get involved in this effort in a meaningful way across a continuum of time commitment levels.

POSTPONED - MSE Seminar: “Additive Manufacturing of Intermetallic: A Designer’s Approach”
2023-01-19 10:30 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Modern materials contain extraordinary levels of complexity, with components spanning a hierarchy of length scales. Designing materials with complex microstructures and demonstrating unique behaviors would be difficult solely using a reductionist approach to materials development. A powerful utility in this endeavor is using multiple, correlative, and scaffolding computational tools. This talk focused on using an integrated materials design approach spanning electronic structure calculations to thermodynamics modeling and paired with combinatorial experimental methods to produce a high-temperature aluminum-based intermetallic for additive manufacturing.

BE Seminar: "Tissue Architecture Driven by Immune Cells" (John Hickey, Stanford University)
2023-01-19 15:30 - 16:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
“Tissue Architecture Driven by Immune Cells”
John has developed multiplexed spatial omics techniques and computational tools to decode critical interactions within the multidimensional data (e.g., multiscale models and deep learning algorithms). He applied these tools to understand spatial relationships of cells within the healthy human intestine, inflammation induced cancers (esophageal cancer), and in T cell therapy for cancer. His lab will bridge spatial-omics technology, computational algorithm development, and engineering biology, to resolve spatiotemporal mechanisms governing multiple scales of biology, with a first application in cell therapies. His interdisciplinary training enables him to “speak” multiple scientific languages to facilitate critical collaborations across scientific disciplines.

PICS/MEAM Seminar: "A Low Rank Tensor Approach for Nonlinear Vlasov Simulations"
2023-01-20 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
In this work, we present a low-rank tensor approach for approximating solutions to the nonlinear Vlasov equation. Our method takes advantage of the tensor-friendly nature of the differential operators in the Vlasov equation to dynamically and adaptively construct a low-rank solution basis through the discretization of the equation and an SVD-type truncation procedure. We utilize finite difference WENO and discontinuous Galerkin spatial discretizations, along with a second-order strong stability preserving multi-step time discretization. To preserve conservation properties, we develop low-rank schemes with local mass, momentum, and energy conservation for the corresponding macroscopic equations. The mass and momentum are conserved using a conservative SVD truncation, while the energy is conserved by replacing the energy component of the kinetic solution with one obtained from a conservative scheme for the macroscopic energy equation. We employ hierarchical Tucker decomposition for high-dimensional problems, and demonstrate the high-order convergence, efficiency, and local conservation properties of our algorithm through a series of linear and nonlinear Vlasov examples.

P.E.S.T.L.E. Orientation - January 20
2023-01-20 16:00 - 17:00 | https://upenn.zoom.us/j/96715197752
