Penn Engineering Events

MEAM Ph.D. Thesis Defense: "Metal and Air Generate Power for Robots"
2022-04-12 10:30 - 11:30 (America/New_York) | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
In many cases, the size and weight of energy storage technologies required to power robotic systems are too large or massive for a robot to carry, leading to limited operational times and long recharging times over which the robot remains unused. Computer-free autonomous decision making based on environmental cues provides exciting alternatives to classic control systems for robots and smart materials. Although this functionality has been studied in microswimmers and active colloids where energy in the surrounding liquid is prevalent, there are no devices that can provide sufficient power from environmental chemicals to move and steer larger scale robots and vehicles in dry environments.
In this talk, I will show a new approach for powering robots and electronics by electrochemically scavenging energy from metal surfaces. This approach overcomes energy storage scaling laws by allowing robots and electronics to extract energy from large volumes of energy dense material without having to carry the material on-board. Then, we characterized the evolution of the metal during discharging by using FIB and Micro-CT in our system. Next, we demonstrated an environmentally controlled voltage source that, when directly attached to electric motors on a vehicle, can increase the energy available to the vehicle and provide computer-free autonomous navigation toward chemical fuels in the environment and away from hazards. The voltage source uses electrochemistry to extract power from the chemical fuels, and the vehicle avoids hazards that reduce the output voltage of electrochemical kinetics.
These works present a novel technique to simultaneously steer and power vehicles and robots without computers by directly responding to a wide variety of chemical fields in their environment using electrochemistry.

MEAM Ph.D. Thesis Defense: "Mechanical Properties of Fibrous Network Materials"
2022-04-12 13:00 - 14:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
We discuss mechanical behavior of specific fibrous network materials, including the evolution of tension in fibrin clots, compression of pulmonary emboli, and fracture of Whatman filter paper.
The first material, fibrin clots, consist of random networks of fibrin fibers. When clots form by polymerization they develop tensile pre-stresses. We construct a mathematical model for the evolution of tension in isotropic fibrin gels. As the fiber diameter grows over time, properties which depend on it, such as the stored energy per unit length of a single fiber, the force-stretch relation of a fiber, and therefore the tension in the network as a whole, also evolve over time.
The second fibrous network is pulmonary emboli, which consist of random networks of fibrin fibers with fluid-filled pores and red blood cells (RBCs). Stress-strain responses of human pulmonary emboli under cyclic compression were measured, revealing that emboli exhibit hysteretic stress-strain curves characteristic of foams. We describe the hysteretic response of emboli using a model of phase transitions, in which the compressed embolus is segregated into coexisting rarefied and densified phases whose fractions change as compression progresses. Our model takes into account RBC rupture in compressed emboli and stresses due to fluid flow through their small pores. The mechanical response of emboli is shown to vary depending on their RBC content.
The third fibrous network is Whatman filter paper. The effect of humidity on properties such as out-of-plane fracture toughness of Whatman filter paper is studied for a broad range of relative humidities. Crack growth is modeled using traction-separation laws, whose parameters are fitted to experiments. Additionally, a novel model is developed to capture the high peak and sudden drop in the experimental force measurement caused by the existence of an initiation region, an imperfect zone ahead of a nascent crack. The relative effect of each independent parameter is explored to better understand the humidity dependence of the traction-separation parameters.
The materials studied have biological, clinical, and industrial applications, and the methods described here are also applicable to other fibrous network materials.

Cell Mechanics Discussion Group
2022-04-13 12:00 - 13:00 | https://upenn.zoom.us/j/96715197752

Spring 2022 GRASP SFI: Georgios Georgakis, University of Pennsylvania, “Cross-modal Map Learning for Vision and Language Navigation”
2022-04-13 15:00 - 16:00 | Levine 512
*This will be a HYBRID Event with in-person attendance in Levine 512 and Virtual attendance via Zoom
We consider the problem of Vision-and-Language Navigation (VLN) in previously unseen realistic indoor environments. Arguably, the biggest challenge in VLN is grounding the natural language to the visual input. The majority of current methods for VLN are trained end-to-end using either unstructured memory such as LSTM, or using cross-modal attention over the egocentric RGB-D observations of the agent. We are motivated by studies on navigation of biological systems that suggest humans build cognitive maps during such tasks. In contrast to other works, we argue that an egocentric map offers a more natural representation for this task. In this talk, we will explore a novel navigation system for the VLN task in continuous environments that learns a language-informed representation for both map and trajectory prediction. This approach semantically grounds the language through an egocentric map prediction task that learns to hallucinate information outside the field-of-view of the agent. This is followed by spatial grounding of the instruction by path prediction on the egocentric map. We experimentally test the basic hypothesis that language-driven navigation can be solved given a map, and then show competitive results on the full VLN-CE benchmark.

CBE Seminar: John A. Quinn Distinguished Lecture - "Molecular and Colloidal Interactions in Water”
2022-04-13 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract
Life occurs in water, and water-mediated interactions are central to biomolecular assembly processes. Synthetic materials as common as soap and shampoo also rely on water-mediated interactions. This presentation will describe experiments that highlight our lack of understanding of interactions in water. The opportunity to formulate a refined set of design rules for self-assembly of functional materials in water will be discussed.

MSE Seminar: "Role of Solvation and Dynamics on Ion Transport in Polymer Electrolytes"
2022-04-14 10:30 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Polymer electrolytes are an important class of ion conducting materials critical to enabling various electrochemical systems. Fundamentally, ion-polymer coordination, inter-connectivity of solvation sites, and corresponding ion-solvating polymer dynamics are critical in understanding the limits of ionic conductivity. Here, the importance of these effects is highlighted in a series of combined experimental and computational studies on model lithium-ion conducting polymer electrolytes. First, we focus on graft polymer architectures of poly[(oligo ethylene oxide) methyl ether methacrylate] (POEM) varying oligo side-chain lengths. With addition of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI), the observed differences in ionic conductivity between the POEM derivatives and linear poly(ethylene oxide) (PEO) cannot be adequately explained by differences in Tg. Instead, graft architecture of POEM leads to nonuniform, position-dependent relaxation and ion solvation behaviors along the side chain. Importantly, the limits of ionic conductivity are dictated by the segmental mobility of the ethylene oxide units that form effective solvation sites, rather than system-wide dynamics. Lastly, the talk will end with results from ongoing work focusing on solvation site formation and ion transport mechanisms in mixed polarity copolymers based on POEM and poly(glycerol carbonate methacrylate) (PGCMA).

GRASP Special Seminar: Steven Ceron, Cornell University, “Swarms Across Length Scales with Local-to-Global Behaviors”
2022-04-14 10:30 - 11:30 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
*This will be a HYBRID Event with in-person attendance in Towne 337 and Virtual attendance via Zoom
Collectives in nature demonstrate behaviors that extend far beyond the capabilities of any single agent. Social slime mold, for example, has thousands of cells that aggregate and form mobile and immobile nutrient-searching structures as a function of chemical signals. This species embodies many features that swarm roboticists wish to incorporate in scalable, self-reconfigurable robot collectives: local-to-global behaviors, low-level communication, plasticity, and simple constituents. I argue that regardless of the length scale, we can implement some of the same principles and features to exploit robot morphology, physical interactions among agents, and low-level coordination mechanisms to enable diverse collective behaviors for useful functions in many fields. I present novel emergent collective behaviors at the macro-scale and micron scale and explain how each behavior arises as a function of agents interacting with other agents, agents reacting to their environment, and agents exploiting their environment to affect other agents. Specifically, I show cell-inspired, macro-scale soft robot collectives for distributed systems with coupled sensing and actuation, magnetic microrobot collectives with reconfigurable behaviors and functions for biomedical applications, and cross-scale coordination mechanisms through virtual swarming coupled oscillators for macro- and micro-scale collective control applications.

MEAM Seminar: "Exploiting Environmental Fields for Orienteering and Planning Problems"
2022-04-14 13:30 - 14:30 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Robots are increasingly being used to complete tasks in complex environments. To complete these tasks, two of the most fundamental choices that the robot must make are (1) task planning: which tasks to complete and in what order, and (2) path planning: what path to take when navigating between those tasks. In this seminar, I will consider robots operating in environments where the vehicle dynamics are impacted by the dynamics of the environment (environments with flows) while they complete these tasks. I begin by exploring several limitations of existing strategies that tackle task and path planning in environments with flows as separate problems. First, I examine a problem that focuses on the high level problem of task planning, but abstracts away the environment and assumes that the low-level path planning work is solved independently. This helps simplify the problem, but neglects to include environmental information in the problem. In order to address this limitation, I consider a path planning algorithm in an environment where the flow field can be designed. In particular, I consider a scenario where a magnetic force field is used to manipulate the flow field. In this case, I show how a topological approach can be used to take advantage of the structures in the field. Finally, I examine a scenario where the flow field is determined by ocean currents and therefore cannot be controlled. I will present an integrated solution approach to task and path planning that unifies the two problems in the presence of ocean currents.

GRASP on Robotics: Vincent Sitzmann, Massachusetts Institute of Technology, “Self-supervised Scene Representation Learning for Robotics”
2022-04-15 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Given only a single picture, people are capable of inferring a mental representation that encodes rich information about the underlying 3D scene. We acquire this skill not through massive labeled datasets of 3D scenes, but through self-supervised observation and interaction. Building machines that can infer similarly rich neural scene representations is critical if they are to one day parallel people’s ability to understand, navigate, and interact with their surroundings. In this talk, I will demonstrate how we can equip neural networks with inductive biases that enable them to learn 3D geometry, appearance, and even semantic information, self-supervised only from posed images. I will show how this approach unlocks the learning of priors, enabling 3D reconstruction from only a single posed 2D image. I will then talk about a recent application of self-supervised scene representation learning in robotic manipulation, where it enables us to learn to manipulate classes of objects in unseen poses from only a handful of human demonstrations, as well as the application of neural rendering to learn latent spaces amenable to control. I will then discuss recent work on learning the neural rendering operator to make rendering and training fast, and how this speed-up enables us to learn object-centric neural scene representations, learning to decompose 3D scenes into objects, given only images. Finally, I will discuss how neural scene representations may offer a new angle to tackle challenges in robotics.

BE Doctoral Dissertation Defense: "Leveraging Macrophage Immune Checkpoint Blockade to Link Innate and Adaptive Immunity Against Solid Tumors" (Jason Andrechak)
2022-04-15 11:00 - 13:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Dennis Discher are pleased to announce the Doctoral Dissertation Defense of Jason Andrechak.

Title: Leveraging Macrophage Immune Checkpoint Blockade to Link Innate and Adaptive Immunity Against Solid Tumors

Date/time: Friday, 4/15 at 11am
Location: Glandt Forum
Singh Center for Nanotechnology
3205 Walnut St, Philadelphia, PA 19104

It will be hybrid:
Zoom link: https://upenn.zoom.us/j/96831196783?pwd=[REDACTED]

Password: [REDACTED]

The public is welcome to attend.

PICS Colloquium: "Transforming Healthcare from the Outside: the OBSERVER project"
2022-04-15 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
We live with a health care system that has evolved into an increasingly fragmented, primarily treatment-oriented, and now heavily burdened environment. More importantly, issues related to privacy, space, and disease transmissibility have limited access to non-medical personnel who might offer creative, evidence-based, radical change to the health care system, as proposed years ago by the National Research Council. One way to reimagine that access is through the use of multimodal digital data that summarize patient encounters and make them amenable to outside observers. This talk with summarize the rationale for this project and offer a framework for thinking through how the OBSERVER project could be realized.

PSOC@Penn Seminar
2022-04-18 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Physical Sciences in Oncology Center PSOC@Penn
Spring 2022 Hybrid-Seminar Series
Towne 225 / Raisler Lounge @ Noon (EST)
For Zoom link , please contact manu@seas.upenn.edu

Tedori-Callinan Distinguished Lecture: "Multiscale Hierarchical Modeling and Thermal Management of Electrification Technologies"
2022-04-19 10:00 - 11:30 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Core electrification technologies require developments in battery packs, chargers, electric motors, and thermal management strategies to improve their performance, longevity, reliability and safety. The next battery technology leap relies on novel thermal management strategies and packaging architectures, realized as intelligent battery thermal management systems (BTMS), which can optimally control the thermo-electrochemical phenomena occurring inside the batteries to maximize performance, minimize degradation, enable fast-charging protocols, and accelerate a seamless transition of degraded electric vehicle (EV) batteries into less-demanding second-life stationary systems. This Lecture will present current engineering challenges and opportunities on EV thermal management, with a focus on our research on multiscale hierarchical design, modelling, and optimization approaches to overcome cooling and heating challenges across multiple physical domains and length scales, from battery electrodes, to battery cells, battery packs, to EV thermal management systems.

SEAS Green Team Book Swap & E-Waste Collection
2022-04-19 10:00 - 14:00 | Lobby and Mezzanine, Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States

ESE Ph.D. Thesis Defense: "Extracting Generalizable Hierarchical Patterns of Functional Connectivity in the Brain"
2022-04-19 15:00 - 17:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The study of the functional organization of the human brain using resting-state functional MRI (rsfMRI) has been of significant interest in cognitive neuroscience for over two decades. The functional organization is characterized by patterns that are believed to be hierarchical in nature. From a clinical context, studying these patterns has become important for understanding various disorders such as Major Depressive Disorder, Autism, Schizophrenia, etc. However, extraction of these interpretable patterns might face challenges in multi-site rsfMRI studies due to variability introduced due to confounding variability introduced by different sites and scanners. This can reduce the predictive power and reproducibility of the patterns, affecting the confidence in using these patterns as biomarkers for assessing and predicting disease. In this thesis, we focus on the problem of robustly extracting hierarchical patterns that can be used as biomarkers for diseases.
We propose a matrix factorization based method to extract interpretable hierarchical decomposition of the rsfRMI data. We couple the method with adversarial learning to improve inter-site robustness in multi-site studies, removing non-biological variability that can result in less interpretable and discriminative biomarkers. Finally, a generative-discriminative model is built on top of the proposed framework to extract robust patterns/biomarkers characterizing Major Depressive Disorder.
Results on large multi-site rsfMRI studies show the effectiveness of our method in uncovering reproducible connectivity patterns across individuals with high predictive power while maintaining clinical interpretability. Our framework robustly identiﬁes brain patterns characterizing MDD and provides an understanding of the manifestation of the disorder from a functional networks perspective which can be crucial for effective diagnosis, treatment and prevention. The results demonstrate the method’s utility and facilitate a broader understanding of the human brain from a functional perspective.

CEMB Future Leaders: "Plant homologs of PIEZO mechanosensitive ion channels localize to the tonoplast and affect vacuolar morphology"
2022-04-20 11:00 - 12:00 | https://upenn.zoom.us/j/96715197752
Launched in May 2021, the Future Leaders in Mechanobiology is a monthly seminar series featuring up-and-coming leaders in mechanobiology–PhD students and postdocs from a wide range of fields, backgrounds, and institutions. By providing an international stage to share one’s work and opportunities to interact with researchers at all career stages, we aim to create an inclusive and valuable series for early-stage researchers and the mechanobiology community as a whole.
Register HERE for access to the Zoom link and visit the CEMB website for more information.

Cobb's Creek Tour
2022-04-20 13:00 - 14:00 | 700 Cobbs Creek Parkway, Philadelphia, PA 19134, 700 Cobbs Creek Parkway, Philadelphia, PA, 19134, United States
Please use the link below to find more information and sign up for the tour!
https://docs.google.com/forms/d/e/1FAIpQLSc-OxodC7fsVFL7AMX_gK4gblHO8zPw5IaZRE-15wUXTUnVRg/viewform

BE Doctoral Dissertation Defense: "Biglycan regulation of regional tendon development via the pericellular matrix" (Ryan Leiphart)
2022-04-20 13:00 - 15:00 | JMB Reunion Auditorium, 3620 Hamilton Walk, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Louis Soslowsky are pleased to announce the Doctoral Dissertation Defense of Ryan Leiphart

Title: Biglycan regulation of regional tendon development via the pericellular matrix

Date: Wednesday, April 20th
Time: 1PM
Location: JMB Reunion Auditorium
John Morgan Building
3620 Hamilton Walk
Philadelphia, PA 19104

Zoom Link: https://upenn.zoom.us/j/94685018569?pwd=[REDACTED]
Password: [REDACTED]

The public is welcome to attend.

Spring 2022 GRASP SFI: Stefanie Tellex, Brown University, “Towards Complex Language in Partially Observed Environments”
2022-04-20 15:00 - 16:00 | Levine 512
*This will be a HYBRID Event with in-person attendance in Levine 512 and Virtual attendance via Zoom
Robots can act as a force multiplier for people, whether a robot assisting an astronaut with a repair on the International Space station, a UAV taking flight over our cities, or an autonomous vehicle driving through our streets. Existing approaches use action-based representations that do not capture the goal-based meaning of a language expression and do not generalize to partially observed environments. The aim of my research program is to create autonomous robots that can understand complex goal-based commands and execute those commands in partially observed, dynamic environments. I will describe demonstrations of object-search in a POMDP setting with information about object locations provided by language, and mapping between English and Linear Temporal Logic, enabling a robot to understand complex natural language commands in city-scale environments. These advances represent steps towards robots that interpret complex natural language commands in partially observed environments using a decision theoretic framework.

CBE Seminar: "Design of Advanced Functional Surfaces Using Oxygen-Tolerant Photopolymerization”
2022-04-20 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract
The covalent attachment of polymers has emerged as a powerful strategy for the preparation of multi-functional surfaces. Patterned, surface-grafted polymer brushes provide spatial control over a variety of physical properties and allow for fabrication of ‘intelligent’ substrates which selectively adapt to their environment. This presentation describes recent advances in our group in using photolithography to produce topographically and chemically-patterned polymer brush surfaces via surface-initiated (SI) photoinduced electron/energy transfer (PET) reversible addition–fragmentation chain transfer (RAFT) polymerization. Using this oxygen tolerant approach, organic light emitting diodes (OLEDs), anti-microbial surfaces, and anti-fogging coatings are engineered to highlight facile pathways towards advanced functional surfaces. Oxygen tolerance, mild reaction conditions, and the use of visible light make this approach user-friendly in its application for the design of patterned and functional organic thin films.

MSE Seminar: "Multiphoton Microscopy for Imaging Deeper, Wider, and Faster"
2022-04-21 10:30 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Multiphoton microscopy has changed how we visualize neurons by providing high-resolution, non-invasive imaging capability deep within intact brain tissue. Multiphoton imaging will likely play a major role in understanding how the brain works at the level of neural circuits. In this talk, in vivo structural and functional imaging of mouse brain using long wavelength excitation and three-photon microscopy will be presented. By quantitative comparison to two-photon microscopy, the application space where 3-photon microscopy outperforms conventional 2-photon microscopy will be defined. In addition, a number of interesting directions, including new laser sources, new spectral windows, optimum illumination schemes, etc., will be presented, and their impact on further improving the imaging depth, volume, or speed in biological tissues will be discussed.

MEAM Ph.D. Thesis Defense: "Some Investigations of Phase Transitions in Rod-like Macro-molecules and Fibrous Gels"
2022-04-21 13:00 - 14:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Two problems pertaining to solid-solid phase transitions are presented here.
First, we conduct Langevin dynamics calculations on a chain of masses and bistable springs in a viscous fluid, and extract a temperature dependent kinetic relation by observing that the dissipation at a phase boundary can be estimated by performing an energy balance. Using this kinetic relation we solve boundary value problems for a bistable bar immersed in a constant temperature bath and show that the resultant force-extension relation matches very well with the Langevin dynamics results. We estimate the force fluctuations at the pulled end of the bar due to thermal kicks from the bath by using a partition function. We also show rate dependence of hysteresis in cyclic loading of the bar arising from the stick-slip kinetics. we also extract equilibrium and non-equilibrium information from an over-damped Langevin system using fluctuation theorems.
Second, we use a double-well stored energy function in a chemo-elastic model of gels to capture the existence of two phases of the network. We model cyclic compression/decompression experiments on fibrous gels and show that they exhibit propagating interfaces and hysteretic stress-strain curves that have been observed in experiments. We can capture features in the rate-dependent response of these fibrous gels without recourse to finite element calculations. We also use the model to study the rheological behavior of fibrous gels. We obtain the storage and loss modulus of fibrous gels by performing small amplitude oscillatory compression around various levels of deformation.

BE Doctoral Dissertation Defense: "Engineering injectable, radiopaque hydrogels for X-ray imaging and therapeutic delivery for cancer treatments" (Clara Dong)
2022-04-21 13:00 - 15:00 | https://upenn.zoom.us/j/96715197752
The Department of Bioengineering at the University of Pennsylvania and Dr. David Cormode are pleased to announce the Doctoral Dissertation Defense of Clara Dong.

Title: Engineering injectable, radiopaque hydrogels for X-ray imaging and therapeutic delivery for cancer treatments
Date: 4/21 1pm
Location: Zoom
https://upenn.zoom.us/j/91096994943?pwd=[REDACTED]

The public is welcome to attend.

GRASP on Robotics: Katherine Kuchenbecker, Max Planck Institute for Intelligent Systems, “Haptics and Physical Human-Robot Interaction”
2022-04-22 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
A haptic interface is a mechatronic system that modulates the physical interaction between a human and their tangible surroundings. Such systems typically take the form of grounded kinesthetic devices, ungrounded wearable devices, or surface devices, and they enable the user to act on and feel a remote or virtual environment. I will elucidate key approaches to creating effective haptic interfaces by showcasing several systems my team created and evaluated over the years. I will go into more detail about Haptipedia, our online database of grounded force-feedback devices, and Haptify, the system we recently created to quantitatively benchmark the performance of such interfaces. The talk will then transition to physical human-robot interaction (pHRI), where the engineered system acts as a social agent rather than a tool. In addition to inventing tactile sensors, we have created a robot that plays exercise games with its human partner and have developed methods for learning dynamic physical interactions from demonstrations, both with applications to rehabilitation. Finally, I will present HuggieBot, a custom robot that uses visual and haptic sensing to give good interactive hugs. The presented research stems from collaborations with Hasti Seifi, Karon MacLean, Farimah Fazlollahi, Naomi Fitter, Mayumi Mohan, Michelle Johnson, Siyao “Nick” Hu, Alexis Block, and many others from Penn, MPI-IS, and elsewhere.

Bioengineering Graduate Research Symposium
2022-04-22 12:45 - 18:00 | Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
2022 Bioengineering Grad Symposium
April 22, 2022
Singh Center for Nanotechnology

Register to Attend
Deadline: April 15, 2022
We are excited to announce that the 2022 Bioengineering Graduate Symposium has been rescheduled and will be held in person on April 22, 2022, 12:45 pm – 6 pm at Singh Center. Food, drinks, and free swag will be available throughout the session (subject to the University events policies). Please save the date and RSVP here!

Register for Poster

Good News! We are having limited spots for poster presenters. If you are interested in presenting a poster please do respond here today! The slots will be covered first-come, first-served.

Should you have any questions and concerns, please contact GABE Symposium Co-Chairs Ludwig Zhao <ludwigz@seas.upenn.edu> and Vasiliki Tassopoulou <vtass@seas.upenn.edu>.

Earth Week Cleanup
2022-04-23 | PA
Please use the below link to find more information and signup!
https://docs.google.com/forms/d/1ntEeVQmO4mBXk7PGNi5GaXLRnrdaQ30fmhoflKIvMpQ/viewform?edit_requested=true

BE Doctoral Dissertation Defense: "Remote Field Guided Assembly of Complex Orthopaedic Tissues" (Hannah Zlotnick)
2022-04-25 11:00 - 13:00 | Class of 62 Auditorium, John Morgan Building, 3620 Hamilton Walk, Philadelphia, PA, 19104
The Department of Bioengineering at the University of Pennsylvania and Dr. Robert Mauck are pleased to announce the Doctoral Dissertation Defense of Hannah Zlotnick.

Title: Remote field guided assembly of complex orthopaedic tissues

Date: Monday April 25th
Time: 11 am

Location: JMB Class of ’62 Auditorium
John Morgan Building
3620 Hamilton Walk
Philadelphia, PA 19104

The public is welcome to attend.

PSOC@Penn Seminar: " "Bottom-up synthetic embryology for understanding early human development" (Jianping Fu, PhD)
2022-04-25 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

BE Doctoral Dissertation Defense: "Human tissue-engineered nigrostriatal pathway encased in hyaluronic acid for axon tract reconstruction in Parkinson’s disease" (Wisberty Gordián Vélez)
2022-04-25 14:00 - 16:00 | JMB Reunion Auditorium, 3620 Hamilton Walk, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. D. Kacy Cullen are pleased to announce the Doctoral Dissertation Defense of Wisberty Gordián Vélez.

Title: Human tissue-engineered nigrostriatal pathway encased in hyaluronic acid for axon tract reconstruction in Parkinson’s disease

Date: Monday, April 25th
Time: 2:00 pm
Location: JMB Reunion Auditorium
John Morgan Building
3620 Hamilton Walk
Philadelphia, PA 19104

The public is invited to attend in person or virtually at the link below:
Zoom Link: https://upenn.zoom.us/j/3047758004?pwd=[REDACTED]

Meeting ID: 304 775 8004
Passcode: [REDACTED]

MEAM Seminar: "Towards Personalized Predictive Human Models"
2022-04-26 10:00 - 23:30 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Numerical simulation of physical phenomena is a powerful tool embraced by scientists and engineers for decades. Using simulation tools to predict human movements is particularly critical for training AI-enabled robots interacting with humans, providing testbeds for wearable device design, and generating a wealth of labeled, high-fidelity human motion data. However, existing physics simulators and motor control algorithms for modeling human movements were developed with a fictitious “average human” in mind, while in reality we are often more interested in predicting the motion of a particular real person. Pursuing the quest towards building personalized predictive human models, we develop a learnable and differentiable physics simulator to harness the power of data, and a data acquisition pipeline to provide large-scale biomechanical motion data for the learnable simulator to consume. These computational tools can potentially simulate a wide range of scenarios, but also provide the option to be personalized to specific individuals using only a moderate amount of data. While we focus on the application domains related to human movements, these tools are general and applicable to other robotic research problems on optimal control and parameter estimation. In this talk, I will describe our overall vision on perusing personalized predictive human models, as well as a collection of projects that advanced the state of the art toward this vision.
