BE Seminar: "Studying the Neural basis of Natural Spatial, Social and Acoustic Behaviors – in Freely Behaving and Flying Bats" (Michael Yartsev, UC Berkeley)
2022-10-11 15:30 - 16:30 (America/New_York) | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid seminar that will take place in Glandt Forum (Singh Center) and via Zoom (check email for link and passcode).
Our lab seeks to understand the neural basis of complex spatial, acoustic and social behaviors in mammals. To do so, we take a neuroethological approach that leverages the specialization of the bat (Rousettus aegyptiacus) for these behaviors in order to elucidate their underlying neural computations. In the spatial domain, we take advantage of the bat’s ability to elegantly navigate during high-speed flight and under varying levels of spatial complexities. In the social-acoustic domain, we utilize the bat’s social communication signals to understand how these are learned and later used during natural group social interactions. In parallel, we have pioneered a suite of cutting-edge technologies that make it possible to study the behavior and neural circuits in freely behaving and flying bats to examine these systems in a way not previously possible. In this talk, I provide an overview of some of the research topics our lab has been working on over the past few years.

Climate Justice in Philadelphia: House by house, block by block
2022-10-11 16:00 - 17:00 | https://upenn.zoom.us/j/96715197752
More details coming soon!

ASSET Seminar: What Transfers in Transfer Learning?, Eric Wong (University of Pennsylvania)
2022-10-12 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
Recently, the transfer learning paradigm has seen a surge of interest due to its impressive capabilities in vision and language. Models are pretrained on ever-growing datasets with enormous parameter counts, trending towards being monolithic and opaque. How can we understand the underlying process? This talk will provide, to some degree, insight on how data affects transfer learning using the framework of influence functions. These findings include pinpointing subpopulations and biases in the pretraining data that help (or hurt) transfer performance.

Impacts of Climate Change on Global Water Resources and Engineering Solutions
2022-10-12 14:00 - 15:00 | https://upenn.zoom.us/j/96715197752
This panel will examine the impact of climate change on global water resources and how these impacts have affected people in the global south. From droughts that have led to crop failures to floods that have damaged crops and property, it is obvious that climate change has brought extremes in weather and has compromised the availability of clean water to peoples in developing countries where resilience against changing climate are fragile at best. Panelists will offer engineering and hydro ideas that can lead to improvement of the current situation.

Speakers:
Doug Jerolmack, Penn Engineering
Tony Sauder, Penn EES/LPS, Water Center at Penn
Paulo Arratia, Penn Engineering

Fall 2022 GRASP SFI: Sonia Chernova, Georgia Institute of Technology, “Semantic-Driven Robot Assistance and User Interaction”
2022-10-12 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
Reliable operation in everyday human environments – homes, offices, and businesses – remains elusive for today’s robotic systems. A key challenge is diversity, as no two homes or businesses are exactly alike. However, despite the innumerable unique aspects of any home, there are many commonalities as well, particularly about how objects are placed and used. These commonalities can be captured in semantic representations, and then used to improve the autonomy of robotic systems by, for example, enabling robots to infer missing information in human instructions, efficiently search for objects, or manipulate objects more effectively. This talk will discuss recent advances in semantic reasoning, particularly focusing on semantics of everyday objects, household environments, and the development of robotic systems that intelligently interact with users.

CBE Seminar Series: Title TBA (Scott Milner, Pennsylvania State University)
2022-10-12 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States

Singh Center for Nanotechnology Annual User Meeting
2022-10-13 | Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
The 2022 Singh Center for Nanotechnology Annual User Meeting will be held on Thursday, October 13, 2022, in the Singh Center’s Glandt Forum. The purpose for this in-person meeting is to welcome the user community as we celebrate the acheivements of nanotechnology-enabled research and innovation at the University of Pennsylvania. For more information: http://singhnano.eventbrite.com/

MSE Seminar: “Additive Manufacturing of Compositionally Complex Alloys with Engineered Microstructures”
2022-10-13 10:30 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The increasing demand for structural metals has driven increasingly complex compositions, which bring critical challenges in processing of these materials. Additive manufacturing, also called 3D printing, is a disruptive technology for creating structural materials and components in a single print. In this talk, I will present our recent work on additive manufacturing of compositionally complex alloys (CCAs) with tailored microstructures and properties. Specifically, I will show the potential of leveraging laser additive manufacturing and direct ink writing to produce CCAs such as high-entropy alloys and bulk metallic glass composites with unique microstructures, leading to extraordinary mechanical properties that can extend far beyond those achievable via conventional processing methods. In addition, I will discuss the abundant opportunities enabled by additive manufacturing for high-throughput materials discovery to accelerate the pace of multicomponent alloy design.

Fall 2022 GRASP on Robotics: Victoria Webster-Wood, Carnegie Mellon University, “It’s Alive! Bioinspired and biohybrid approaches towards life-like and living robots”
2022-10-14 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

Animals have long served as an inspiration for robotics. However, the adaptability, complex control, and advanced learning capabilities observed in animals are not yet fully understood, and therefore have not been fully captured by current robotic systems. Furthermore, many of the mechanical properties and physical capabilities seen in animals have yet to be achieved in robotic platforms. For example, standard materials for robotic fabrication do not exhibit self-healing or have the ability to autonomously generate energy, as is seen in biological systems. Additionally, traditional robotic actuators lack the compliance, energy efficiency, and power-to-weight ratio combinations observed in musculoskeletal systems.
In this talk, I will share efforts from my group in our two primary research thrusts: Bioinspired robotics, and biohybrid robotics. By using neuromechanical models and bioinspired robots as tools for basic research we are developing new models of how animals achieve multifunctional, adaptable behaviors. Building on our understanding of animal systems and living tissues, our research in biohybrid robotics is enabling new approaches toward the creation of autonomous biodegradable living robots. Such robotic systems have future applications in medicine, search and rescue, and environmental monitoring of sensitive environments (e.g., coral reefs).

PICS Colloquium, “Sound Attenuation and the Vibrational Properties of Glasses”
2022-10-14 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Abstract: Understanding of the universal low-temperature properties of glasses and why they differ from their crystalline counterparts requires the understanding of the vibrational properties of glasses. Due to recent advances of computational techniques, we are now able to study simulated glasses with a wide range of vibrational properties, which is essential to understanding their role in the low-temperature properties of glasses. In this talk I will discuss the stability dependence of the vibrational modes of glasses ranging from poorly annealed to exceptionally stable. Our most stable glasses are comparable to exceptionally-stable, vapor- deposited laboratory glasses. We find that the density of quasi-localized, low-frequency modes decrease quickly with increasing stability and the density of these modes are correlated with sound attenuation in the harmonic approximation. We use a recently developed theory that very accurately reproduces the low-frequency sound attenuation to examine the relationship between the vibrational modes and sound attenuation. This theory indicates that the non- affine forces, which are responsible for the renormalization of the speed of sound in amorphous solids, is responsible for sound attenuation. Surprisingly, we find that the low- frequency, quasi-localized modes make a relatively small contribution to the sound attenuation coefficient compared to the extended, low-frequency modes. I will conclude by discussing recent attempts at identifying regions of the glass that play an enhanced role in sound attenuation, if they exist.

P.E.S.T.L.E. Orientation - October 14
2022-10-14 16:00 - 16:30 | https://upenn.zoom.us/j/96715197752
Join PESTLE for our Zoom Orientation session on Friday, October 14 at 4:00 pm! Please email us at pestle@seas.upenn.edu if you have any questions.

MEAM Seminar: "Exergy-based Methods as a Promising Modern Thermodynamic Evaluation and Optimization Tool"
2022-10-18 10:00 - 11:30 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Exergy-based methods are powerful tools for developing, evaluating, understanding, and improving energy conversion systems. In addition to conventional methods, advanced exergy-based analyses consider (a) the interactions among components of the overall system, and (b) the real potential for improving each important system component. The main role of an advanced analysis is to provide energy conversion system designers and operators with information useful for improving the design and operation of such systems. This presentation will include the advanced exergy-based evaluations and optimization methods as well. Advanced exergy-based method means splitting the exergy destruction, the capital investment cost, and the component-related environmental impact associated with each single component of an energy conversion system into endogenous/exogenous and avoidable/unavoidable parts and using a further splitting of the exogenous exergy destruction improves (a) our understanding of the processes that take place, and (b) the quality of the conclusions for improvement obtained from the analysis. It will be discussed the main features and some recent developments in the area of advanced exergy-based methods. Application of the method to different energy-conversion systems will be demonstrated.

Joint PSOC/Center for Soft & Living Matter Seminar: “Feeling for cell function” (Jochen Guck, Max Planck Institute)
2022-10-18 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Fall 2022 Hybrid-Seminar Series
Special joint seminar on Tuesday October 18th at 12:00 Noon
Towne 225 / Raisler Lounge
For Zoom link, please contact <manu@seas.upenn.edu

CIS Seminar: "Equilibrium Complexity and Deep Learning"
2022-10-18 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Deep Learning has recently made significant progress in learning challenges such as speech and image recognition, automatic translation, and text generation, much of that progress being fueled by the success of gradient descent-based optimization methods in computing local optima of non-convex objectives. From robustifying machine learning models against adversarial attacks to causal inference, training generative models, multi-robot interactions, and learning in strategic environments, many outstanding challenges in Machine Learning lie at its interface with Game Theory. On this front, however, Deep Learning has been less successful. Here, the role of single-objective optimization is played by equilibrium computation, but gradient-descent based methods fail to find equilibria, and even computing local equilibria — the analog of computing local optima in single-agent settings — has remained elusive.

We shed light on these challenges through a combination of learning-theoretic, complexity-theoretic, and game-theoretic techniques, presenting obstacles and opportunities for Machine Learning and Game Theory going forward, including recent progress on multi-agent reinforcement learning.

(I will assume no deep learning, game theory, or complexity theory background for this talk and present results from joint works with Noah Golowich, Stratis Skoulakis, Manolis Zampetakis, and Kaiqing Zhang.)

ASSET Seminar: New approaches to detecting and adapting to domain shifts in machine learning, Zico Kolter, Ph.D. (Carnegie Mellon University)
2022-10-19 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
Machine learning systems, in virtually every deployed system, encounter data from a qualitatively different distribution than what they were trained upon. Effectively dealing with this problem, known as domain shift, is thus perhaps the key challenge in deploying machine learning methods in practice. In this talk, I will motivate some of these challenges in domain shift, and highlight some of our recent work on two topics. First, I will present our work on determining if we can even just evaluate the performance of machine learning models under distribution shift, without access to labelled data. And second, I will present work on how we can better adapt our classifiers to new data distributions, again assuming access only to unlabelled data in the new domain.

Fall 2022 GRASP SFI: Srinath Sridhar, Brown University, “Learning to Generate, Edit, and Arrange 3D Shapes"
2022-10-19 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
In computer vision and robotics, we often need to deal with 3D objects. For instance, we may want to generate instances of 3D chairs, edit the generated chairs using natural language instructions, or arrange them in a canonical orientation. In this talk, I will present some of our work on addressing these problems. First, I will talk about ShapeCrafter, a model for recursively generating and modifying 3D shapes using natural language descriptions. ShapeCrafter generates a 3D shape distribution that gradually evolves as more phrases are added resulting in shapes closer to text instructions. In addition, I will introduce the notions of invariance, equivariance, and ‘canonicalization’, and discuss their importance in 3D understanding. I will describe ConDor, a self-supervised method for canonicalizing the orientation of full and partial 3D shapes. Finally, I will identify future directions including opportunities for expanding 3D understanding to neural fields, articulating objects, and object collections.

CIS Seminar: "Rater Equivalence: An Interpretable Measure of Classifier Accuracy Against Human Labels"
2022-10-20 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
In many classification tasks, the ground truth is either noisy or subjective. Examples of noisy ground truth include: does this radiology image show a cancerous growth? does this radar data portend an imminent tornado? Examples of subjective ground truth include: which of two alternative paper titles is better? is this comment toxic? what is the political leaning of this news article? We refer to tasks where human labels are the only indication of ground truth available at the time that decisions must be made as survey settings. In these settings, measures of classifier accuracy against human labels, such as precision, recall, and cross-entropy, confound the quality of the classifier with the level of agreement among human raters. Thus, they have no meaningful interpretation on their own. We describe a procedure that, given a dataset with predictions from a classifier and K labels per item, rescales any underlying accuracy measure into one that has an intuitive interpretation. The K raters are divided into a source panel and a target panel. The source panel’s labels for an item are combined to produce a predicted label for another rater. Both the source panel predictions and classifier predictions are scored against the same target panel’s labels. The rater equivalence of any classifier is the minimum number of source raters needed to produce the same expected score as that found for the classifier. We explore the stability of the rater equivalence measure as the target panel size varies and find one underlying measure, determinant mutual information, for which it is invariant.

MSE Seminar: “What Governs Grain Boundary Migration?"
2022-10-20 22:30 - 23:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Curvature is the common driving force for grain boundary motion in all polycrystals. However, models and simulations derived from curvature-based motion cannot predict irregular, albeit commonly observed, grain growth behavior. To build better predictive models, we need to employ new tools to understand what governs grain growth. First, I will demonstrate how high energy x-ray diffraction microscopy (HEDM) can be used to observe grain growth in real 3D polycrystalline systems. In a grain growth study employing HEDM of strontium titanate, we find that curvature is a poor predictor of grain boundary migration. Instead, anisotropic grain boundary properties are hypothesized to override the contribution of curvature. Second, I will describe how reinforcement learning, a machine learning tool, can capture the underlying behavior of an evolving Markov decision process and “teach” it to maximize the “rewards” regarding the agreement between prediction and simulation. To demonstrate the feasibility of this approach, we built a deep reinforcement model that emulates grain growth by training on Monte Carlo Potts grain growth simulations. The developed reinforcement model was validated on different microstructural architectures to ensure that it captures the underlying physics. The accuracy of our short and long-term predictions will be evaluated. Then, I will discuss how HEDM and our machine learning model can be combined to understand how anisotropic grain boundaries migrate in 3D polycrystals.

Fall 2022 GRASP on Robotics: Jim Ostrowski, Blue River Technology, "Robotics and Deep Learning in Production Agriculture"
2022-10-21 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
With a growing population to feed, a heightened awareness of the environmental impact of agriculture, and continued challenges of labor availability, the need is greater than ever for advanced technologies applied to automation and autonomy in agriculture. In this talk, I will describe two projects that we have been developing, and discuss the role of robotics, computer vision, and machine learning in delivering commercially viable products. The products include a smart spraying solution called See & Spray Ultimate and an autonomous tractor for tillage. I will explore some of the key focus areas, technological development, and common themes that have allowed us to move these products to production.

PRECISE Center/xLab presents: Routing with Privacy for drone package delivery systems, Max Z. Li, Ph.D. (University of Michigan)
2022-10-21 12:00 - 13:00 | Levine Hall 279, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
Uncrewed aerial vehicles (UAVs), or drones, are increasingly being used to deliver goods from vendors to customers. To safely conduct these operations at scale, drones are required to broadcast position information as codified in remote identification (remote ID) regulations. However, location broadcast of package delivery drones introduces a privacy risk for customers using these delivery services: Third-party observers may leverage broadcast drone trajectories to link customers with their purchases, potentially resulting in a wide range of privacy risks.
We propose a probabilistic definition of privacy risk based on the likelihood of associating a customer to a vendor given a package delivery route. Next, we quantify these risks, enabling drone operators to assess privacy risks when planning delivery routes. We then evaluate the impacts of various factors (e.g., drone capacity) on privacy and consider the trade-offs between privacy and delivery wait times. Finally, we propose heuristics for generating routes with privacy guarantees to avoid exhaustive enumeration of all possible routes and evaluate their performance on several realistic delivery scenarios.

PICS Colloquium: "Computation of Flow-Induced Sound at Low Mach Numbers"
2022-10-21 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Abstract: Flow-induced noise is a significant problem for air, road and marine vehicles as well as many other engineering applications. At low Mach numbers, large disparities in energy levels and length scales between the flow and the concomitant sound present unique challenges for acoustic predictions. This talk will start with a brief overview of computational methods for low-Mach-number flow noise in the framework of Lighthill’s aeroacoustic theory in combination with high-fidelity flow simulations, followed by a discussion of recent investigations of several aeroacoustic problems involving airframe noise and propeller noise. A study of rotor interaction with an axisymmetric turbulent boundary layer (TBL) at the tail-end of a body of revolution (BOR) will be highlighted. The TBL on the nose and midsection of the BOR is computed using wall-modeled large-eddy simulation whereas that in the acoustically important tail-cone section is wall resolved. This approach is shown to predict the correct turbulence statistics of rotor inflow and sound-pressure spectra compared with experimental data. Correlation and spectral analyses demonstrate rapidly growing turbulence structures in the decelerating tail-cone TBL whose interaction with successive rotor blades generates spectral peaks, known as haystacking peaks, in the broadband sound pressure spectra. The spatial and frequency characteristics of blade acoustic dipole sources will be discussed in relation to the turbulence properties of the boundary layer.

PSOC Seminar: Jamal S. Lewis, University of Florida
2022-10-24 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

MEAM Seminar: "Predicting and Reducing High-Speed Jet Noise"
2022-10-25 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The intense noise radiated by supersonic jets leads to sound-induced structural vibration, fatigue and personnel-related operational difficulties. Experimental, theoretical, and computational investigations into the physics and control of jet noise have identified several important sound sources, including wavepackets, screech, Mach wave radiation, and broadband shock associated noise. Reducing the loudest sources of jet noise, without sacrificing propulsive performance, has relied on intuition, parametric survey, or optimal control techniques. With the aim of developing a more general and robust method of jet noise reduction, we present a physics-based approach that reveals jet dynamics/mechanisms, highlighted by a linear resolvent analysis, crucial to the the generation of jet noise in a biconical tactical jet nozzle. Our approach uses large-eddy simulation to predict the turbulent flow within and exhausted by the jet nozzle and then identifies optimal forcing/response modes of the compressible Navier-Stokes operator, linearized about a fully-resolved jet mean flow, to identify and manipulate coherent structures that are primarily responsible for the production of jet noise. The operating conditions of the jet and nozzle geometry are motivated by tactical Naval aircraft.

CIS Seminar: "The Long Arm of Theoretical Computer Science: A Case Study in Blockchains/Web3"
2022-10-25 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Blockchains that support a general contract layer (e.g., Ethereum) export the functionality of a general-purpose, ownerless, and open-access computer that can enforce property rights for digital data. How is such functionality implemented? Using a lot of extremely cool computer science ideas! And like everywhere else in computer science, theory plays an undeniable role in the understanding and advancement of this technology. In this talk, Tim Roughgarden will highlight three examples (among many):

Possibility and impossibility results for permissionless consensus (i.e., implementing an “ownerless” computer).
Incentive-compatible transaction fee mechanism design (part of implementing an “open-access” computer).
Succinct proofs of computation (for boosting the computer’s power by piggybacking on off-chain computation).

Parts of this talk are based on joint work with Andrew Lewis-Pye.

ASSET Seminar: How to Design Molecules that Dock Well but Can't Exist, Jacob Gardner, Ph.D.
2022-10-26 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:BIO
Machine learning has become an indispensable aid to researchers developing the next generation of novel therapeutics. In this talk, I will discuss how some of the most important problems in virtual screening for new potential drug molecules can be cast as black-box optimization problems, where the goal is to find molecules maximizing some desired property — for example, the binding affinity to a known drug target. By leveraging recent work on representation learning for molecules and high dimensional black-box optimization, we are able to achieve up to a 20x performance improvement over state of the art on several of the most widely used benchmarks for molecule design. I will then show how this powerful new approach reveals flaws in tools commonly used for computational molecule design. Even the most widely used docking simulators can be fooled by a sufficiently powerful optimizer producing molecules that could not plausibly exist in nature — a challenge reminiscent of adversarial image generation in computer vision. These findings can be mitigated to a degree through the use of constrained optimization, but also motivate adapting lessons from robust machine learning to the docking simulators themselves.

Fall 2022 GRASP SFI: Charlie Andersen and Terry Scott, Burro, "Founders' journey of building a robotics company in Philadelphia"
2022-10-26 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
Charlie Andersen (CEO) and Terry Scott (CTO) are two of the founders of Burro. They share their origin story of Burro and we follow their journey of building a robotics company and a product intended to bring new life into an ancient industry. Off a small launchpad of accelerator funding and Charlie’s personal savings, they build their proof of concept utility robot and target specific sectors within agriculture to garner interest and investment. With the closure of a seed round, they embarked on turning that proof-of-concept into a functional prototype. They will share how the company, product and technology has evolved from 4 people and an idea to a company with 33 members and growing, with one of the largest deployed operational robotic fleets within agricultural robotics.

CHANCE LECTURE (CBE Seminar Series): "A Fluid Paradigm for Biological Organization" (Clifford P. Brangwynne, Princeton University)
2022-10-26 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States

MSE Seminar: “A More Sustainable Future via Polymer Circularity"
2022-10-27 10:30 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
In a Circular Economy, atoms and molecules are kept inside the economy where they continue to produce value, and they are kept out of unwanted places like our environment. At a high level, this concept applied to polymers and plastics should reduce the flow of material into the environment, while improving efficiency and reducing demand for natural resources, but the reality is much more complex. When considering the full supply chain, from design and manufacture, to use and retrieval, the system is full of challenges and potential for leakage. The only way to ensure progress, is to design changes to the system with these fundamental goals in mind, and to build the measurement and data frameworks that can support difficult decision-making and confidence in the results. The talk will present some NIST activities in fundamental materials design and measurement relevant to this larger need, including polyolefin molecular design for improved recovery, and models and processes to improve compatibilization of polymer blends relevant to mechanical recycling.

CIS Seminar: "Designing Hardware for Cryptography and Cryptography for Hardware"
2022-10-27 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
There have been few high-impact deployments of hardware implementations of cryptographic
primitives. We present the benefits and challenges of hardware acceleration of sophisticated
cryptographic primitives and protocols, and describe our recent design work in accelerating
Fully Homomorphic Encryption by three to four orders of magnitude using programmable hardware
accelerators. We argue the significant potential for synergistic codesign of cryptography and
hardware, where customized hardware accelerates cryptographic protocols that are designed with
hardware acceleration in mind.

Joint work with Daniel Sanchez's group at MIT.
