Penn Engineering Events

BE Doctoral Dissertation Defense: "High Throughput Microfluidics for Ultrasensitive Blood-Based Diagnostics" (Nishal Shah)
2022-11-18 14:00 - 16:00 (America/New_York) | towne 217
The Department of Bioengineering at the University of Pennsylvania and Dr. David Issadore are pleased to announce the Doctoral Dissertation Defense of Nishal Shah.

Title: High Throughput Microfluidics for Ultrasensitive Blood-Based Diagnostics.
Date: November 18, 2022
Time: 2:00 pm
Location: Towne 217 ALC
or via Zoom, link below

https://upenn.zoom.us/j/93933189939

The public is welcome to attend.

Dissertation Defense: Jingyu Wu
2022-11-21 10:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
LARGE-SCALE MICROFLUIDIC MANUFACTURING OF GRANULAR HYDROGELS AND MULTIPLE EMULSIONS
Abstract:
Droplet microfluidics have made tremendous progress in the last two decades in the generation of micrometer- and nanometer-scale materials. One of the major developments lies in the incorporation of multiple microfluidic devices onto single chips enabling emulsion generation at clinical and industrial-relevant scale. However, most demonstrated successes have focused on producing simple emulsions; production upscaling of complex emulsion and materials have not been realized. In this thesis, I will demonstrate new approaches and some early successes to fill this gap between lab-scale and industrially relevant scale production of complex emulsion and drop-based on-chip material synthesis. First, a silicon-and-glass based microchip is developed for ultrahigh throughput on-chip photopolymerization of microgels. We demonstrate that the mechanical properties of microgels can be modulated by tuning the UV dosage and a massive parallelization of 4080 microfluidic synthesis lines on a 4-inch wafer. Second, a new wettability patterning strategy, along with the fabrication process, is developed to pattern the hydrophobicity of a silicon-based microfluidic chip. We demonstrate wettability patterning with micrometer resolution and generation of both W/O/W and O/W/O double emulsions. Further, the scalability of this approach is demonstrated with chips that incorporate 50 parallelized double-emulsion generating devices, producing double emulsions in a high throughput manner (26.5 kHz double emulsions). Lastly, we extend the above approach and develop a novel approach to perform surface wettability patterning via polymer enrichment and replica molding (SUPER), controlling the wettability of microfluidic channels made of a solvent-resistant PFPE-PEG copolymer network. We demonstrate the utility of this approach by fabricating a PFPE-PEG based microfluidic chip, with hydrophobic/hydrophilic patterned microchannels, to generate double emulsions.

PSOC Seminar: "Mechanical Control of T Cell Function" (Morgan Huse, The Sloan Kettering Institute)
2022-11-21 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Fall 2022 Hybrid-Seminar Series
Mondays 1.00-2.00 pm (EST)
Towne 225 / Raisler Lounge
For Zoom link, please contact <manu@seas.upenn.edu

PSOC Seminar: “Mechanical waves identify the amputation position during wound healing in the amputated zebrafish tailfin” (Keng-hui Lin, Institute of Physics)
2022-11-28 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

MEAM Seminar: "The Challenges and Opportunities of Battery-Powered Flight"
2022-11-29 10:00 - 10:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Sustainable transportation and aviation are critical to address climate change and renewable energy powered battery electric vehicles represent a promising path towards this goal. I will discuss the performance metrics needed of batteries for electric land and air vehicles, and assess the energy-efficiency of electric vertical take-off and landing (eVTOL) aircraft compared to ground vehicles.[1] Identifying the challenging but achievable battery performance requirements for eVTOL, I will discuss our approach to achieve simultaneously high specific energy and power by using lithium metal anodes, enabled through a new density-driven dendrite suppression mechanism realized through a soft polymer-ceramic composite separator[2]. I will discuss the unique performance failure mode related to power fade for eVTOLs rather than energy fade for electric vehicles. Following this, I will discuss the requirements and challenges for all-electric battery-powered single and twin-aisle aircraft and outline battery chemistry innovations that offer a pathway to approaching these requirements.[3] I will discuss two key tools to accelerate the innovation timeline for these battery chemistries: (i) in-situ and operando characterization[4] (ii) closed-loop battery material discovery with physics based simulation and robotic experimentation.[5]
References: [1] Sripad, Viswanathan, Proceedings of the National Academy of Sciences 9, 2021 118 (45) e2111164118 [2] Fu et al., Nature Materials, (2020), 19, 758–766. [3] Viswanathan et al., Nature, 601, 519–525 (2022), [4] Hafiz et al., Nature, 594, 213–216 (2021) [5] Dave et al., arXiv:2111.14786. Nature Communications (under revision)

CIS Grace Hopper Lecture: "Data Privacy is Important, But It's Not Enough"
2022-11-29 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Our current data ecosystem leaves individuals, groups, and society vulnerable to a wide range of harms, ranging from privacy violations to subversion of autonomy to discrimination to erosion of trust in institutions. In this talk, I’ll discuss the Data Co-ops Project, a multi-institution, multi-disciplinary effort I co-lead with Kobbi Nissim. The Project seeks to organize our understanding of these harms and to coordinate a set of technical and legal approaches to addressing them. In particular, I’ll mention recent joint work with Ayelet Gordon and Alex Wood, wherein we argue that legal and technical tools aimed at controlling data and addressing privacy concerns are inherently insufficient for addressing the full range of these harms.

ASSET Seminar: Scallop: A Language for Neuro-Symbolic Programming, Mayur Naik (University of Pennsylvania)
2022-11-30 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
Neurosymbolic learning is an emerging paradigm which, at its core, combines the otherwise complementary worlds of classical algorithms and deep learning; in doing so, it ushers in more accurate, interpretable, and domain-aware solutions for today’s most complex machine learning challenges. I will begin by reviewing the various fundamentals, such as algorithmic supervision, symbolic reasoning, and differentiable programming, which have defined this intersection thus far. I will then present Scallop, a general-purpose programming language that allows for a wide range of modern neurosymbolic learning applications to be written and trained in a data and compute efficient manner. Scallop is able to achieve these goals through three salient overarching design decisions: 1) a flexible symbolic representation that is based on the relational data model; 2) a declarative logic programming language that builds on Datalog; and 3) a framework for automatic and efficient differentiable reasoning that is based on the theory of provenance semirings. I will present case studies demonstrating how Scallop expresses algorithmic reasoning in a diverse and challenging set of AI tasks, provides a succinct interface for machine learning programmers to integrate logical domain-specific knowledge, and outperforms state-of-the-art deep neural network models in terms of accuracy and efficiency.
This is joint work with PhD students Ziyang Li and Jiani Huang.

Fall 2022 GRASP SFI: Nitin Sanket, Worcester Polytechnic Institute, "AI-Powered Robotic Bees: A Journey Into The Mind And Body!"
2022-11-30 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Levine 307 and virtual attendance via Zoom.
ABSTRACT
The human fascination to mimic ultra-efficient living beings like insects and birds has led to the rise of small autonomous robots. Smaller robots are safer, more agile and are task-distributable as swarms. One might wonder, why do we not have small robots deployed in the wild today? Smaller robots are constrained by a severe dearth of computation and sensor quality. To further exacerbate the situation, today’s mainstream approach for autonomy on small robots relies on building a 3D map of the scene that is used to plan paths for executing a control algorithm. Such a methodology has severely bounded the potential of small autonomous robots due to the strict distinction between perception, planning, and control. Instead, we re-imagine each agent by drawing inspiration from insects at the bottom of the size and computation spectrum. Specifically, each of our agents is made up of a series of hierarchical competences built on bio-inspired sensorimotor AI loops by utilizing the action-perception synergy. Here, the agent controls its own movement and physical interaction to make up for what it lacks in computation and sensing. Such an approach imposes additional constraints on the data gathered to solve the problem using Active and Interactive Perception. I will present how the world’s first prototype of a RoboBeeHive was built using this philosophy. Finally, I will conclude with a recent theory called Novel Perception that utilizes the statistics of motion fields to tackle various class of problems from navigation and interaction. This method has the potential to be the go-to mathematical formulation for tackling the class of motion-field-based problems in robotics.

ESE 2022 Jack Keil Wolf Lecture - "Sustaining the Semiconductor Revolution: Challenges and Opportunities"
2022-11-30 15:00 - 16:15 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Advancements in semiconductor integrated circuit (IC) “chip” technology over the past 60+ years have enabled exponential growth in chip functionality with exponential reduction in cost per transistor, resulting in the proliferation of information and communication devices and systems, with revolutionary impact on society; today cloud computing, big data and artificial intelligence are driving the digital transformation of all industries. As fundamental limits approach for transistor miniaturization, alternative, more innovative approaches to improving chip performance will be needed. In this talk I will give some examples of such approaches and discuss opportunities to collaborate in diversifying talent development pathways to meet the growing innovation and workforce development needs of the U.S. semiconductor microelectronics industry, spurred by the CHIPS and Science Act of 2022.

CBE Seminar Series: "Interfacial Transport Processes with Computations at Different Scales" (Dimitrios V. Papavassiliou, The University of Oklahoma)
2022-11-30 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States

MSE Seminar: “Biomineralogical Signatures of Pathlogical Mineralization”
2022-12-01 10:30 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Pathological calcification is a wide-spread phenomenon in the human body, in which calcium minerals form in soft tissues and are found in both healthy and diseased tissues. One example are microcalcifications (MCs), which are primarily biological apatite and occur in cancerous and benign breast pathologies. MCs are key mammographic indicators, however, little is known about their materials properties and associated organic matrix, or their correlation to breast cancer prognosis. Outside the clinic, numerous microcalcification compositional metrics (e.g., carbonate and metal content) are linked to malignancy, yet microcalcification formation is dependent on microenvironmental conditions, which are notoriously heterogeneous in breast cancer. We have interrogated multiscale heterogeneity in calcifications from over 20 breast cancer patients. Employing an omics-inspired approach, for each microcalcification we define a “biomineralogical signature” combining metrics derived from Raman microscopy and energy dispersive spectroscopy. We observe that 1) calcifications cluster into physiologically relevant groups reflecting tissue type and local malignancy; 2) carbonate content exhibits substantial intratumor heterogeneity; 3) trace metals including zinc, iron, and aluminum, are enhanced in malignant-localized calcifications; 4) the lipid-to-protein ratio within calcifications is lower in patients with poorer prognosis, suggesting that expanding diagnostic metrics to include “mineral-entrapped” organic material may hold prognostic promise. This multimodal methodology lays the groundwork for establishing MC heterogeneity in the context of breast cancer biology, and has the potential to be applied to other pathological minerals, as well as in vitro models of mineralization.

Fall 2022 GRASP Seminar: Ankit Shah, Brown University, "Training Robots Like Apprentices"
2022-12-01 14:00 - 15:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This is a HYBRID Event with in-person attendance in Levine 307 and virtual attendance via Zoom.
ABSTRACT
Domains such as high-mix manufacturing, domestic robotics, space exploration, etc., are key areas of interest for robotics. Yet, the difficulty of anticipating the role of robots in these domains is a crucial hurdle for the adoption of robots. Developing robots that can be re-programmed easily during deployment by domain experts without requiring extensive programming knowledge, or in other words robotic apprentices that learn from experts will drive the next wave of robotics adoption.
In this talk, I present a multi-modal Bayesian framework for teaching a robot learner to identify the teacher’s intended task from natural teaching modalities such as demonstrations, and acceptability assessments of the execution. The framework centers on using formal languages such as LTL to model the task specification, and using probabilistic reasoning to reason about the ambiguity in natural teaching modalities. Utilizing the Bayesian framework, we can teach the robot the task specifications from demonstrations, and the robot models its updated belief over specifications as a distribution of logical formulas. We propose Planning with Uncertain Specifications (PUnS), a novel framework to reason about the uncertainty of task specifications while computing the robot policy. We also demonstrate how using formal languages along with active learning can help the robot refine its belief efficiently. Finally we demonstrate how the temporal abstractions afforded by temporal logics in particular can help the robot learn to reuse policies from one task to accomplish other closely related tasks without any additional learning.

BE Seminar: "Cellular and Acellular Strategies for Heart and Lung Repair" (Ke Cheng, UNC/NCSU)
2022-12-01 15:30 - 16:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid seminar: Check email for the zoom link and passcode.
“Cellular and Acellular Strategies for Heart and Lung Repair”
Therapeutic tissue regeneration using stem cells has been hampered by the controversial identity of resident stem cells, low cell retention/engraftment, tumorigenecity and immunogenicity issues. Taking a bioengineering/biomaterials approach, this lecture will introduce the uses of drug delivery and biomaterials strategies to generate more potent cell therapies for heart and lung diseases. In addition, a pharmacoengineering approach is taken to refine cell therapies by developing acelluar therapeutics such as stem cell-derived secretome and exosomes in the setting of heart and lung regeneration. This lecture will also mention a couple of stories in translating bench research into IND-enabled clinical trials on cell-based therapies.

Fall 2022 GRASP on Robotics: Matthew Johnson-Roberson, Carnegie Mellon University, “Lessons from the Field: Deep Learning and Machine Perception for field robots”
2022-12-02 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom.

ABSTRACT
Mobile robots now deliver vast amounts of sensor data from large unstructured environments. In attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine learning techniques to mobile robotic perception. We will discuss solutions to the assessment of risk in self-driving vehicles, thermal cameras for object detection and mapping and finally object detection and grasping and manipulation in underwater contexts. Real field data will guide this process and we will show results on deployed field robotic vehicles.

CEMB Seminar: "Bungee jumping into chromosome instability in human cancer," Yamini Dalal, NCI/NIH
2022-12-02 13:30 - 15:00 | LRSM 112C, 3231 Walnut Street, Philadelphia, PA, 19104, United States
This seminar will be held in person (LRSM 112C) and virtually (https://upenn.zoom.us/j/98620440148).

PICS Seminar: "A Non-local Plasticity Model for Porous Metals with Deformation-induced Anisotropy: Mathematical and Computational Issues"
2022-12-02 14:00 - 15:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
A non-local (gradient) plasticity model for porous metals that accounts for deformation-induced anisotropy is presented. The model is based on the work of Ponte Castañeda and co-workers on porous materials containing randomly distributed ellipsoidal voids. It takes into account the evolution of porosity and the evolution/development of anisotropy due to changes in the shape and the orientation of the voids during plastic deformation. A “material length” λ is introduced and a “non-local” porosity is defined from the solution of a modified Helmholtz equation with appropriate boundary conditions. At a material point located at x , the non-local porosity f (x) , can be identified with the average value of the “local” porosity floc (x) over a sphere of radius 3Rλ centered at x.
The same approach is used to formulate a non-local version of the Gurson isotropic model. The mathematical character of the resulting incremental elastoplastic partial differential equations of the non-local model is analyzed. It is shown that the hardening modulus of the non-local model is always larger than the corresponding hardening modulus of the local model; therefore, the non-local incremental problem retains its elliptic character, and the possibility of discontinuous solutions is eliminated. A rate-dependent version of the non-local model is also developed.
An algorithm for the numerical integration of the non-local constitutive equations is developed, and the numerical implementation of the boundary value problem in a finite element environment is discussed. An analytical method for the required calculation of the eigenvectors of symmetric second-order tensors is presented. The non-local model is implemented in ABAQUS via a material “user subroutine” (UMAT or VUMAT) and the coupled thermo-mechanical solution procedure, in which temperature is identified with the non-local porosity. Several example problems are solved numerically and the effects of the non-local formulation on the solution are discussed. In particular, the problems of plastic flow localization in plane strain tension, the plane strain mode-I blunt crack tip under small-scale-yielding conditions, the cup-and-cone fracture of a round bar, and the Charpy V-notch test specimen are analyzed.

MEAM Seminar: "Nonlinear Mechanical Behavior of Kirigami-inspired Architected Materials"
2022-12-06 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
As 3D printing and other advanced manufacturing techniques have become more common, it is increasingly possible to produce structures with nearly arbitrary internal geometric and compositional features, opening up vast new design space for engineers. In this work, we consider a kirigami-inspired, flexible architected material comprising rotating squares joined at their vertices. The rotational degrees of freedom result in significant structural compliance due to the large internal rotations of the squares. While the static properties of these structures (such as their auxetic characteristics) have been studied extensively, much less work has been done on their dynamic properties, especially nonlinear dynamic properties induced by large movement of internal components. Here, we examine the nonlinear static and dynamic responses of these systems, including the propagation of vector solitons and transition waves, and collisions of these nonlinear waves. Finally, we discuss how stimuli-responsive materials can be integrated with the nonlinearities of kirigami-inspired architected materials to enable autonomous behaviors, including movement and control of trajectory, as well as mechanical computing, which enables “information processing” to be treated as a material property.

Fall 2022 GRASP SFI: Harold Soh, National University of Singapore, "Towards Trustworthy Robots that Interact with People"
2022-12-07 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom.
ABSTRACT
What will it take to develop robots that work with us in real-world tasks? In this talk, we’ll discuss some of our work across the autonomy stack of a robot as we make progress towards an answer. We’ll begin with multi-modal sensing and perception, and then move on to modeling humans with little data. We’ll end with the primary insights gained in our journey and a discussion of challenges in deriving robots that we trust to operate in social environments.

CBE Seminar Series: "Flexible Protein Networks in Membrane Biology and Medicine" (Jeanne Stachowiak)
2022-12-07 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States

MSE Seminar: “Compressibility of Nanoconfined Fluids: Relating Atomistic Modeling to Ultrasonic Experiments”
2022-12-08 10:30 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Fluids confined in nanopores are ubiquitous in nature and technology. In recent years, the interest in confined fluids has grown, driven by research on unconventional hydrocarbon resources — shale gas and shale oil, much of which are confined in nanopores. When fluids are confined in nanopores, many of their properties differ from those of the same fluid in the bulk. These properties include density, freezing point, transport coefficients, thermal expansion coefficient, and, as it was shown recently [1], elastic properties.
The elastic modulus of a fluid confined in the pores contribute to the overall elasticity of the fluid-saturated porous medium and determine the speed at which elastic waves traverse through the medium. In this talk I will show how elastic modulus of a confined fluid in a nanopore can be calculated based on Monte Carlo and molecular dynamics simulations and illustrate it with calculations for various fluids [2]. Additionally, I will present our recent experimental measurements of elastic properties of water confined in nanoporous glass samples. Our results suggest that some of the models widely used for describing elasticity of fluid-saturated porous solids need to be revised [3].
[1] Dobrzanski, C. D.; Gurevich, B.; Gor, G. Y. “Elastic Properties of Confined Fluids from Molecular Modeling to Ultrasonic Experiments on Porous Solids” Appl. Phys. Rev. 2021, 8, 021317, DOI: 10.1063/5.0024114
[2] Maximov, M. A.; Gor, G. Y. “Molecular Simulations Shed Light on Potential Uses of Ultrasound in Nitrogen Adsorption Experiments” Langmuir 2018, 34(51), 15650-15657, DOI: 10.1021/acs.langmuir.8b02909
[3] Gor, G. Y.; Gurevich, B. “Gassmann Theory Applies to Nanoporous Media” Geophys. Res. Lett., 2018, 45(1), 146-155, DOI: 10.1002/2017GL075321

ESE Fall Colloquium - "On compression of, for, and with neural networks"
2022-12-08 12:30 - 13:30 | Zoom – Meeting ID 971 2264 9281
Data compression is enjoying a renaissance fueled by an unprecedented growth in both the amount of data being generated and our reliance on powerful computation. At its heart is an increasingly intricate interplay between compression, artificial neural networks, and (our) biological neural networks. I will survey some related research in which I have been involved, and conclude with thoughts about future research.

MEAM Ph.D. Thesis Defense: "An Aquatic Underactuated Modular Self-Reconfigurable Robotic System for Information-Limited Navigation in Gyre-Like Flows"
2022-12-08 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Aquatic modular self-reconfigurable robotic systems (MSRRs) have incredible potential for bringing practical, flexible, and adaptable robotic tools to challenging environments. They could build mobile ocean platforms or bridges for larger vehicles, act as ocean-going manipulators to perform repairs on infrastructure, or function as oceanographic research platforms, using reconfiguration to achieve precise spatial resolution when sensing or to improve energy efficiency when traveling over large distances.
Development of aquatic MSRRs, however, is limited by the assumption that modules need to be capable of holonomic actuation, which makes them complex and expensive. This work challenges this limitation, presenting a novel underactuated aquatic robot called the Modboat that uses a single motor and passive flippers for propulsion and steering, and developing a capable aquatic MSRR that can dock, undock, reconfigure, and move as a collective using Modboats as its modules.
Aquatic systems are further limited because conventional techniques assume that full flow models are needed to use ocean currents for navigation. Such flow models are rarely available, so practical deployments are limited to high thrust and energy-capacity systems. This dissertation challenges this assumption, demonstrating that limited knowledge of ocean gyres can be used for energy-efficient navigation even by low-thrust systems, and that this navigation can significantly expand the operational range of energy-limited robotic systems. Modboat modules are used to verify these results as an example underactuated and low-power robot.

Grace Hopper Distinguished Lecture: "How Memory Guides Value-Based Decisions" (Daphna Shohamy, Columbia University)
2022-12-08 15:30 - 16:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
This distinguished lecture will be a hybrid event held in the Glandt Forum (Singh Center) and via Zoom. A light reception will follow the live lecture.
Zoom link
Passcode: [REDACTED]
“How Memory Guides Value-Based Decisions”
From robots to humans, the ability to learn from experience turns a rigid response system into a flexible, adaptive one. In the past several decades, major advances have been made in understanding how humans and other animals learn from experience to make decisions. However, most of this progress has focused on rather simple forms of stimulus-response learning, such as automatic responses or habits. In this talk, I will turn to consider how past experience guides more complex decisions, such as those requiring flexible reasoning, inference, and deliberation. Across a range of behavioral contexts, I will demonstrate a critical role for memory in such decisions and will discuss how multiple brain regions interact to support learning, what this means for how memories are used, and the consequences for how decisions are made. Uncovering the pervasive role of memory in decision-making challenges the way we think about what memory is for, suggesting that memory’s primary purpose may be to guide future behavior and that storing a record of the past is just one way to do so.
In support of its educational mission of promoting the role of all engineers in society, the School of Engineering and Applied Science presents the Grace Hopper Lecture Series. This series is intended to serve the dual purpose of recognizing successful women in engineering and of inspiring students to achieve at the highest level. Grace Hopper is a wonderful example of a visionary in her field who exhibited the type of pioneering spirit that is an inspiration to all of us.
In support of the accomplishments of women in engineering, departments within the School invite a prominent speaker to campus for a visit that incorporates a public lecture, various mini-talks and opportunities to interact with students and faculty. This series provides another avenue for recognition of distinguished leaders in engineering and presents role models that help remind all of us why we chose this profession.

CIS Seminar: " Exploring the role of scientific machine learning in electric power system decarbonization"
2022-12-08 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Electric power systems lie at the heart of efforts to mitigate and adapt to the effects of climate change. Mitigation requires shifting electricity generation away from carbon-emitting technologies toward zero carbon sources such as wind and solar generation, and converting energy end uses like transportation and space conditioning to use that electricity. Adaptation requires designing electricity infrastructure to withstand extreme weather conditions, including heat waves, hurricanes, and wildfire. Computing and data sit at the heart of planning for these changes so that they are cost effective and reliable. This talk will survey three challenges in this space, namely, (i) ensuring power system stability in the face of massive changes in generation infrastructure, (ii) exploring the scope of infrastructure change required to reliably serve millions of electrified cars and buildings and (iii) quantifying the risk of wildfire caused by millions of pieces of electricity infrastructure, and the risk reduction achieved by a suite of possible upgrades to that infrastructure. In the course of the survey, the talk will discuss how machine learning tools — including state of the art scientific machine learning principles — can be brought to bear on these problems.

Fall 2022 GRASP on Robotics: David Fouhey, University of Michigan, "Understanding the Physical World from Images"
2022-12-09 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom.

ABSTRACT
If I show you a photo of a place you have never been to, you can easily imagine what you could do in that picture. Your understanding goes from the surfaces you see to the ones you do not, like parts that are hidden behind furniture. Your understanding even enables reasoning about how the scene could be if someone interacted with it, for instance by opening a cabinet. My research aims to give computers this same level of physical understanding. I believe that this physical understanding will be critical for autonomous agents, as well as for enabling new insights in research fields that vision does not often interact with: progress on many problems across the sciences and humanities can be accelerated by being able to robustly measure some quantity at scale.

My talk will show my research group’s work towards the goal of understanding the physical world from images. I will first show how we can reconstruct 3D scenes, including invisible surfaces, from a single RGB image. We have developed an approach that learns to predict a scene-scale implicit function using realistic 3D supervision that can be gathered by consumers or robots instead of by using artist-created watertight 3D assets. After showing reconstructions of our system in everyday scenarios, I will talk about how measuring the world can unlock new insights in science, from millimeter-sized bird bones to solar physics data where a pixel is a few hundred miles wide. I will conclude by showing work towards understanding how humans can interact with objects, including work on understanding hands and the objects they hold.

PICS Colloquium: "From Molecular Vibrations to Solvation, Protein Dynamics and Models of the Cytoplasm"
2022-12-09 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Abstract: Vibrational spectroscopies at mid-infrared frequencies provide excellent probes to characterize functional groups and their immediate chemical environment. However, from a thermodynamic and dynamic point of view, only the ground state of these vibrations is significantly populated. Most of the “jiggling and wiggling” of atoms and molecules (referred to in the famous quote by Feynman) happens at lower frequencies in the far-infrared, where vibrations are easily excited by thermal collisions.
The Heyden research group develops methods to characterize and extract information from far-infrared vibrations in molecular dynamics simulations of biomolecular systems: 1) We develop methods that eliminate the need for harmonic and quasi-harmonic approximations in the analysis of collective vibrational modes and their contributions to vibrational spectra. 2) We use intermolecular vibrations of the water-hydrogen bond network to generate detailed 3D maps of protein hydration free energies and water-mediated interactions. 3) We use such 3D maps to generate implicit solvation models that enable realistic simulations of large biomolecular systems including many interacting proteins.
Each of these methods has its own applications, but combined they allow us to develop computationally efficient models of complex biomolecular environments such as the cytoplasm. We developed a multi-conformation Monte Carlo algorithm that uses input from existing molecular dynamics simulation trajectories to generate new simulation models of systems containing 100’s of interacting flexible proteins at very low computational cost. This allows us to analyze consequences of biomolecular crowding in a multitude of scenarios, which remain inaccessible to direct molecular dynamics simulations.

Fall 2022 MEAM 5200: Block Stacking Challenge!
2022-12-11 12:00 - 16:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom.

ABSTRACT

Teams of 3-4 students will compete head-to-head in a block stacking challenge as their class final project for MEAM 5200: Introduction to Robotics. Each team controls one 7 DOF Franka-Emika Panda manipulator arm using their modeling/planning skills and gaming strategy. The team that stacks the most blocks wins!
Come cheer on your classmates at the MEAM 5200 stacking competition in person or via zoom!
12:00pm-2pm (Qualifiers)

2:30pm-4pm (Knock-outs)

PSOC Seminar: “Validation of a bicistronic CAR to overcome intratumoral heterogeneity in GBM” (Zev Binder, PSOM)
2022-12-12 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

Fall 2022 GRASP Seminar: Nare Karapetyan, University of Maryland, "Area Coverage Path Planning: From Graphs to Field Deployments"
2022-12-14 11:00 - 12:00 | 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 Levine 307 and virtual attendance via Zoom.

ABSTRACT
Area coverage path planning is the problem of finding an efficient path that traverses the region of interest while avoiding existing obstacles. When dealing with real systems, the dynamic changes and uncertainties of the environments increase the state space exponentially and make these problems intractable. As such, exploiting the inherent geometric properties of the areas allows for redefining planning as a combinatorial optimization task. This helps to reduce the overhead complexity of the problem and break it into manageable subproblems for handling uncertainties.
In this talk, we will discuss a two-phase approach for generating a complete pipeline of robust exploration/coverage plans: (i) generate a global coverage plan and (ii) incorporate dynamic changes to adjust the plan. We will specifically discuss different coverage strategies for single and multi-robot systems that take into account obstacles and implicit geological properties of the environment and perform effective data collection suitable to the deployed sensors. We will also discuss how to incorporate uncertainties within these plans. Moreover, we will also see these methods deployed in the real world, automating scientific sampling operations.

ASSET Seminar: ML for Causal Inference, Konrad Kording, University of Pennsylvania
2022-12-14 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT
Machine learning traditionally does not get at causality and causality research traditionally treats machine learning as a dangerous set of highly biased estimators. In my talk I will talk about our lab’s efforts to use machine learning as a component of more traditional quasi-experimental techniques. I will also discuss meta-learning approaches to causal inference, approaches where the estimators themselves are learned. I will lament the relative lack of interactions between the various subfields of the causal inference space.
