Penn Engineering Events

MEAM Seminar: "Fusion for Robot Perception and Controls"
2021-03-02 10:30 - 12:00 (America/New_York) | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Machine learning has led to powerful advances in robotics: deep learning for visual perception from raw images and deep reinforcement learning (RL) for learning controls from trial and error. Yet, these black-box techniques can often require large amounts of data, have results difficult to interpret, and fail catastrophically when dealing with out-of-distribution data. In this talk, I will introduce the concept of “fusion” in robot perception and controls for robust, sample efficient, and generalizable robot learning. On the perception side, we fuse multiple sensor modalities and demonstrate generalization to new task instances and robustness to sensor failures that are out-of-distribution. On the controls side, we leverage fusion by combining known models with learned policies, making our policy learning substantially more sample efficient.

PSOC Webinar: "Polarity Signaling Ensures Epidermal Homeostasis By Coupling Cellular Mechanics and Genomic Integrity" (Sandra Iden)
2021-03-01 12:00 - 13:00 | PA
Physical Sciences in Oncology Center PSOC@Penn
Spring 2021 Webinar Series Mondays at 12:00 noon (EST)
For webinar links, please contact manu@seas.upenn.edu.

ODEI Spotlight: USABE Fireside Chat with Dr. CJ Taylor
2021-02-26 16:00 - 17:00 | PA
Fireside Chat with Dr. CJ Taylor
Date: Friday, February 26th
Time: 4:00 – 5:00 PM EST
Join USABE on Friday, February 26th at 4 PM for a conversation with Dr. CJ Taylor, Associate Dean for Diversity, Equity, and Inclusion at Penn Engineering, to discuss his experiences in STEM and engineering and his role as a professor in SEAS. Please register for the event and submit your questions for Dr. Taylor at tiny.cc/USABEfiresidechat.

PICS Colloquium: "Learning about learning by many-body systems"
2021-02-26 14:00 - 15:00 | PA
Abstract: Many-body systems from soap bubbles to suspensions to polymers learn the drives that push them far from equilibrium. This learning has been detected with thermodynamic properties, such as work absorption and strain. We progress beyond these macroscopic properties that were first defined for equilibrium contexts: We quantify statistical mechanical learning with representation learning, a machine-learning model in which information squeezes through a bottleneck. We identify a structural parallel between representation learning and far-from-equilibrium statistical mechanics. Applying this parallel, we measure four facets of many-body systems’ learning: classification ability, memory capacity, discrimination ability, and novelty detection. Numerical simulations of a classical spin glass illustrate our technique. This toolkit exposes self-organization that eludes detection by thermodynamic measures. Our toolkit more reliably and more precisely detects and quantifies learning by matter.

GRASP On Robotics: “Photoacoustic Vision for Surgical Robots”
2021-02-26 11:00 - 12:30 | Zoom
Abstract: The concept of “x-ray vision” is widely understood to be the ability to see through structures that are not transparent to the human eye. This concept would be a useful feature for surgeons and surgical robots, particularly when navigating complex anatomy. The Photoacoustic & Ultrasonic Systems Engineering (PULSE) Lab is developing imaging systems to offer this capability, but not with ionizing x-rays. Instead, we are utilizing a different wavelength on the electromagnetic spectrum, specifically the nm wavelengths required to induce the photoacoustic effect and enable photoacoustic imaging. To implement this vision, laser pulses delivered through optical fibers illuminate surgical regions of interest, causing an acoustic response that is detectable with ultrasound transducers. Beamforming is then implemented to create a photoacoustic image. In this talk, I will highlight novel light delivery systems, new spatial coherence beamforming theory, deep learning alternatives to beamforming, and robotic integration methods, each pioneered by the PULSE Lab to enable an exciting new frontier known as photoacoustic-guided surgery. This new paradigm has the potential to eliminate the occurrence of major complications (e.g., inaccurate targeting, excessive bleeding, paralysis, accidental patient death) during a wide range of delicate surgeries and procedures, including neurosurgery, cardiac catheter-based interventions, liver surgery, spinal fusion surgery, hysterectomies, biopsies, and teleoperative robotic surgeries.
Click here to join the Zoom Webinar

ODEI Event: Do You Have a Crew? The Importance of Friendship in Creating a Fulfilling Life
2021-02-25 19:00 - 21:00 | PA
Don’t isolate. Congregate! Join Penn Engineering’s Office of Diversity, Equity, and Inclusion to meet six dynamic men and learn about how their bonds of friendship and NSBE affiliation benefited them personally and professionally. Hear their story and engage in Q&A for the first hour (7PM-8PM). Then, meet someone new in breakout groups (8PM-8:30PM). An additional 30 minutes (8:30 PM-9PM) will be available for extended conversations. Do you have a crew? Join us to expand your circle!
Zoom Link: https://upenn.zoom.us/j/98242572639
Zoom ID: 982 4257 2639

CIS Seminar:"Probabilistic proofs: theory, hardware, and everything in between"
2021-02-25 15:00 - 16:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
In the past decade, systems that use probabilistic proofs in real-world applications have seen explosive growth. These systems build upon some of the crown jewels of theoretical computer science—interactive proofs, probabilistically checkable proofs, and zero-knowledge proofs—to solve problems of trust and privacy in a wide range of settings.
This talk describes my work building systems that answer questions ranging from “how can we build trustworthy hardware that uses untrusted components?” to “how can we reduce the cost of verifying smart contract execution in blockchains?” Along the way, I will discuss the pervasive challenges of efficiency, expressiveness, and scalability in this research area; my approach to addressing these challenges; and future directions that promise to bring this exciting technology to bear on an even wider range of applications.

BE Seminar: "Dissecting Multicellular Therapeutic Responses Using a Large-scale Single-cell Profiling Platform" (Siyu Chen)
2021-02-25 15:00 - 16:00 | PA
This event will be held virtually via Zoom (check email or contact ksas@seas.upenn.edu).
Human diseases are fundamentally multicellular in nature with many different cell types contributing to disease progression and treatment response. However, how therapeutics impact each cell type in a heterogeneous population remains poorly understood because most studies are focused on isolated cell types or a handful of pathways. Now, single-cell transcriptional profiling methods allow us to collect a deep molecular portrait of the collective response of heterogeneous populations of cells to any perturbation. In my talk, I will present my research in harnessing the power of single-cell transcriptional profiling measurements to dissect therapeutic response in heterogeneous cell populations. In the first part, I will describe the probabilistic modeling framework I developed for analyzing single-cell population data across perturbations at scale (PopAlign). PopAlign models single-cell data with semantically interpretable, low-error, highly-compressed probabilistic models, which allows fast comparisons across hundreds of samples. In the second part, I will discuss how I applied this framework to analyze a drug response study of over 1.6M human primary immune cells to 500 commercially-available immunomodulatory compounds. While most compounds in the library exert broad impact across multiple cell types in the population, my analysis also reveals highly cell-type specific activity, including a novel myeloid-suppressing function of a group of compounds including NSAIDs and an artificial sweetener. My work provides new depth and insight into how existing compounds reshape immune populations, and a general platform for evaluating and designing population-level responses to therapeutic interventions.

ESE Seminar: "Sensing the Physical World using Pervasive Wireless Infrastructure"
2021-02-25 11:00 - 12:00 | Zoom – Email ESE for Link jbatter@seas.upenn.edu
Emerging applications such as smart cities, autonomous vehicles, and mixed reality rely on embedded systems that are engaging with the physical environment through sensors. Building upon this connection, my vision is to advance Omnipresent Sensing by harnessing the wireless infrastructure in and around buildings and cities to act as a non-intrusive sensing platform. This is possible by innovating at the crossroads of two recent trends in mobile computing: (1) Wireless technologies such as Millimeter-wave (mmWave) and Massive MIMO systems can now support higher bandwidth for communication and improved resolution for RF sensing applications. (2) Advancements in CPUs and RF front-ends are making it easier to develop software-defined sensing and communication systems. This is affording edge devices the ability to do more advanced signal processing and machine learning.
In this talk, I will focus on how to design an RF-equivalent of optical retro-reflectors and use them as fiducial markers in autonomous vehicles, robotics, and mixed reality applications. I will then discuss how nuances from the environment itself can be leveraged to improve sensing quality in the context of human sensing, object tracking, and indoor localization. I will conclude this talk with a roadmap of combining radar-style RF sensors and wireless communication links for the wireless embedded systems of the future.

MSE Seminar: "Harnessing Temporally Controlled Biophysical Cues To Direct Stem Cell Phenotype"
2021-02-25 10:45 - 11:45 | PA
Endogenous tissue-specific stem cells are crucial regulators of tissue health throughout life, orchestrating diverse functions ranging from learning and cognition to skeletal muscle homeostasis. The local microenvironment, or stem cell niche, presents a myriad of biochemical and biophysical factors that direct cell fate. Stem cell mediated tissue regeneration relies on presentation of these factors in a precise temporal sequence at appropriate doses. Dysregulation of this process, such as in aging and disease, leads to diminished tissue function and potentially organ failure. Despite the known importance of biophysical cues in regulating stem cell phenotype, the effects of temporal changes in the mechanical and microstructural properties of the extracellular matrix (ECM) on stem cell fate remain poorly understood, in large part due to a lack of suitable engineered systems to selectively probe how changing matrix properties impact cellular signaling. In my talk, I will describe a multifaceted strategy to elucidate unappreciated mechanisms behind cell-ECM interactions impacting homeostasis and disease, drawing on protein engineering, bioorthogonal chemistries, and stem cell biology. In the first half of the talk, I will discuss the use of protein engineered biomaterials to identify critical ECM properties that are required for neural stem cell expansion. The second half of the talk will focus on the development of bioorthogonal chemical strategies to regulate the mechanical properties of synthetic cell culture substrates on demand and the application of these materials to determine how temporally varying matrix properties impact muscle stem cell commitment. Together, these research projects highlight the power of engineered platforms in elucidating novel biological mechanisms implicated in development, disease, and aging.

Inaugural Joseph Bordogna Forum: “A Call to Action for Racial Justice and Equity in Engineering”
2021-02-24 16:00 - 17:30 | https://upenn.zoom.us/j/96715197752
Racism and anti-Blackness are crises that jeopardize our democracy, productivity and well-being and call into question whether we can all live together peaceably and harmoniously in a just and equitable American society. At this critical moment in our nation’s history we need more than words that renounce racism and anti-Blackness, we need actions to abolish them.
We must be willing to have meaningful and difficult conversations if we are to rid ourselves of the fear of the other, the yoke that prevents us from becoming a nation where everyone is treated with dignity and respect. Engineers must be at the table where these conversations take place.
In this lecture, Dr. Slaughter will discuss the social responsibilities that engineers have in making the world a more equitable place and the solutions that corporations and academic institutions can enact to create lasting and meaningful change.
Zoom Link | Password: [REDACTED]

Spring 2021 GRASP SFI: “Hunting for Unknown Unknowns: AI and Ethics in Society”
2021-02-24 15:00 - 16:00 | Zoom
Abstract: Homo Sapiens is considered a “hyper-cooperative species,” and this aptitude for cooperation may be responsible for our dominance over the Earth. Cooperation promises great benefits, but each participant is vulnerable to exploitation by their partners. Successful cooperation requires trust: acceptance of vulnerability, with confidence that it will not be exploited. The culture of any society includes ethical principles specifying how to be trustworthy, to whom trustworthiness is owed, and how to recognize who is likely to be trustworthy. The continued viability of a society depends on how well this mechanism does its job. Deployments of AI systems for autonomous vehicles, facial recognition, medical diagnosis, decisions about credit or parole, and other domains have raised questions about their trustworthiness. These questions apply not only to robotic and AI systems based on digital computers, but also to institutional structures such as governments and corporations. Trust failures arise when a carefully designed decision mechanism confronts a situation outside its comprehension: an “unknown unknown.” Science, engineering, economics, law, and public policy all depend on models to cope with the unbounded complexity of the real world. A model specifies a limited set of elements and relations that support inferences relevant to the purpose of the model. Everything else is considered negligible relative to the purpose of the model. If some of these unknown unknowns stop being negligible, the model can fail, possibly with serious consequences. Game-theoretic reasoning, maximizing expected utility, can be a powerful decision tool in multi-agent settings, but its validity depends critically on the quality of the model, especially the definition of utility. A particular failure mode, when the utility measure is oblivious to trust and trustworthiness, is to encourage each participant to optimize expected utility by exploiting the vulnerabilities of the other participants. Trust and cooperation are thereby discouraged. Widespread loss of trust and cooperation can become an existential threat to the society. Our task in AI is to identify potentially dangerous unknown unknowns, and find appropriate ways to incorporate them into our models, supporting trust and cooperation in our society.
Click here to join the Zoom meeting

CIS Seminar: "Enhancing Usability and Explainability of Data Systems"
2021-02-24 15:00 - 16:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
The recent growth of data science has expanded its reach to an ever-growing user base of non-experts. Unfortunately, most existing systems offer limited usability and support for explanations: these systems are usable only by experts with sound technical skills, and even experts are hindered by the lack of transparency into the inner workings of the systems. My research focuses on solving the challenges users face while interacting with data systems and, thus, pushes the frontiers towards achieving democratization of data systems, demanding that people with different skills and backgrounds should be able to use these data systems alike. Further, my research aims at providing explainability of the behavior of data systems to help the users understand and trust the system function, especially when unexpected behavior occurs. In this talk, I will discuss frameworks that address these challenges in a variety of settings and applications, including relational data querying, document summarization, system debugging, and trust in machine-learning models that learn from data.

CBE Seminar: "Probing Protein Interactions from Molecular to Cellular Scales with Microscale Technologies"
2021-02-24 15:00 - 16:00 | Zoom – Email CBE for link
Abstract
Biological molecules rarely act alone. For example, in many pediatric cancers, a chromosomal rearrangement results in a fusion protein with altered DNA and protein interactions that yield proliferative and aggressively metastatic cell subpopulations. In this talk, I will describe quantification of molecular interaction properties relevant to fusion oncoprotein biology using microscale tools with distinct forces tailored to each biological question. First, I will discuss measurement of cellular heterogeneity in cytoskeletal protein complex abundance as is needed to uncover ‘rogue’ metastatic and drug resistant cells. I introduced a microfluidic biochemical assay using electrophoretic forces and sieving hydrogels to fractionate dynamic protein complexes from single cells faster than dissociation kinetics. Second, I will describe biophysically probing protein-DNA molecular mechanics to understand how tension plays a role in DNA pairing during DNA damage repair. To reveal forces the Rad51 repair protein exerts on DNA, microscale tweezers apply a magnetic piconewton-scale force to single molecules of DNA. Finally, I will share future directions discerning the biochemical and biophysical roles of multi-component protein complexes in fusion oncoprotein-driven pediatric cancers, such as Ewing’s sarcoma. My group will uncover new targets for ‘molecularly surgical’ Ewing’s sarcoma therapies through interrogation of molecular interactions towards replacing combination chemotherapy and crude tumor removal surgeries.

CIS Seminar: "Provably Secure Indistinguishability Obfuscation"
2021-02-23 15:00 - 16:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
Abstract:
In this talk, we will cover some exciting progress on the problem of Indistinguishability Obfuscation (proposed by Barak et. al. 2001). In a nutshell, an Indistinguishability Obfuscation scheme is an efficient compiler that takes as input a program and outputs a new program with the same input-behavior and only a polynomial slowdown, but in addition, we have the guarantee that the new program reveals minimal information about the original program.
If realized securely and efficiently, such an obfuscation scheme would have huge consequences to both theory and practice. However, until now we did not know if it exists under any reasonably well-believed conjecture. Our work places iO onto “terra-firma”, by giving a construction that is as secure as several well-studied mathematical problems that are widely believed to be extremely hard to solve.
In this talk, we will hear about indistinguishability obfuscation, why it is useful, how it can be constructed, and future work.

MEAM Seminar: "Engineering Interfaces To Improve The Thermal Performance of Wide Bandgap Semiconductors"
2021-02-23 10:30 - 12:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Wide bandgap electronics are currently under development due to their potential to create some of the most advanced RF and power electronics in the world. A key concern in their development is the control of the junction temperature during operation which is impacted by the internal device thermal resistance. To address this concern, we will discuss advancements in thermal characterization techniques that have allowed new insights into the role of material interfaces on the thermal response of electronic devices made from GaN, AlGaN, and Ga2O3. While combining these semiconductors with high thermal conductivity like AlN, SiC or diamond have promise for improving heat dissipation, manufacturing challenges exist that must be addressed. We will discuss a few of these methods of integration ranging from direct growth to plasma activated bonding. Finally, for power electronics, packaging solutions for the thermal management of ultrawide bandgap devices will be presented, allowing for the future implementation of this technology.

BE Dissertation Defense: "Microtissue Engineered Neural Networks as Optically-Controlled Living Electrodes for Circuit Modeling and Neuroprosthetics" (Dayo Adewole)
2021-02-22 09:00 - 11:00 | PA
The Department of Bioengineering at the University of Pennsylvania and Dr. D. Kacy Cullen are pleased to announce the Doctoral Dissertation Defense of Dayo Adewole.

Title: Microtissue Engineered Neural Networks as Optically-Controlled Living Electrodes for Circuit Modeling and Neuroprosthetics

Date: February 22, 2021
Time: 9:00am

Please join via the zoom link below:

https://zoom.us/j/2559106703?pwd YVFuVkxsZDk2NGRJU0tzREh3SDUzQT09

The public is welcome to attend.

PICS Colloquia: "Recent Advances in Modeling Subduction and Viscoelastic Flow in Geodynamic Computations"
2021-02-19 14:00 - 15:00 | Zoom – email kathom@seas.upenn.edu
Abstract: We will describe two separate but related methodologies that have been implemented in the open source, finite element code ASPECT, which computational geophysicists use to model a wide variety of problems that arise in Earth and Planetary geophysics. The first technique is a volume-of-fluid (VOF) interface tracking algorithm that was originally designed to model the subduction of the oceanic lithosphere of a tectonic plate beneath a less dense lithosphere of a second plate. However, we have since used this VOF methodology to model some basic laboratory experiments in order to benchmark some of the rheological models that have been implemented in ASPECT. The second technique is the particle or particle-in-cell (PIC) methodology, which we have been developing and benchmarking for use in ASPECT for the past seven years or so. This PIC methodology has been shown to have excellent weak and strong scaling over at least three orders of magnitude of model size on a uniform grid. In addition, our PIC algorithm shows that strong scaling for the adaptive grid case is nearly as good as for the uniform grid case, decreasing the total runtime essentially linearly from 96 to 3,072 cores. We will briefly show a collection of benchmarks we have used and developed to assess the accuracy of this PIC methodology and conclude with a description and video of a beam bending in a less dense viscoelastic medium due to the force of gravity in which the viscoelastic rheology is modeled by the components of stress that are carried on the particles and interpolated onto the underlying finite element grid at each time step.

ODEI Spotlight: A Conversation with Stacey Abrams
2021-02-19 12:00 - 13:30 | PA
Please join us on February 19th at noon EST for a conversation with Stacey Abrams, moderated by Benjamin Todd Jealous and with remarks from President Amy Gutmann.
The event is sponsored by the Annenberg School for Communication, the University of Pennsylvania Carey Law School, the Stavros Niarchos Foundation Paideia Program, and the Penn Provost’s Office.
Register Here.
If you would like to ask Stacey Abrams a question at the event, please submit it in advance using this link.

ESE Seminar: "(Re)building Human Dexterity: Inferring Musculoskeletal Dynamics for Next-Generation Assistive Devices & Diagnostics"
2021-02-19 12:00 - 13:00 | Zoom – Email ESE for Link jbatter@seas.upenn.edu
While there exist a number of mechanically sophisticated exoskeletons, prostheses, and assistive robots, with articulations similar to those of the intact human arm and hand, these devices remain limited in their ability to augment human dexterity and safely interact with human users and collaborators. In particular, due to the limits of conventional sensing, robots remain locked in industrial cages, prosthesis users can often modulate only a single degree of freedom, and when human–device interactions do occur, we have almost no understanding of the resulting physiological impacts on the user’s musculoskeletal system.
In this talk, I will discuss my work addressing these dual problems of device capability and safety by leveraging two novel signal classes — muscle deformation, as measured via ultrasound, and vibration, as measured via acoustic myography (AMG) — to probe individual muscle forces, which cannot currently be measured noninvasively but are key to understanding musculoskeletal dynamics during dexterous motion. Specifically, I will address our progress in precisely characterizing these signals and their relationship to muscle output force, and in measuring them in real time, paving the way for future research on the extraction of multiple independent signals for high-dimensional device control and enhanced overall understanding of the joint human–machine dynamical system, both healthy and pathological.

GRASP On Robotics: “Trajectory Planning Using Dynamic and Power Models: a Heuristics-Based Approach”
2021-02-19 11:00 - 12:30 | https://upenn.zoom.us/j/96715197752
Abstract: Robot planning is needed for robots to perform purposeful missions in their environments. In realistic situations, planning does not simply involve getting to a desired destination without collisions, but often requires achieving a desired goal configuration in an optimal or near-optimal fashion. Common optimality criteria include minimum distance, minimum time, and minimum energy. To plan feasible robot motions, it is necessary to take into account robot dynamics and/or power models along with motion constraints imposed by the actuators and the environment, which are kinodynamic motion planning problems. In addition, due to the dynamic nature of the robot environments and the uncertainties in locomotion, robots must be able to plan and replan trajectories in a computationally efficient manner. This seminar reviews Sampling Based Model Predictive Optimization (SBMPO), a motion planning framework capable of addressing the needs expressed above. The seminar will present the usage of heuristics and also discuss early results on learning models and heuristics.

CIS Seminar: "Enabling Hyperscale Web Services"
2021-02-18 15:00 - 16:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
Abstracts:
Current hardware and software systems were conceived at a time when we had scarce compute and memory resources, limited quantity of data and users, and easy hardware performance scaling due to Moore’s Law. These assumptions are not true today. Today, emerging web services require data centers that scale to hundreds of thousands of servers, i.e., hyperscale, to efficiently process requests from billions of users. In this new era of hyperscale computing, we can no longer afford to build each layer of the systems stack separately. Instead, we must rethink the synergy between the software and hardware worlds from the ground up.
In this talk, I will focus on re-thinking (1) software threading and concurrency paradigms and (2) data center hardware architectures. First, I will detail μTune, my software threading framework that is aware of the overheads induced by the underlying hardware’s constraints. Then, I will discuss SoftSKU and Accelerometer—my proposals to answer the question of: How should we build data center hardware for emerging software paradigms in the post-Moore era? Finally, I will conclude by describing my ongoing and future research towards re-designing the systems stack to enable the hyperscale web services of tomorrow.

BE Seminar: "Engineering Synthetic Biomaterials for Islet Transplantation" (María M. Coronel)
2021-02-18 15:00 - 16:00 | PA
This event will be held virtually via Zoom (check email or contact ksas@seas.upenn.edu).
Two major challenges to the translation of cellular-based tissue-engineered therapies are the lack of adequate oxygen support post-implantation and the need for systemic immunosuppression to halt the strong inflammatory and immunological response of the host. As such, strategies that aim at addressing oxygen demand, and local immunological responses can be highly beneficial in the translation of these therapies. In this seminar, I will focus on two biomaterial strategies to create a more favorable transplant niche for pancreatic islet transplantation. The first half will describe an in-situ oxygen-releasing biomaterial fabricated through the incorporation of solid peroxides in a silicone polymer. The implementation of this localized, controlled and sustained oxygen-generator mitigates the activation of detrimental hypoxia-induced pathways in islets and enhances the potency of extrahepatic 3D islet-loaded devices in a diabetic animal model. In the second part, I will focus on engineering synthetic biomaterials for the delivery of immunomodulatory signals for transplant acceptance. Biomaterial carriers fabricated with polyethylene glycol microgels are used to deliver immunomodulatory signals to regulate the local microenvironment and prevent allograft rejection in a clinically relevant pre-clinical transplant model. The use of synthetic materials as an off-the-shelf platform, without the need for manipulating the biological cell product, improves the clinical translatability of this engineered approach. Designing safer, responsive biomaterials to boost the delivery of targeted therapeutics will significantly reinvigorate interventional cell-based tissue-engineered therapies.

ESE PhD Dissertation Defense: "Enhanced Nonlinearity Enabled via Doped ENZ Metastructures: Theory & Potential Applications"
2021-02-18 13:00 - 15:00 | Zoom – Email nahvi@seas.upenn.edu for link
Synthetic composite structures, known as metamaterials, have been increasingly applied in
the past two decades in numerous applications for obtaining electromagnetic characteristics far beyond
naturally occurring materials. In particular, epsilon-near-zero (ENZ) media are a special category of
metamaterials which have been shown to exhibit exotic wave-matter interaction properties, rendering
them suitable for numerous applications. Exploiting the distinctive property of spatial uniformity of the
magnetic field in 2D ENZ (i.e. infinitely extended along a given direction) media, it has been recently
theoretically and experimentally demonstrated that a 2D ENZ body doped with a dielectric inclusion is
equivalent to a magnetic ENZ medium for an outside observer, a concept coined “photonic doping”. In
this dissertation, I theoretically extend this concept for additional classes of inclusions and propose
several potential applications harnessing the peculiar electromagnetic characteristics of such structures.

ODEI Spotlight: The Masc We Live In - Cultural Implications of Masculinity
2021-02-17 17:00 - 18:00 | PA
Join us as we host an open discussion on masculinity in different cultural contexts and the intersections of race, religion and other factors which influence how we view, interpret, and navigate masculinity. This is the first of four conversations in our ongoing discussion series for the Spring Semester. All gender identities welcome. The event is open to all members of the campus community (students, faculty, staff, and alum)
https://vpul-upenn.zoom.us/j/96122940110?pwd=[REDACTED]
Meeting ID: 961 2294 0110
Passcode: [REDACTED]

Spring 2021 GRASP SFI: “Model-Based Deep RL for Robotics”
2021-02-17 15:00 - 16:00 | PA
Abstract: Deep learning has shown promising results in robotics, but we are still far from having intelligent systems that can operate in the unstructured settings of the real world, where disturbances, variations, and unobserved factors lead to a dynamic environment.
In the first part of the talk, I will show that model-based deep RL can indeed allow for efficient skill acquisition, as well as the ability to repurpose models to solve a variety of tasks. I will then scale up these approaches to enable locomotion with a 6-DoF legged robot on varying terrains in the real world, as well as dexterous manipulation with a 24-DoF anthropomorphic hand in the real world.
In the second part of the talk, I will focus on the inevitable mismatch between an agent’s training conditions and the test conditions in which it may actually be deployed, thus illuminating the need for adaptive systems. Inspired by the ability of humans and animals to adapt quickly in the face of unexpected changes, I will present a meta-learning algorithm within this model-based RL framework to enable online adaptation of large, high-capacity models using only small amounts of data from the new task. These fast adaptation capabilities are seen in both simulation and the real-world, with experiments such as a 6-legged robot adapting online to an unexpected payload or suddenly losing a leg. Finally, I will further extend the capabilities of our robotic systems by enabling the agents to reason directly from raw image observations. Bridging the benefits of representation learning techniques with the adaptation capabilities of meta-RL, I will present a unified framework for effective meta-RL from images. With robotic arms in the real world that learn peg insertion and ethernet cable insertion to varying targets, I will show the fast acquisition of new skills, directly from raw image observations in the real world.
I conclude that model-based deep RL provides a framework for making sense of the world, thus allowing for reasoning and adaptation capabilities that are necessary for successful operation in the dynamic settings of the real world.
Join the Zoom Meeting here

CIS Seminar: "IDEs for Ideas"
2021-02-17 15:00 - 16:00 | PA
Abstract:
A Jupyter notebook, a preprint from arXiv, and a Stack Overflow code snippet. What do they all have in common?
All convey complex ideas from a writer to an audience. However, the tools to create and read them have not kept pace with the complexity of their contents. What would it look like if we had tools as sophisticated as state-of-the-art IDEs (integrated development environments, like Visual Studio or IntelliJ) for authoring and reading these artifacts? What interactions would they provide? What algorithms and models would they need?
In this talk, I discuss novel core requirements for reading and writing complex information artifacts, and reify these in the design and implementation of IDEs for Ideas. One IDE lets you click on results in a messy Jupyter notebook and trace the code that computed it. Another brings the meaning of scientific papers to life. Come to this talk to learn about the challenges we face using complex information artifacts every day, a vision of how our tools should help, systems embodying this vision with novel interactions and algorithms, and evidence from usability studies validating their design.

CBE Seminar: "Insights into Active Site Structures for Bimetallic Heterogeneous Catalysts"
2021-02-17 15:00 - 16:00 | Zoom – Email CBE for link
Abstract
I will describe three examples investigating the use of bimetallic catalysts for reaction systems of industrial relevance and explore the origins of their improved performance. Investigation of Pd-based bimetallic catalysts for the selective hydrogenation of acetylene and for hydrodechlorination of 1,2-dichloroethane will be explored. Additionally, Pt-based bimetallic catalysts for the hydrogenation of a model α,β-unsaturated aldehyde, citral, will be described. These reaction systems serve as examples of (i) improving existing reaction processes, (ii) producing valuable products from waste streams, and (iii) developing more environmentally friendly routes to producing existing products, demonstrating the variety of ways in which improved catalysts can impact the chemical industry. The insights into active site structures for bimetallic catalysts developed in this work are an example of how structure-performance relationships can enable the development of improved catalytic materials. As a result, such catalysts can be used in industrial processes to reduce use of toxic and costly chemicals and solvents as well as decrease energy requirements, moving forward towards a more sustainable future.

CIS Seminar: "Structural Foundations of Efficient Reinforcement Learning:
2021-02-16 15:00 - 16:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
Abstract:
The design of learning agents which observe, interact with, and manipulate their environment to optimize desirable behaviors is a long-standing goal in machine learning, with roots in artificial intelligence, adaptive experimental design and adaptive feedback control. In machine learning, these questions are typically studied in the area of reinforcement learning (RL), which has seen a recent surge of interest both due to potential applications, from robotics and autonomous systems to healthcare and recommendations; as well as popular successes such as superhuman performance in games and dexterous manipulation of a Rubik’s cube.
On the theoretical front, foundations for sample efficient learning were laid in the early 2000’s, for problems where the agent perceives the environment through relatively simple observations. However, these settings fail to capture the complex sensorimotor observation streams which most application domains naturally contain. In this talk, I will describe a research program aimed at addressing this critical gap in our theoretical understanding.
I will begin by highlighting some key challenges faced by an RL agent, and the importance of understanding the structure of real-world applications to address these challenges. With this aim, I will then introduce a complexity measure, called Bellman rank, for general RL problems. Crucially, many application domains naturally exhibit a small Bellman rank, and I will describe how low Bellman rank enables sample efficient RL. Bellman rank remains one of the most general ways of measuring the complexity of RL problems, however, computationally practical algorithms for all problems with a small Bellman rank still elude us.
The second part of the talk will focus on algorithmic questions, designing optimization-based methods for solving a subclass of problems with a small Bellman rank. I will present an algorithm Policy Cover Policy Gradient (PC-PG), which comes with strong practical guarantees when the problem dynamics obey a certain linear structure. The algorithm is highly practical, and easily composes with modern deep learning libraries for an efficient implementation. I will confirm its effectiveness beyond the confines of the theoretical assumptions in empirical evaluation against popular baselines.
Finally, I will conclude with a brief synopsis of work I have done on Contextual Bandits, a much smaller, yet practically useful subclass of RL. The research here has led to the design and creation of a general purpose cloud service at Microsoft, which powers many applications of Contextual Bandits both inside and outside the company.
The first two parts of the talk are based on the papers https://arxiv.org/abs/1610.09512 and https://arxiv.org/pdf/2007.08459.pdf respectively.

PSOC Webinar: "Sensing Matrix Rigidity: Transducing Mechanical Signals From Integrins to the Nucleus" (Pere Roca-Cusachs Soulere)
2021-02-15 12:00 - 13:00 | PA
