Penn Engineering Events

Penn Engineering Commencement 2024: Master's Ceremony
2024-05-17 14:00 - 16:30 (America/New_York) | Palestra, 223 South 33rd Street, Philadelphia, PA, 19104, United States
Celebrate the Penn Engineering 2024 Master’s Graduates. Additional information is available on the Penn Engineering Commencement website.

Celebrating Penn Engineers: Past, Present and Future
2024-05-18 09:00 - 10:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Penn Engineering invites all alumni, family and friends to join us for the dedication of two new hallway installations that honor the past while inspiring the future. Join Dean Kumar to reconnect with classmates and hear remarks from notable alumni. Breakfast will be provided at 9:00am, program begins at 9:45 a.m. Click to see the full schedule of events for Penn Alumni Weekend.

Penn Engineering Commencement 2024: Undergraduate Ceremony
2024-05-18 14:00 - 16:00 | Palestra, 223 South 33rd Street, Philadelphia, PA, 19104, United States
Celebrate the Penn Engineering Undergraduate Class of 2024. Additional information is available on the Penn Engineering Commencement website.

Penn Engineering 2024 Commencement Open House
2024-05-20 12:15 - 14:15 | PA
On Monday, May 20, 2024, from 12:15-2:15 p.m., Penn Engineering will host an Open House for the School’s returning graduates and their families throughout the first floors of the main Engineering complex, immediately following the University Ceremony.
Included are photo booth opportunities, a t-shirt giveaway (including a live t-shirt press!), and light refreshments. Please join us!

GRASP Seminar: Yinghao Xu, Stanford University, "Large Reconstruction Model for Efficient 3D Reconstruction and Generation"
2024-05-24 13:00 - 14:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This seminar will be held in-person in Wu and Chen as well as virtually via Zoom.
ABSTRACT
Over the past year, the large language model has achieved significant milestones, approaching human-like intelligence across various domains. However, there has been limited investigation into large-scale 3D reconstruction in the literature. In this talk, I will primarily focus on our recent advancements in large-scale 3D reconstruction.
I will start with an introduction to the basics of the Large-scale Reconstruction Model (LRM), aiming to develop a robust and highly generalizable 3D reconstruction system utilizing high-quality 3D data. I will also explain how LRM can be used to efficiently perform high-quality text-to-3D and image-to-3D generation tasks, such as Instant3D and DMV3D.Finally, I will highlight our recent work, specifically our progress in large-scale 3D reconstruction using Gaussian Splatting (GRM). As a large-scale reconstructor, GRM can reconstruct a 3D asset from sparse-view images in about 0.1 seconds. Moreover, GRM shows promising potential in generative tasks, such as text-to-3D and image-to-3D, through its integration with existing multi-view diffusion models.

BE Doctoral Dissertation: "Biologic Delivery to Preserve Joint Health and Promote Tissue Repair" (Elisabeth Lemmon)
2024-05-28 10:00 - 12:00 | JMB Reunion Auditorium, 3620 Hamilton Walk, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Rob Mauck are pleased to announce the Doctoral Dissertation Defense of Elisabeth Lemmon.

Title: Biologic Delivery to Preserve Joint Health and Promote Tissue Repair
Date: May 28, 2024
Time: 10:00 AM
Location: JMB Class of ’62 Auditorium
Zoom link – https://upenn.zoom.us/j/93923840583?pwd=[REDACTED]

Please email elemmon@vet.upenn.edu for the zoom password.

The public is welcome to attend.

PRIML Seminar: "Matrix Completion and Algebraic Geometry"
2024-05-30 12:30 - 13:30 | Towne 307, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Low-rank matrix completion is a well-studied problem, for which a rich theory exists, mainly from the optimization and statistical points of view. However, the majority of the theoretical analysis in the literature assumes random observation patterns. On the other hand, the pattern of observed entries depends on the nature of each application, and is usually not random. This leads to the following fundamental question: What are the uniquely completable patterns at a certain rank r? This is a natural question of algebraic geometry that we will undertake in this talk (no prior experience with algebraic geometry will be assumed).

PRIML Seminar: "Matrix Completion and Algebraic Geometry" (Manolis Tsakiris)
2024-05-30 12:30 - 14:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States

ESE PhD Thesis Defense: "Integrated Electronic-Photonic Solutions From Quantum Control Systems to Optical Transmitters"
2024-06-03 13:00 - 15:00 | Towne 337
Silicon’s advanced fabrication processes have enabled the miniaturization of complex electronic systems, enhancing performance and efficiency. Recent technological developments have further expanded silicon’s utility to integrate photonic systems, merging electronic and photonic technologies on a single chip. This integration has opened new avenues for high-speed communication and computation, attracting significant interest from both research and industry. In this thesis, integrated electronic-photonic solutions ranging from quantum control systems to optical transmitters are presented. Firstly, an integrated reconfigurable quantum control system is demonstrated. This system is used to determine electron-spin resonance frequency and perform Rabi, Ramsey, and Hahn-echo measurements for an NV center spin qubit in diamond. Secondly, two monolithically integrated single-channel optical PAM-4 transmitters are implemented, studied, and compared. Lastly, monolithically integrated 8- and 32-channel wavelength-division multiplexed optical transmitter systems are presented. These systems operate in the infrared optical C-band using custom-designed two-section PN-capacitive micro-ring modulators. The 8- and 32-channel systems support aggregate data rates up to 256 Gb/s and 1.024 Tb/s, respectively, and are highly integrated with a wavelength stabilization circuit, test data generators, and high-swing electrical drivers on the same CMOS silicon-on-insulator chip.

MEAM Seminar: "Dynamically Tunable Adhesion and Friction via Active Materials with Thermally Modulated Stiffness"
2024-06-04 10:00 - 11:30 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Contact interactions, including adhesion and friction, are critical to the design of many engineered systems. Currently, most systems rely on materials with static mechanical properties, requiring careful selection of materials to realize effective systems for specialized tasks. However, with advances in smart materials, system design is no longer limited to materials with static properties. There is a significant potential to exploit active materials for dynamic control of mechanical behaviors, including adhesion and friction, to enable the design of systems with improved performance and new functionalities. Example applications of such systems are robotic grasping and manipulation. In this work, active control of adhesion and friction is realized using materials with tunable stiffness. In particular, thermally responsive polymers, which exhibit substantial changes in stiffness, provide significant potential for adhesion and friction control. We demonstrate the use of a shape memory polymer with thermally modulated stiffness to dynamically tune adhesion and friction. Through a combination of experimentation and finite element analysis, we present a composite microstructured adhesive with high strength and adhesion switchability, while highlighting the role of scale in achieving fast response times. Through further experimentation, we investigate the ability to tune friction, using stiffness modulation to enable a transition from Coulomb friction to adhesion-dominated friction. This ability to dynamically control adhesion and friction offers new opportunities for the design of engineered systems.

ESE PhD Thesis Defense: "Algorithms for Adversarially Robust Deep Learning"
2024-06-04 13:00 - 15:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Given the widespread use of deep learning models in safety-critical applications, ensuring that the decisions of such models are robust against adversarial exploitation is of fundamental importance. In this thesis, we discuss recent progress toward designing algorithms that exhibit desirable robustness properties. First, we discuss the problem of adversarial examples in computer vision, for which we introduce new technical results, training paradigms, and certification algorithms. Next, we consider the problem of domain generalization, wherein the task is to train neural networks to generalize from a family of training distributions to unseen test distributions. We present new algorithms that achieve state-of-the-art generalization in medical imaging, molecular identification, and image classification. Finally, we study the setting of jailbreaking large language models (LLMs), wherein an adversarial user attempts to design prompts that elicit objectionable content from an LLM. We propose new attacks and defenses, which represent the frontier of progress toward designing robust language-based agents.

GRASP Seminar: Lillian Chin, University of Texas at Austin, "Materials Make the Bot: Directly Embedding Actuation and Perception into Robotic Structures"
2024-06-04 14:00 - 15:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This seminar will be held in-person in Levine 307 as well as virtually via Zoom.
ABSTRACT

To make a future where robots are helpful and commonplace, robots must physically interact with humans and their surroundings. In this talk, I argue that robots should be designed from a materials-centric approach to better facilitate these interactions. If core robotic features like actuation and perception can be directly incorporated into a robot’s materials, we could directly control the robot’s primary interface to the outside world.
Drawing from principles in mathematics and metamaterial design, I use auxetic materials as a case study to show how metamaterials can be explicitly designed as the foundation for a robot’s movement and sensing capabilities. I demonstrate the power of this approach by creating expanding modular robots with strength-to-weight ratios of 76x and developing a novel class of auxetics that make soft robotic grippers that are 20x more efficient than standard pneumatic versions. I also present a method for directly sensorizing metamaterial structures in general by embedding internal fluidic channels within the struts themselves as the structure is being 3D printed. This technique offers proprioceptive feedback with minimal hysteresis, enabling accurate pose reconstruction from these fluidic sensors alone. I close my talk with some preliminary work on adapting this materials-focused approach towards medical applications.

xLab Seminar: "Learning to Control with Vision–Language Models"
2024-06-05 14:00 - 15:30 | Towne 337
If learning from data is valuable, can learning from big data be very valuable? It has been, so far, in vision and language, for which foundation models can be trained on web-scale data to support a plethora of downstream tasks; not so much in control, for which scalable learning remains elusive. Can information encoded in vision and language models guide reinforcement learning of control policies? In this talk, I will discuss several ways for foundation models to help agents to learn to behave. Language models can provide better context for decision-making: we will see how they can succinctly describe the world state to focus the agent on relevant features; and how they can form generalizable skills that identify key subgoals. Vision and vision–language models can help the agent to model the world: we will see how they can block visual distractions to keep state representations task-relevant; and how they can hypothesize about abstract world models that guide exploration and planning.

IDEAS Seminar: "An optimization framework for designing robust state estimators"
2024-06-05 15:30 - 16:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Cyber-physical systems often include communication networks that ensure data transmission between different components of the system (sensors, actuators, processing units, etc). The presence of such networks renders the whole system vulnerable to malicious attacks consisting, for example, in the injection of arbitrary signals. In this context, the data collected over the communication channel may be so unreliable that their use for state estimation or system identification requires design methods which are more robust than conventional ones.
Resilience is a particular robustness property which characterizes the sensitivity of some performance function of interest with respect to a class of disturbances (model uncertainties). For example, we say that a state estimator is resilient to a set of disturbances E if the estimation error induced by that estimator is (a) zero whenever the actual model uncertainty lies in E and (b) continuously dependent on the distance from the actual uncertainty to the set E. In this talk we will discuss a resilience-inducing optimization framework for secure state estimation in the scenario where E is a set of impulsive (or sparse) noise sequences. This type of noise signal can account typically for intermittent sensor failures or adversarial attacks in the context of cyber-physical systems. It can also arise artificially as a methodological device for example, in the identification, estimation and control of switched systems. We consider both batch off-line and online recursive estimation.

BE Doctoral Dissertation Defense: "Goal-Directed Dynamics of Network Topology" (Shubhankar Patankar)
2024-06-07 11:30 - 13:30 | Heilmeier Hall (Room 100), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Dani Smith Bassett are pleased to announce the Doctoral Dissertation Defense of Shubhankar Patankar.

Title: Goal-Directed Dynamics of Network Topology
Date: June 7, 2024
Time: 11:30 am – 1:30 pm
Location: Heilmeier Hall, Room 100 Towne Building
Zoom: https://upenn.zoom.us/j/95495692170

The public is welcome to attend.

infoLeNS Seminar: "Emerging computational imaging inverse problems: from theory to algorithms"
2024-06-07 13:00 | Room 452 C, 3401 Walnut, 3401 Walnut Street, Philadelphia, PA, 19104, United States
In this talk, I will focus on two challenging imaging systems: snapshot compressive imaging and coherent imaging under speckle noise interference. I will begin by reviewing the core mathematical modeling of the inverse problem corresponding to each system. I will develop a maximum likelihood estimator (MLE)-based optimization for each, employing untrained neural networks (NNs) to model the source structure. Theoretical analysis of the MLE-based methods will be shown to enable, on one hand, an understanding of the fundamental limits of these systems and, on the other hand, optimization of the image recovery algorithms and hardware. I will also discuss our proposed algorithms that merge classic bagging ideas with untrained neural networks for solving the inverse problems in these imaging systems. For each application, I will demonstrate how our method achieves state-of-the-art performance.

Community for Rigor Public Talk and Live Podcast Recording: "Rigor in Plain English"
2024-06-12 11:00 - 12:00 | Tedori Family Auditorium, Levin Building, 425 S University Ave, Philadelphia, PA, United States
You’ve probably seen reports about reproducibility issues and science gone wrong due to lack of rigor. But what does it mean to do rigorous scientific research? If the word conjures up images of stiffness, strictness, and difficulty, the Community for Rigor is here to help! Join us for Rigor in Plain English, a live podcast recording event on June 12, at the University of Pennsylvania. This event is free and open to the public. Our speakers will share their views on scientific rigor, explain why it’s crucial to your research and science in general, and share how you can be part of a growing global movement striving for better science!
Community for Rigor is an NIH-funded initiative making educational materials to help scientists learn the principles and practice of research rigor.

GRASP Seminar: Matthias Nießner, Technical University of Munich, “Photo-realistic AI Avatars”
2024-06-12 11:00 - 12:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This seminar will be held in-person in Levine 307 as well as virtually via Zoom.
ABSTRACT
In this keynote, I will talk about our latest research on creating photo-realistic AI Avatars. Here, our main goal is to create virtual characters that can are visually indistinguishable from photos and videos of real people. Further, we aim to control such avatars with multi-modal control signals such as animation rigs, text, or voice in order to replicate real-world conversations and leverage our avatars for 3D content creation. Ultimately, we aim to witness the evolution of photos and videos into interactive, holographic 3D content that is indistinguishable from the physical reality. To this end, we focus on the possibility of capturing and sharing 3D photos with friends, family, or through social media platforms. Imagine the ability to comprehensively document historical events along with the participating people for future generations, or to generate content for upcoming applications in augmented and virtual reality.

GRASP Seminar: Angela Dai, Technical University of Munich, “From Understanding to Interacting with the 3D World”
2024-06-12 13:30 - 14:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This seminar will be held in-person in Levine 307 as well as virtually via Zoom.
ABSTRACT
Understanding the 3D structure of real-world environments is a fundamental challenge in machine perception, critical for applications spanning robotic navigation, content creation, and mixed reality scenarios. In recent years, machine learning has undergone rapid advancements; however, in the 3D domain, such data-driven learning is often very challenging under limited 3D/4D data availability. In this talk, we first explore learning 3D priors from data capture and annotation for supervision, leveraging synthetic data as a strong 3D prior for reconstruction and semantic understanding of 3D scenes observed from commodity RGB and RGB-D sensors. As synthetic priors can be limited in diversity, we then discuss real-world 3D data alternatives, followed by relaxing 3D supervision constraints to weakly supervised formulations for such object-based reconstruction and 3D semantic scene understanding. Finally, as real-world scenes are often dynamic, we characterize 3D interactions and propose to distill knowledge from other data modalities to enable zero-shot 3D interaction synthesis. These 3D learning strategies promise to usher in a new paradigm of generalized 3D perception, beyond the limits of existing 3D datasets, to enable in-the-wild 3D analysis of environments.

MEAM Ph.D. Thesis Defense: "Bistable Structures Enable Passive Transitions in Mobile Robots"
2024-06-17 13:00 - 14:00 | Towne 319, 220 S. 33rd Street, Philadelphia, 19104, United States
Making robots more capable, agile, and efficient requires careful design of the robot’s mechanical body to match task requirements. Passive components allow a robot to perform a task without a dedicated actuator, often improving both power consumption and overall performance. In this thesis, we investigate robotic applications of bistable mechanisms, mechanical structures that exhibit two stable equilibria, to enable passive actuation and locking for systems with discrete task modes.
The main underlying idea of this thesis is that “force reversal” provides a practical means of causing bidirectionally passive snap-through of bistable structures, meaning that in the frame of the bistable mechanism, force must be applied toward each target equilibrium state. Force reversal can be produced through a variety of means that do not necessarily require direction change in the actuators. In particular, the design of the mechanism surrounding the bistable structure serves as transmission to redirect actuation forces. We demonstrate this idea in the context of three unique systems: a gripper that uses contact, a gripper that uses a twisting Kresling origami pattern, and a morphing aerial vehicle that uses inertial forces.
More specifically, the main theoretical contribution of this thesis is a method for determining the actuation force requirements for dynamically-actuated bistable mechanisms, where inertial forces are responsible for producing snap-through. In this case, there is a direct relationship between the inertial forces and the output force of the actuators that produce the associated motions. We find that the minimum actuating force required for snap-through depends on the ratio between the mass on the bistable structure and the robot’s total mass, and that it also depends on friction but not on viscous damping. The main experimental contribution includes demonstrations of the impact of bistable mechanisms on grasping and flying systems. For perching, we show that attaching a linkage to a passive bistable structure augments a gripper’s locking strength, leading to passive grasping with a high strength-to-weight ratio. For aerial reconfiguration, we demonstrate that the energy cost of passive dynamic transformation can be offset by the efficiency gains of transforming from a quadrotor to a fixed wing mode. Overall, this thesis shows that passive bistable mechanisms can eliminate the need for task-specific actuators by repurposing existing locomotion actuators.

MEAM Seminar: "Controlling Contact Transitions for Dynamic Robots"
2024-06-18 10:00 - 11:30 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Legged robots, robotic manipulators, and their combined embodiment as humanoid robots have received considerable attention across both academia and industry. However, with few notable exceptions, state-of-the-art demonstrations are significantly less dynamic than their biological counterparts. A considerable challenge for performing more dynamic tasks for both legged robots and robotics manipulators lies within controlling contact interactions with their environment. Legged robots are sensitive to impacts with the ground when executing dynamic motions because they undergo large changes in their velocities in a short amount of time with uncertainty in both the impact model and timing. Robotics manipulators often focus on quasistatic models or static contacts to avoid the underactuation that comes with sliding. First, we will propose a general framework for reducing sensitivity to uncertainty to the impact event, which we demonstrate on dynamic jumping and running controllers on the 3D bipedal robot, Cassie. Next, we explore a dynamic non-prehensile manipulation task that requires the consideration of the full spectrum of hybrid contact modes. We leverage recent methods in contact-implicit MPC to handle the multi-modal planning aspect of the task. We demonstrate, with careful consideration of integration between the simple model used for MPC and the low-level tracking controller, how contact-implicit MPC can be adapted to dynamic tasks. Finally, I propose small modifications to the MPC framework to add a dual-sided margin to the stick-slip boundary.

ESE PhD Thesis Defense: "Engineering copper-vacancy color centers in zinc sulfide for quantum defect discovery"
2024-06-18 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Photoluminescent point defects, or color centers, in wide-bandgap semiconductors are important platforms for quantum information science because they can be operated as solid-state quantum spin-light interfaces. Implementing so-called defect qubits in an expanded variety of materials systems is beneficial for applications, since the host-defect material properties determine operating parameters such as emission wavelength, spin coherence time, and pathways for device integration. A key challenge is obtaining materials that contain defects of interest, and at sufficiently low concentrations to allow observation of quantum emission. This thesis concerns the creation of copper-vacancy complexes for quantum defect studies in zinc sulfide, a material in which there is no known defect qubit. Zinc sulfide, as the host material, possesses a wide bandgap and a low concentration of nuclear spins, enabling the operation of an electronically isolated spin-light interface with low magnetic background noise. The copper-vacancy center, as the point defect of interest, has been shown to exhibit favorable characteristics including radiative transitions between isolated states inside the zinc sulfide bandgap, a paramagnetic ground state, and a C3V-symmetric impurity-vacancy structure which results in favorable orbital and spin characteristics for several known defect qubits. We use both chemical synthesis and focused ion beam (FIB) implantation to obtain copper-vacancy color centers in zinc sulfide. FIB implantation of copper followed by annealing creates localized arrays of copper-vacancy color centers in single-crystal zinc sulfide. Studies of copper-vacancy center activation in bulk zinc sulfide reveal new evidence regarding the origins of the associated emission, and provide bright ensembles of centers sharing a single crystal lattice for field-dependent measurements. However, the background emission in commercially available zinc sulfide poses a barrier to observing quantum emission from copper-vacancy color centers. This barrier is overcome by the successful activation of copper-vacancy centers in colloidal nanocrystals of zinc sulfide, which we can sufficiently dilute using solution processing methods to the extent that we are able to measure photon antibunching from copper-vacancy centers. We discuss the templated assembly and isolation of colloidal nanocrystals of zinc sulfide containing copper-vacancy color centers, which can withstand liftoff and ligand-exchange procedures without quenching of the copper-vacancy luminescence. We further discuss techniques uniquely developed for the spin-optical characterization of these copper-vacancy centers as potential defect qubits. These include time-gating photoluminescence scans to improve the visibility of copper-vacancy centers based on the long-lived emission components we measure in ensemble studies, and 2D, room-temperature optically-detected magnetic resonance spectroscopy capabilities compatible with time-gating. Prior to the work presented here to gain access to red-emitting copper-vacancy color centers for their attractive properties as a defect qubit candidates, there has not been an intensive effort to create or understand red-emitting copper-vacancy color centers (R-Cu centers) in zinc sulfide since the mid-20th century. As a result, they have never been created using ion beam implantation, and there is only one report of copper-doped zinc sulfide nanocrystals which emit a red peak assigned to these color centers. In providing routes for obtaining arrays of localized emission from copper-vacancy color centers in both bulk and colloidal nanocrystal zinc sulfide, this thesis provides new understanding of the red emission from the copper-vacancy color centers and proposes a solution to inconsistencies in reports of their emission mechanism and peak energy. We find that the R-Cu emission arises from thermally activated carrier transfer between two radiative manifolds, producing an anomalous plateau in the thermal quenching profile and blueshifted luminescence upon increasing temperature. Understanding of these characteristics and their relationship to the charge and spin states of the R-Cu center can inform the development of protocols for operating the center as a quantum spin-light interface. We further demonstrate the powerful advantages of quantum defect exploration using colloidal nanocrystals in place of bulk single-crystals or powders.

MEAM Ph.D. Thesis Defense: "Computational Fluid-Structure Interaction Modeling of the Cardiovascular System"
2024-06-19 10:00 - 11:00 | Towne 319, 220 S. 33rd Street, Philadelphia, 19104, United States
Patient-specific computational modeling and simulation has become a routine part of cardiovascular clinical research. These techniques leverage medical imaging to construct subject-specific models that can be used to study disease processes, design and evaluate medical devices, perform predictive surgery, and aid in clinical decision-making. Modern cardiovascular simulations often require millions of elements and tens of thousands of time steps. Incorporation of additional physics only contributes to these costs and increases model complexity. Due to the presence of complex pulsatile hemodynamics potentially coupled with deformable vessel walls or heart valves, development of accurate, robust, and efficient cardiovascular simulation tools remains a challenging task. In this thesis, I present several improvements to existing finite element solver technologies for computational modeling of the cardiovascular system, all of which were implemented in a new computational FSI framework I developed in the Modular Finite Elements Methods (MFEM) C++ library. First, I describe a block preconditioning technique for implicit time discretization of the Navier-Stokes equations monolithically coupled to reduced dimension models of the cardiovascular system (e.g. Windkessel model). Mass conservation properties of various solution algorithms are investigated in a patient-specific aorta model. Next, I show how these improved techniques can be leveraged to simulate FSI problems, such as blood flow through deformable vessels, using the arbitrary Lagrangian-Eulerian method combined with a quasi-Newton solution procedure. Lastly, I present an immersed approach for computational modeling of fluid-structure interaction. A fully implicit monolithic coupling method is described, as well as several discretization improvements targeted for immersed thin structures. I demonstrate the potential of the method to simulate heart valves dynamics over the cardiac cycle using an idealized problem and two extensions: heterogeneous valves as a simplified model for calcification, as well as an anisotropic Fung type constitutive model for the leaflets.

MEAM Seminar: "Rapidly Understanding Novel Object Dynamics for Robotic Manipulation"
2024-06-25 10:00 - 11:30 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The field of robotic manipulation is attempting to expand from structured warehouse and lab environments to in-the-wild applications in human-centric settings. When deployed in novel settings, a robot may see and need to interact with a new object for the first time. Model-based control approaches rely on a priori dynamics models, an assumption that does not extend beyond highly constrained lab settings. Data-driven control approaches can require immense amounts of data and may only perform well on scenarios in their training data distribution. An alternative that boasts the interpretability of model-based approaches without requiring a model or inordinate amounts of data beforehand is to rapidly build a model of a newly encountered object. In this talk, I will present our work on data efficient dynamics model building through contact-rich interactions. The talk will cover learning dynamics models of single and multi-link objects from state information, theoretical insights into why our loss formulation is more data efficient than naïve alternatives, and how we combine dynamics learning with pose estimation from computer vision.

BE Doctoral Dissertation Defense: "Harnessing the Regenerative Characteristics of Meniscus Superficial Zone Cells" (Sereen Assi)
2024-06-25 11:00 - 12:00 | Berger Auditorium (Room 13), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Yale Cohen are pleased to announce the Doctoral Dissertation Defense of Sereen Assi.

Title: Harnessing the Regenerative Characteristics of Meniscus Superficial Zone Cells
Date: June 25, 2024
Time: 11:00 AM
Location: Berger Auditorium, Skirkanich Hall
Zoom option: https://upenn.zoom.us/j/93851147060?pwd=[REDACTED]

The public is welcome to attend.

BE Doctoral Dissertation Defense: "Lipid Nanoparticles Allow Intracellular Protein Delivery for Modulation of Difficult Therapeutic Targets" (Rebecca Haley)
2024-06-26 11:30 - 13:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Mike Mitchell are pleased to announce the Doctoral Dissertation Defense of Rebecca Haley.

Title: Lipid Nanoparticles allow Intracellular Protein Delivery for Modulation of Difficult Therapeutic Targets
Date: June 26, 2024
Time: 11:30am
Location: Levine Hall, Wu & Chen Auditorium

Zoom option: https://upenn.zoom.us/j/93908532827, Meeting ID: 939 0853 2827

The public is welcome to attend.

ESE Ph.D. Thesis Defense: "Mobile Mission Planning in Uncertain Environments"
2024-06-26 13:00 | Berger Auditorium (Room 13), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
Robotic mission planning in uncertain environments remains a formidable challenge due to environmental complexity and sensor noise. This dissertation introduces new methodologies to tackle these issues. We develop a method for Linear Temporal Logic (LTL) planning, extending it to completely unknown environments to enable dynamic understanding and task fulfillment. Large language models (LLMs) are also leveraged to make task expression more user-friendly and to exploit their reasoning capabilities to improve mission planning while maintaining the guarantees from traditional LTL planning. For multi-robot systems, I focus on enhancing scalability and coordination using Graph Neural Networks (GNNs) for distributed, non-myopic active information gathering. I validate the resulting algorithms with several numerical simulations.

ESE Seminar: "Fluorite and Wurtzite Structure Ferroelectrics. From Fundamentals to Semiconductor Applications"
2024-06-27 13:30 - 15:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Ferroelectric properties were initially discovered in perovskite-structured materials over a century ago. However, it was only in the last two decades that these properties were confirmed in fluorite-structured doped HfO2 and wurtzite-structured AlN films, respectively[1][2]. The ferroelectricity in doped HfO2 or ZrO2 has been attributed to a previously unknown non-centrosymmetric orthorhombic Pca21 phase, while it relates to the hexagonal P63mc phase in wurtzite-structured ferroelectrics. In addition to different dopants in HfO2, it was found that a certain dopant content, oxygen vacancies, surface and bulk effects, and quenching are beneficial for the formation of the polar phase. All effects indicate that strain and stress contribute to the ferroelectric phase formation. Similarly, strain and bond ionicity are discussed for doped AlN, GaN, and ZnO to influence the properties strongly[3,12].
Since ferroelectric properties were first found for nanometer-scale doped HfO2 films, processes had to be optimized to extend the occurrence of the polar phase to the bulk material [4]. For wurtzite-structured layers, properties were found above 100 nm and needed to be scaled down to thinner films. Both material systems are compatible with semiconductor processing, including excellent temperature stability above 200°C. Depending on the doped HfO2 composition, a temperature-induced transition to the tetragonal and monoclinic phase is reported. In contrast, no evidence of ferroelectric to paraelectric phase transition has emerged for AlScN below 600°C [11]. Transmission electron microscopy, electrical characterization, and piezoresponse force microscopy studies reveal domain nucleation limited switching kinetics for fluorite-structured films and a Kolmogorov–Avrami–Ishibashi like switching behavior for wurtzite-structured layers [9][10].
The newly found properties of HfO2, even below 10 nm film thickness, enabled an increasing number of applications such as high aspect ratio ferroelectric capacitors (FeCap) and field effect transistors (FeFET)[5][6]. Other applications, such as ferroelectric tunnel junctions, neuromorphic, piezo-, and pyroelectric devices, are also under discussion [7][8]. Multiple devices could be realized on smaller technology nodes and in larger memory arrays. For wurtzite-structured films, mainly ferroelectric FeCap, FeFET, and piezo applications have been discussed since the properties were found more than ten years later than for the fluorite-structured case [13].
This talk will, therefore, review and discuss fundamental aspects of the recently discovered ferroelectricity in both material structure classes and present the state-of-the-art of their material integration and final properties in working devices.

References
[1] T. Boescke et al., APL 99, 102903 (2011)
[2] S. Fichtner et al., J. Appl. Phys. 125, 114103 (2019)
[3] S. Yasuoka et al., ACS Appl. Electron. Mater. (2022)
[4] X. Xu et al., Nature Materials (2021)
[5] T. Boescke et al., IEEE-IEDM 2011
[6] U. Schroeder et al. Elsevier book 2019
[7] S. Fujii et al., IEEE VLSI (2016) 148
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Summer 2024 GRASP on Robotics: Sami Atiya, ABB Ltd., "The Evolution of Robotics/AI: an Industry Perspective"
2024-06-28 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This seminar will be held in-person in Wu and Chen as well as virtually via Zoom.
ABSTRACT

Since its inception, Robotics has constantly used technological developments to address new customer needs. These developments have occurred in two areas: mechatronics and software & control.
Mechatronic advances made robots stronger, faster, and more accurate. In parallel, software & control has made it easier to program and operate robots, for example e.g., through lead through programming and wizards. The increasing ease of use has addressed a key need for the deployment of robots in industries and businesses whose employees do not have deep technical expertise, enabling them to deploy and interact with robots.
From a market perspective, global robot density comparisons indicate further significant growth potential, particularly across new segments and SME’s and driven by global megatrends, including an aging workforce, the individualized consumer, geopolitical uncertainty, digitalization, and sustainability.
To unlock this potential, robotics needs to continue to progress in mechatronics, and in particular in making robots more intelligent and autonomous through software/Artificial Intelligence.
Artificial Intelligence is already used to provide robots with autonomous skills, like item picking. It will further enable robots to learn and acquire new sensory-motor skills efficiently, leading to higher degrees of perception and dexterous manipulation.
Additionally, prompt-based, natural language technology and autonomous planning and decision making will allow non-expert users to deploy robotics.
Matching customer needs for automation with new technological developments has been a key growth driver for robotics in the past. With the rapid advancement of Artificial Intelligence for robotics, this trend will continue.

MSE Thesis Defense: "Alloy Anodes for Alkali-Metal Batteries: Elucidating Lithiation Pathways of Metal/Metal Composites and Solid Solution Alloys Using Novel Nanoporous Tri-Layer Metal/Metal/Metal Composites"
2024-07-01 11:00 - 13:00 | LRSM Reading Room, 3231 Walnut St., Philadelphia, PA, 19104, United States
The pressing issues of global warming and the rapid depletion of fossil fuel reserves have prompted both private and governmental organizations to seek clean, renewable energy alternatives. Solar and wind energy have been extensively researched, leading to significantly reduced costs for energy production. However, to address the intermittent nature of these energy sources, reliable methods for storing excess energy produced during peak times are necessary for use during off-peak hours, such as nighttime for solar energy. One such method is using batteries – such as Li-ion, Na-ion, and Mg-ion batteries – to store this excess energy. However, current batteries suffer from relatively low energy densities, which make it difficult to store large amounts of energy for a prolonged period of time. One promising solution is to drastically increase the energy densities by replacing current low specific capacity graphite anodes with alloy anode materials, specifically with nanoporous structure. Incorporating nanoporosity into alloy anodes has shown improved performance in terms of cycling stability and rate capability. Further advancements have been achieved by combining materials to exploit their synergistic effects. Typically, though, nanoporous metal fabrication methods require a sacrificial element to be etched from a parent alloy, leading to significant material waste and poor sustainability — often having waste material exceeding 50 at. % of the parent material.
In this work, we introduce a novel technique called “chlorine-neutral etching” for sustainably producing nanoporous metals without sacrificing materials. This technique uses oxidative and reductive pulses to convert bulk silver into nanoporous silver without any sacrificial elements. We extended this method to a gold-silver alloy precursor, successfully separating gold and silver into distinct nanoporous gold and silver layers, creating a tri-layer composite material. Using scanning electron microscopy (SEM) and small-angle X-ray scattering (SAXS), we confirmed the uniform porosity of the entire material. With this innovative nanoporous silver | gold | silver tri-layer composite structure, we explored the electrochemical alloying reaction pathways with lithium (principles which can be extended to storage of other alkali and alkaline-earth metal ions) of both a solid solution alloy and the tri-layer metal/metal composite material. We predicted phase morphology evolution in a material combining gold and silver phases based on the equilibrium phase diagrams of each component. By comparing the voltage profiles of the solid solution alloy and the composite structure, we assessed how each structure’s voltage profile compared to the sum of its individual components. Our conclusions suggest future research directions and present preliminary results for extending the chlorine-neutral etching method to a promising alloy anode, lead metal. We also developed battery cells using bulk lead metal and compared the long-term cycling performance of solid solution alloys against nanoporous metal/metal composite materials.
