Penn Engineering Events

BE Doctoral Dissertation: "Development of Hyperpolarized Xenon-129 Imaging Approaches for Assessing Lung Transplantation" (Faraz Amzajerdian)
2023-12-18 11:00 - 13:00 (America/New_York) | Donner-Grice Auditorium
The Department of Bioengineering at the University of Pennsylvania and Dr. Rahim Rizi are pleased to announce the Doctoral Dissertation Defense of Faraz Amzajerdian.

Title: “Development of Hyperpolarized Xenon-129 Imaging Approaches for Assessing Lung Transplantation”.

Date: Monday, December 18, 2023
Time: 11:00 AM
Location: Donner-Grice Auditorium (HUP Dulles Building 2nd floor)

The public is welcome to attend.

Herman P. Schwan Distinguished Lecture: “Seeing the Unseen: How AI Redefines Bioengineering” (Dorin Comaniciu, Siemens Healthineers)
2023-12-13 13:00 - 15:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract coming soon. The lecture and Q&A will be followed by a light reception in Levine Lobby.
The Herman P. Schwan Distinguished Lecture is in honor of one of the founding members of the Department of Bioengineering, who emigrated from Germany after World War II and helped create the field of bioengineering in the US. It recognizes people with a similar transformative impact on the field of bioengineering.

ESE Fall Seminar - "Magnetic technologies for battery-free bioelectronics and neuromodulation"
2023-12-12 15:00 - 16:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Miniature implanted and injected technologies capable of manipulating and recording biological signals promise to improve the way we study biology and the way we diagnose and treat disease; however, to create an effective bioelectronic network we must overcome myriad engineering challenges. In this talk, I will describe how we can leverage unique material properties to overcome some of these challenges. Specifically, I will show how magnetoelectric materials allow us to effectively transmit data and power to mm-sized devices deep inside the body. I will also describe how we can engineer fast magnetic control of genetically targeted neurons. Overall, these technologies provide a suite of miniature interfaces that could support next-generation brain-computer interfaces and closed-loop electronic medicine.

Fall 2023 GRASP Seminar: Yufei Ye, Carnegie Mellon University, "Predicting and Reconstructing Everyday Human Interactions"
2023-12-12 13:15 - 14:15 | Levine 512
*This seminar will be held in-person in Levine 512 with virtual attendance via Zoom. The seminar will NOT be recorded.
ABSTRACT
In this talk, I will discuss about building computer vision system that understands everyday human interactions with rich spatial information, in particular hand-object interactions (HOI). Such systems can benefit VR/AR to perceive reality and to modify its virtual twin, and robotics to learn manipulation by watching humans. Previous methods are limited to constrained lab environments or pre-selected objects with known 3D shapes. My works explore learning general interaction priors from large-scale data that can generalize to novel everyday scenes for both perception and prediction.
The talk consists of two parts. The first part focuses on HOI prediction — predicting plausible human grasps for any objects. We found that image synthesis serves as a shortcut for 3D prediction for better generalization. The second part focuses on reconstructing interactions in 3D space for generic objects by leveraging data-driven prior, including from single images and everyday video clips.

CBE Doctoral Dissertation: "From Nanoplates to Bottlebrushes: Engineering Thermodynamics in Polymer Nanocomposites" (Christian Tabedzki)
2023-12-11 16:30 - 18:00 | DRL A2
Abstract: Polymer nanocomposites (PNCs) represent a diverse class of materials where manipulating design parameters is crucial for tailoring material properties. Of utmost importance for nanocomposites is nanoparticle dispersion, which is affected by the nanoparticle itself as well as the overall polymer melt, providing two design routes. This dissertation explores PNCs through two distinctive systems: (1) nanoplates grafted with polymers in a linear diblock copolymer matrix and (2) bare nanospheres in a core-shell bottlebrush matrix. The investigation advances the understanding of nanoparticle dispersion in linear diblock copolymer matrices and unveils the thermodynamics of a novel core-shell bottlebrush architecture. The initial focus on grafted nanoplates in linear diblock copolymers employs a hybrid particle/self-consistent field theory (hSCFT) to reveal the impact of nanoparticle insertion on polymer interfaces and exploring nanoparticle dispersion and inter-particle distance. The subsequent chapter extends this work, exploring diverse polymer matrix molecular weights and demonstrating the dependence of free energy minima on nanoplate size relative to lamellar domain dimensions. Shifting to a novel polymer architecture called core-shell bottlebrush copolymer, the analysis investigates the order-to-disorder transition, chain conformations, and thermodynamic integration of nanospheres. The research provides insights into the preference of nanoparticle localization within the bottlebrush structure, influenced by surface area considerations. Future work is proposed, including a comprehensive phase diagram exploration for core-shell bottlebrushes, expanded nanoparticle studies, and refinement of the liquid crystalline model to capture experimental complexities, emphasizing the need for continuous improvement in modeling PNCs to align with evolving experimental insights.
Christian Tabedzki is a Ph.D. student advised by Prof. Robert Riggleman in the Department of Chemical and Biomolecular Engineering at the University of Pennsylvania. Christian received his bachelor’s degree in chemical engineering at Rutgers University in New Jersey. His research focuses on the grafted polymer nanoplates within a lamellar system and spherical nanoparticles within core-shell bottlebrush copolymers.

Advisor: Robert Riggleman (CBE)

Committee Members: Russell Composto (MSE), Chinedum Osuji (CBE), Amish Patel (CBE)

Fall 2023 GRASP on Robotics: Marc Miskin, University of Pennsylvania, "Tiny Robots"
2023-12-08 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 on Zoom.
ABSTRACT
Nature routinely makes smart, complex, yet microscopically tiny machines. But how can humans do it? And can we do it in a way that is easy to design and understand? This talk is about building microscopic robots, those too small to see with the naked eye. By co-opting semiconductor technology, I’ll show how to build fully autonomous, programmable micro-robots. These machines pack memory, microprocessors, communication systems, sensors, actuators, and on-board power into a single package too small to see by eye. I’ll show several types of tiny robots including quadrupeds, hexapods and even some that use solid-state electrokinetic propulsion mechanisms to swim. Finally, I’ll discuss early applications, including a project to regrow damaged nerves by using robots to literally pull them where they need to go.

PRECISE Seminar: Formal Methods for Computer Architecture: Reducing the Barriers to Entry
2023-12-08 10:00 - 11:00 | Room 307, Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Formal methods can provide strong correctness guarantees for today’s computing systems, but their usage is often restricted to formal methods experts. Formal verification is then bottlenecked on these experts, limiting its effectiveness. This problem is acute in computer architecture, since many architects do not have formal methods expertise.

In this talk, I will present recent work with my students and collaborators that reduces the barriers to entry for computer architects to use formal methods. First, I will discuss our work on automatically generating formal microarchitectural models of hardware. These models are necessary for microarchitectural verification, and generally need to be written by hand by formal methods experts. In contrast, our work can automatically generate such models from accessible inputs like test programs and execution traces or from hardware RTL implementations. These models can then be used for formal verification of memory consistency and hardware security using known automated verification techniques. I will also speak briefly on our technique for automated verification of cyber-physical systems written in the Lingua Franca coordination language.
Meanwhile, we also need to develop formal models and verification techniques for emerging architectures that significantly change the hardware-software interface. As an example, I will discuss our ongoing work on developing a verified programming model for a recent non-traditional memory hierarchy. I will conclude with our work on automatically converting axiomatic formal models to their operational equivalents, enabling each type of model to be used for the tasks it handles best.

MSE Grace Hopper Lecture: "Quantum Simulations for Quantum Technologies," (Giulia Galli - University of Chicago)
2023-12-07 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
In this talk, I will describe theoretical and computational strategies based on quantum mechanical calculations, aimed at predicting material properties suitable for the development of quantum technologies. Specifically, I will discuss the electronic structure and coherent states of spin defects in two- and three-dimensional semiconductors and insulators, obtained using both classical and near-term quantum computers.

CBE Seminar: "Fabrication and Long-term Reliability of High Efficiency Monocrystalline Silicon Solar Cells" (Agarwal, Colorado School of Mines)
2023-12-06 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Global energy demand will continue to increase, and the ability of fossil fuels to meet these demands is limited due to the associated climate change concerns. In response to these concerns, new energy installations are increasingly based on renewable energy resources such as wind and solar. To further develop solar energy as a renewable energy resource, it is critical to improve the efficiency and reliability of silicon-based solar cells, which represent more than 95% of the current photovoltaics market. In this presentation, I will discuss strategies to improve the efficiency of silicon solar cells via passivating contacts, which serve both as a contact layer and a passivation layer for the crystalline silicon (c-Si) surface. These types of contacts are currently being incorporated into the next-generation industrially-manufactured cSi solar cells. I will discuss the fabrication of these contacts, the underlying principle for charge transport through these contacts, and their performance on both planar and textured surfaces. I will also discuss field degradation mechanism of c-Si solar cells, and describe strategies that can be implemented to suppress these defects.

Fall 2023 GRASP SFI: Ge Yang, NSF Institute of AI and Fundamental Interactions and MIT CSAIL, "Feature Fields for Robotics: Language-Grounded Perception and Mapping at Multiple Scales"
2023-12-06 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 on Zoom.
ABSTRACT
What kind of representation do robots need in order to be as generally capable as humans in handling unseen scenarios? Recent work in vision and vision-language foundation models has become quite good at telling what is in a scene, but they do not capture the geometry needed for handling physical contact. State-of-the-art methods in inverse graphics capture detailed 3D geometry, but they are missing the semantics. In this talk, I will present a way to combine accurate 3D geometry with rich semantics into a single representation format called distilled feature fields and ways to use this representation for perception during few-shot manipulation with a robotic arm. Using features sourced from the vision-language model, CLIP, our method allows the user to designate novel objects for manipulation via free-text natural language, and can generalize to unseen expressions and novel categories of objects. I will also present ways to scale feature fields up for building maps and the dual purpose of building realistic physics simulators for reinforcement learning. Finally, I will present our recent effort in building a unified representation for semantics, geometry, and physics called Feature Splatting.

ASSET Seminar: "Robust Machine Learning with Foundation Models" (Aditi Raghunathan, Carnegie Mellon University)
2023-12-06 12:00 - 13:15 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
In recent years, foundation models—large pretrained models that can be adapted for a wide range of tasks—have achieved state-of-the-art performance on a variety of tasks. While the pretrained models are trained on broad data, the adaptation (or fine-tuning) process is often performed on limited data. As a result, the challenges of distribution shift, where a model is deployed on a different distribution as the fine-tuning data remain, albeit in a different form.
First, via experiments on pretrained vision and language models, we show different kinds of “catastrophic forgetting’’ where pretrained information is forgotten and correspondences between and in-distribution and out-of-distribution features are weakened. As a result, fine-tuned models are not maximally robust to distribution shifts. We then provide new fine-tuning and prompting methods, backed by theoretical insights, that minimize such distortion and vastly improve accuracy and robustness. On the flip side, our work shows that pretrained knowledge can be hard to get rid of, thereby underlining the potential perils of overreliance on fine-tuning for safety.

Fall 2023 GRASP Seminar: Shangzhe Wu, Stanford University, "Learning 3D Fauna and Flora in the Wild"
2023-12-06 10:30 - 11:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Raisler Lounge and virtual attendance on Zoom.
ABSTRACT
Nature presents a captivating confluence of diversity and similarity. In order to make sense of our visual experiences in the world, humans as well as other natural intelligences are innately adept at recognizing the underlying intrinsic patterns, by simply looking at 2D projections of a constantly evolving 3D environment. Designing unsupervised perception systems to do the same is not only key to many AR/VR and robotics applications, but also a cornerstone for understanding visual perception in general. In pursuit of this ultimate goal, this talk will mainly focus on a recent line of effort in learning dynamic 3D objects like animals, simply from casually-recorded, unlabeled Internet images and videos. In addition, I will also briefly discuss a few other relevant works on inverse rendering, visual concept learning and spatial audio synthesis, which, collectively, attempt to explore the various aspects of our experiences in the natural world.

CIS Grace Hopper Distinguished Lecture: "AGI is Coming… Is HCI Ready?"
2023-12-05 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
We are at a transformational junction in computing, in the midst of an explosion in capabilities of foundational AI models that may soon match or exceed typical human abilities for a wide variety of cognitive tasks, a milestone often termed Artificial General Intelligence (AGI). Achieving AGI (or even closely approaching it) will transform computing, with ramifications permeating through all aspects of society. This is a critical moment not only for Machine Learning research, but also for the field of Human-Computer Interaction (HCI).

In this talk, I will define what I mean (and what I do NOT mean) by “AGI” (and related concepts, like superintelligence), and my journey from AGI skeptic to believing we are within five years of reaching this milestone. I will then discuss how this new era of computing necessitates a new sociotechnical research agenda on methods and interfaces for studying and interacting with AGI. For instance, how can we extend status quo design and prototyping methods for envisioning novel experiences at the limits of our current imaginations? What novel interaction modalities might AGI (or superintelligence) enable (e.g., “ESP”)? How do we create interfaces for computing systems that may intentionally or unintentionally deceive an end-user? How do we bridge the “gulf of evaluation” when a system may arrive at an answer through methods that fundamentally differ from human mental models, or that may be too complex for an individual user to grasp? How do we evaluate technologies that may have unanticipated systemic side-effects on society when released into the wild?

I will close by reflecting on the relationship between HCI and AI research. Typically, HCI and other sociotechnical domains are not considered as core to the ML research community as areas like model building. However, I argue that research on Human-AI Interaction and the societal impacts of AI is vital and central to this moment in computing history. HCI must not become a “second class citizen” to AI, but rather be recognized as fundamental to ensuring the path to AGI and beyond is a beneficial one.

MEAM Seminar: "Computational Design of Origami and Compliant Robots"
2023-12-05 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Soft and compliant robots provide new opportunities for machines that are flexible, adaptable, safe, and robust. Origami-inspired engineering enables custom robots to be designed and fabricated within days, or even hours. These robots are capable of executing a variety of shape-changing and dynamical tasks by taking advantage of their folded shape and programmable mechanics. In this talk, I will show how the kinematics and compliance of a thin-shell mechanism can be designed algorithmically. I will also discuss how we can leverage these designs for better performance and simpler control, and how these approaches provide robots with capabilities such as dynamical hopping, swimming, and flight.

MSE Thesis Defense: "Grain Boundary Structural Responses to Dislocation Loop Absorption"
2023-12-04 16:30 - 18:00 | zoom email johnruss@seas.upenn.edu for the link
This talk aims to describe GB responses to absorption of dislocation loops, as part of increasing understanding of component phenomena of radiation damage in materials. The context of radiation damage in materials and the broader importance of understanding related material behavior are summarized, as well as some background on grain boundary structure and defects, and approaches are introduced that will be used throughout the defense. Initially, the discussion presents cases of a Sigma-5 (210)[001] symmetric tilt grain boundary in bcc-Fe responding to absorption of different sizes of interstitial and vacancy loops, which exhibit both a DSC-disconnection reaction and some extent of a state change response concurrently, with extent of each depending on the size and character of the inbound loop. The next case presented details state changes observed in a Sigma-5 (012)[100] STGB in (bcc) Mo after absorption of interstitial loops. The presentation then explores disconnection reaction response to interstitial loop absorption in two Sigma-13 STGBs in Mo. Comparisons and contrasts are drawn between the initial Fe case, which exhibits multiple concurrent response types, and the Mo cases, which each present a single type of response. My defense then presents an approach to characterize defect absorptions by GBs in experimental settings by linking atomistic descriptions of absorption phenomena with experimental Nye tensor measurement changes. Finally, the talk presents overarching conclusions from all of the work discussed, in the hope that understanding these cases of single-loop absorptions and resulting GB responses will then provide more detailed understanding of GB evolution (and factors affecting it) as more defects are absorbed.

BE Doctoral Dissertation: "Piezo1 regulation of muscle stem cell heterogeneity and function and skeletal muscle generation" (Nuoying Ma)
2023-12-04 09:30 - 11:30 | CRB Auditorium, 415 Curie Boulevard, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Foteini Mourkioti are pleased to announce the Doctoral Dissertation Defense of Nuoying Ma.

Title: Piezo1 regulation of muscle stem cell heterogeneity and function and skeletal muscle generation.
Date: Monday, December 4, 2023
Time: 9:30AM
Location: CRB Austrian Auditorium
Zoom link: https://us06web.zoom.us/j/81956870491?pwd=[REDACTED]

The public is welcome to attend.

Fall 2023 GRASP on Robotics: Nancy Amato, University of Illinois at Urbana-Champaign, “Sampling-Based Task and Motion Planning: From Robotic Manipulators to Intelligent CAD to Analyzing Proteins”
2023-12-01 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 on Zoom.
ABSTRACT
Task and motion planning has application in robotics, animation, virtual prototyping and training, and even for seemingly unrelated tasks such as evaluating architectural plans or simulating protein motions. Surprisingly, sampling-based methods have proven effective on problems from all these domains. In this talk, we provide an overview of sampling-based planning and describe some methods developed in our group, including strategies suited for collaborative task planning, multi-agent systems, and analyzing bio-molecules.
We will finish with a short introduction of our new Mind in Vitro NSF Expeditions project in which we will use neurons grown from mouse stem cells to build simple devices that can be composed to form more complex systems. We plan to train these systems to obtain behaviors which can be used to build programmable bio-robots.

PRECISE Seminar: Protecting Health Care & Cyberphysical Systems - Wicked Bizarre Semiconductor Physics of Sensor Security
2023-12-01 10:00 - 11:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Medical devices, healthcare delivery, and other cyber-physical systems depend on sensors to make safety-critical, automated decisions. My research lab investigates the problem of how to protect cyber-physical systems from adversaries who can maliciously control sensor output by subverting its semiconductor physics. Finding principled, systematic solutions is extremely important to give consumers confidence in innovative medical devices and other emerging technology. Unique to our embedded security research contributions is an emphasis on protecting the longevity of implanted batteries and using software-only approaches to mitigate design flaws in legacy hardware. These contributions were important to creating the field of medical device security; advancing the academic community’s ability to measurably defend against signal injection attacks on sensors; and changing how international regulators evaluate security of consumer products. In this talk, I will highlight academic research on protecting sensor semiconductors from maliciously modulated sound waves, radio waves, and lasers that can compromise software systems in cyber-physical systems such as pacemakers and vaccine cold-chain transportation. Prof. Fu’s lab at Northeastern University in Boston is recruiting highly motivated PhD students from Electrical & Computer Engineering, Computer Science, or Biomedical Engineering for (1) technology and public policy research on health care and medical device security engineering, or (2) research based on the physics of optics, RF, acoustics, and high frequency pulsed lasers for improving sensor semiconductor hardware security.

CBE Doctoral Dissertation: "Understanding and Controlling Polymer-Porous Solid Interactions for Catalytic Recycling of Polymers" (Tian Ren)
2023-12-01 09:00 - 11:00 | Berger Auditorium (Room 13), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
Abstract:

Understanding and controlling polymer-solid interactions is critical for optimizing the catalytic processes involved in polymer upcycling. In this Ph.D. thesis, I explored the intricacies of polymer behavior in nanoporous materials by monitoring the capillary infiltration dynamics of polystyrene (PS) and polyethylene (PE) into random packings of silica nanoparticles. To test the effect of surface chemistry without changing the structure and size of nanopores, these silica nanoparticle packings were modified with TiO 2 , WO 3 , and CaCO 3 using atomic layer deposition (ALD). Based on the Lucas-Washburn model, I quantified the polymer-porous solid interactions using contact angles and interfacial energies, finding a negative correlation between specific adsorption behaviors of small molecules and interfacial energies of polymers. Furthermore, I investigated the confinement effect, observing that the effective viscosity of polymer confined in sub-20 nm pores is inversely related to pore size. Changing the surface chemistry or polymer structure did not affect this inverse relationship, indicating the dominant role of physical confinement on the translational dynamics of PE. I also assessed the melting points of PE when confined within porous media. I observed a consistent decrease in the melting point as the pore size was reduced, down to a threshold of 11 nm. Below this size, the melting point stabilized and remained constant. These findings on the effect of surface chemistry and pore size on the dynamics and thermal properties of polymers potentially provide important insights and guidelines in designing efficient polymer upcycling reactions.

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Date: Friday, December 1, 2023
Time: 9:00 AM – 11:00 AM
Location: Berger Auditorium, Skirkanich
Zoom link: https://upenn.zoom.us/j/99057767904?pwd=[REDACTED]

CIS Seminar: "Diffusion Models in Computer Vision"
2023-11-30 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Denoising diffusion models represent a recent emerging topic in computer vision, demonstrating impressive results in generative modeling. A diffusion model is a deep generative model that is based on two stages, a forward diffusion stage and a reverse diffusion stage. In the forward diffusion stage, the input data is gradually perturbed over several steps by adding Gaussian noise. In the reverse stage, a model is tasked at recovering the original input data by learning to gradually reverse the diffusion. Diffusion models are widely appreciated for the quality and diversity of the generated images. In this talk I will present our recent work on how diffusion models can be employed for solving computer vision problems. First, I will discuss temporal action segmentation for comprehending human behaviors in complex videos, which aims to process a long video and produce a sequence that delineates the action category for each frame. I will present a framework based on the denoising diffusion model that iteratively produces action predictions starting with random noise, conditioned on the features of the input video. To effectively capture three key characteristics of human actions, namely the position prior, the boundary ambiguity, and the relational dependency, we propose a cohesive masking strategy for the conditioning features. Next, I will briefly discuss how diffusion models are employed to solve the problems of person image synthesis, cloth-changing person re-identification, and limited field of view cross-view geo-localization and present state of results.
Although the use of diffusion models has yielded positive results in text-to-image generation, there is a notable lack of research regarding the understanding of these models. For example, there is a rising need to understand how to design effective prompts that produce the desired outcome. Next, I will briefly talk about our ongoing work on Reverse Stable Diffusion: What prompt was used to generate this image? I will end this talk by briefly discussing our recent work that underscores the significance of incorporating symmetries into diffusion models, by enforcing equivariance to a general set of transformations within DDPM’s reverse denoising learning process.

BE Doctoral Dissertation Defense: "A robotic system for automated genetics of Caenorhabditis elegans" (John Zihao Li)
2023-11-30 14:00 - 16:00 | Greenberg Lounge (Room 114), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Christopher Fang-Yen are pleased to announce the Doctoral Dissertation Defense of John Zihao Li.

Title: A robotic system for automated genetics of Caenorhabditis elegans.

Date: Thursday, November 30, 2023
Time: 2:00pm
Location: Greenberg Lounge, 114 Skirkanich Hall

Zoom Option:
https://upenn.zoom.us/j/5692069917?pwd=[REDACTED]
Meeting ID: 569 206 9917
Passcode: [REDACTED]

The public is welcome to attend.

ESE Fall Seminar - "Electromagnetics for advanced power electronics and wireless power transfer"
2023-11-30 11:00 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Power electronics is an essential enabler for efficient energy utilization across many different applications as well for renewable electricity generation. Advances in power semiconductor materials and devices are improving power electronics capabilities, but power electronics also relies heavily on passive electromagnetic components—inductors, transformers, and capacitors. The capabilities of these components are increasingly the bottlenecks limiting improvements in efficiency and miniaturization of power electronics.
The fundamental limitations and scaling laws that make advances in passive components difficult will be outlined, and approaches to circumvent these limitations will be discussed, including co-design of circuits and components as well as electromagnetic design and modeling. Innovations discussed enable not only improved power converters but also wireless power transfer for medical and mobility applications.

MSE Seminar: "Aluminum Scandium Nitride Thin Films and Microdevices for Radio Frequency Filters and Magnetoelectric Sensors"
2023-11-30 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Aluminum Nitride (AlN) is a well-established thin film piezoelectric material. AlN bulk acoustic wave (BAW) radio frequency (RF) filters were one of the key innovations that enabled the 3G and 4G smart phone revolution. Recently, the substitutional doping of scandium (Sc) for aluminum (Al) to form aluminum scandium nitride (AlScN) has been studied to significantly enhance the piezoelectric properties and to introduce ferroelectric properties into AlN based material systems. The properties achieved have profound implications for the performance of future 5G and 6G RF filters, piezoelectric sensors, piezoelectric energy harvesters, and for scaling the bit density of ferroelectric nonvolatile memories (NMV). This talk will present on the synthesis of highly Sc alloyed AlScN materials of the thickness, stress, and crystallinity required for applications in microelectromechanical systems (MEMS). The material properties and device performance achieved will be reported and placed in the context of device specific figures-of-merit. Exemplar AlScN based RF and magnetoelectric sensor devices will be presented and discussed in the context of alternative technologies.

CBE Seminar: "Revolutionizing Bioimaging to Elevate Human Health"
2023-11-29 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Holistic imaging of diverse functional, anatomical, and molecular architecture that span multiple levels, from cells to an entire system, remains a major challenge in biology. In this talk, I will introduce a series of technologies that enable integrated multiscale imaging and molecular phenotyping of both animal tissues and human clinical samples. I will discuss how we engineer (1) the physicochemical properties of biological tissues, (2) molecular interactions, and (3) molecular transport all together to achieve integrated organ-wide 3D molecular analysis at unprecedented speed and resolution. I will also discuss how these technologies can be commercialized and deployed synergistically to study a broad range of biological questions.

Fall 2023 GRASP SFI: Xiaolong Wang, University of California San Diego, "Generalizable Geometric Robot Learning"
2023-11-29 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 on Zoom.
ABSTRACT
Robot learning has witnessed significant progress in terms of generalization recently, with the help of data-driven learning and image/text foundation models. While these achievements are encouraging, most tasks conducted in this context are relatively simple (e.g., pick-and-place with a parallel gripper). In this talk, I will talk about our recent efforts to learn generalizable skills focusing on tasks with rich physical contacts and geometric reasoning. Specifically, I will discuss our research on: (i) the use of a large number of low-cost, binary force sensors to enable Sim2Real manipulation; (ii) unifying 3D and semantic representation learning to generalize policy learning across diverse objects and scenes. I will showcase the real-world applications of our research, including dexterous manipulation, and legged locomotion control, and language-driven mobile manipulation.

CBE Doctoral Dissertation: “A Multiscale Computational Framework for Simulating Thrombus Growth Under Flow” (Kaushik Shankar)
2023-11-29 12:30 - 14:30 | Room 534 A Wing, 3401 Walnut, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:

Modeling thrombus growth in pathological flows allows evaluation of risk under patient-specific pharmacological, hematological, and hemodynamical conditions. To this end, we have developed a 3D multiscale framework for the prediction of thrombus growth under flow on a spatially resolved surface presenting collagen and tissue factor (TF). The multiscale framework is composed of four coupled modules: a Neural Network (NN) that accounts for platelet calcium signaling, a Lattice Kinetic Monte Carlo (LKMC) simulation for tracking platelet positions, a Finite Volume Method (FVM) simulator for solving convection-diffusion-reaction equations describing soluble agonist release and transport, and a Lattice Boltzmann (LB) flow solver for computing the blood flow field over the growing thrombus. A reduced model of the coagulation cascade was embedded into the framework to account for TF-driven thrombin production. The 3D model was first tested against in vitro microfluidics experiments of whole blood perfusion with various antiplatelet agents targeting COX-1, P2Y1, or the IP receptor. The model was able to accurately capture the evolution and morphology of the growing thrombus. Certain problems of 2D models for thrombus growth (artifactual dendritic growth) were naturally avoided with realistic trajectories of platelets in 3D flow. The generalizability of the 3D multiscale solver enabled simulations of important clinical situations, such as cylindrical blood vessels and acute flow narrowing (stenosis). Enhanced platelet-platelet bonding at pathologically high shear rates (e.g., von Willebrand factor unfolding) was required for accurately describing thrombus growth in stenotic flows.

To enable larger computations in a reasonable amount of time, each module within the multiscale framework was individually parallelized. Parallelization was achieved by developing in-house parallel routines for NN and LKMC, while the open-source libraries OpenFOAM and Palabos were used for FVM and LB, respectively. Importantly, the parallel LKMC solver utilizes particle-based parallel decomposition allowing efficient use of cores over highly heterogeneous regions of the domain. The parallelized model was validated against a reference serial version for accuracy, demonstrating comparable results for both microfluidic and stenotic arterial clotting conditions. Moreover, the parallelized framework was shown to scale essentially linearly on up to 64 cores for a benchmark simulation of thrombus growth in a stenotic vessel of size ~1 mm. Overall, the parallelized multiscale framework allows consideration of patient-specific platelet signaling and vascular geometry for the prediction of thrombotic episodes.

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Date: Wednesday, November 29, 2023
Time: 12:30 PM
Location: PICS Room 534, 3401 Walnut Street
Zoom link: https://upenn.zoom.us/j/99504914980

ASSET Seminar: "Inherent Interpretability via Language Model Guided Bottleneck Design" (Mark Yatskar, Penn)
2023-11-29 12:00 - 13:15 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
As deep learning systems improve, their applicability to critical domains is hampered because of a lack of transparency. Post-hoc explanations attempt to address this concern but they provide no guarantee of faithfulness to the model’s computations. Inherently interpretable models are an alternative but such models are often considered to be too simple to perform well. In this talk we challenge this assumption by demonstrating how to create high performance inherently interpretable models. Our methods extend concept bottlenecks, a class of inherently interpretable models, by casting their creation as a generation problem for large language models. This allows us to develop search routines for finding high performing bottlenecks. We specialize this general approach to image classification, text classification, and visual question answering. In these domains, language model guided bottleneck models perform competitively to their uninterpretable counterparts and in low-data settings even sometimes outperform them.

PSOC Seminar: Denise Montell, University of California, Santa Barbara
2023-11-29 12:00 - 13:00 | DRL 2N3
PSOC@Penn Seminar,
Wednesday Nov 29th

** New Location **

DRL 2N3
2N3 conference/seminar room is in DRL 2nd floor towards end of hallway that parallels Walnut St

-Noon – 1.00pm : PSOC talk
Speaker: Denise Montell, PhD
Duggan Professor and Distinguished Professor,
Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
https://www.mcdb.ucsb.edu/people/faculty/denise-montell
https://denisemontell.mcdb.ucsb.edu/
Talk : “TBA”
Contact manu@seas.upenn.edu with any questions.

CIS Seminar: "Mitigating Technology Abuse in Intimate Partner Violence and Encrypted Messaging"
2023-11-28 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Computer security is traditionally about the protection of technology, whereas trust and safety efforts focus on preventing technology abuse from harming people. In this talk, I’ll explore the interplay between security and tech abuse, and make the case that trust and safety represents an important frontier for computer security researchers. To do so, I’ll draw on examples from two lines of my recent work.
First, I’ll overview our work on technology abuse in the context of intimate partner violence (IPV). IPV is a widespread social ill affecting about one in four women and one in ten men at some point in their lives. Via interviews with survivors and professionals, online measurement studies, and reverse engineering of malicious tools, our research has provided the most granular view to date of technology abuse in IPV contexts. This has helped educate our efforts on intervention design, most notably in the form of what we call clinical computer security: direct, expert assistance to help survivors navigate technology abuse. Our work led to establishing the Clinic to End Tech Abuse, which has so far worked to help hundreds of survivors of IPV in New York City.
Second, I’ll discuss how basic security tools like encrypted messaging need to be adapted in light of tech abuse. Here we find a fundamental tension between the desire for messaging service providers to help moderate malicious content and the confidentiality goals of encryption, which prevent the platform from seeing content. I’ll show how we end up reconceptualizing and redesigning basic cryptographic tools to more securely support abuse mitigation.
The talk will include content on abuse, including discussion of physical, sexual, and emotional violence.

MEAM Seminar: "Advancing Bioadhesive Technologies with Mechanical Principles"
2023-11-28 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Bioadhesive technologies are important in a wide range of applications, spanning from wound management to wearable technologies. Forming and controlling tough adhesion on biological tissues has been a long-lasting challenge, necessitating transdisciplinary approaches. In my talk, I will share our recent progress in the design, mechanics, and applications of tough bioadhesives. I will first discuss the limitations of clinically used surgical glues and blood clots in terms of adhesion properties. I will then present the mechanical principles for making tough bioadhesives that exhibit superior adhesion performance on diverse tissues. Furthermore, I will discuss our transdisciplinary approaches and underlying mechanisms for controlling tough bioadhesion through ultrasound and interfacial entanglements. Lastly, I will showcase the applications of tough bioadhesives in wound management, tissue repair, and hemorrhage control. This talk will highlight the synergy of materials and mechanics in the development of new biomaterials poised to address clinical challenges.
