ESE PhD Thesis Defense: "Nano-Optical and Electrical Imaging of Excitonic Semiconductor Interfaces"
2023-03-23 12:00 - 14:00 (America/New_York) | Room 313, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
As nanotechnology plays essential parts in developing of high performance or new concepts of electrical and optical devices, new class of nanomaterials has emerged to beat conventional optical and electronic devices. Mixed-dimensional hetero-interfaces consisting of low-dimensional material components, have been the focus of ongoing research efforts to surpass Si-based device and to explore excitonic nano-optical phenomenon. The physical and electronic properties of these interfaces such as transitions in density of states, intimacy of contact and localized strain, govern the charge/energy transfer between neighboring nanomaterials, granting them entirely new optoelectronic functions. However, a limited understanding of the fundamental physical properties of these interfaces exists due to their deep-subwavelength nature challenged by diffraction-limit. Deep-subwavelength imaging therefore takes important role as it enables collection of nano-optical and electrical signals within a tens of nanometer range.
In this dissertation, I present multiple nanoscale interfaces where scanning probe techniques effectively and directly probe the mixed-dimensional interfaces with deep-subwavelength resolution. First, I optically investigate various nanoscale defects in as-grown MoSe2 using chemical vapor deposition, contributing to the rational synthesis of nanomaterials by providing direct evidence of defect distribution. Second, I introduce a universal strategy for characterizing buried semiconductor-metal contact interfaces involving 2D semiconductors and 3D metals and discuss critical factors that impact their optical and electrical properties. Third, I exhibit localized emissions at the 2D semiconductor -metal interfaces and reveal how charge transfer significantly influences the localized states. Finally, I provide experimental and computational evidence that strong light-matter interactions of quantum dot can be visualized using tip-enhanced nano-optical spectroscopy. The approaches presented in this dissertation offer valuable insights for studying various excitonic nanomaterial systems advancing the fields of nano-optical imaging as well as electronics based on these low-dimensional semiconductors.

ESE Spring Seminar - "Risk-Aware Control and Planning in Unstructured Environments"
2023-03-23 12:30 - 13:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Providing safety and performance guarantees for motion planning and control algorithms is a well-studied problem for robotic systems with well-known dynamics that operate in structured environments. However, when robots operate in a real-world setting where the environment is dynamic and unstructured, common assumptions used to develop the planning algorithms are no longer valid and consequently, the safety guarantees no longer hold. In this talk, I will describe my work on developing new theoretical tools for risk-aware, stochastic motion planning to account for diverse and varying uncertainty descriptions while retaining the tractability of the state-of-the-art approaches. The theory has practical and scalable implementation and has been deployed not just in controlled laboratory settings but also in complex, real-world environments.
I will provide techniques to account for uncertainty in static, extreme terrain and in dynamic environments. I will introduce a theoretical framework for motion planning while accounting for risk in a model predictive control setting. The risk-aware control policies are distributionally-robust to the uncertainty in the environment and have probabilistic guarantees for task completion and recursive feasibility. These techniques will be described in the context of my work deployed on ground robots for search and rescue operations in the DARPA Subterranean Challenge and for aerial vehicles in dynamic environments. The goal of my research is to develop verifiable algorithms for safety-critical autonomous systems that are able to perceive their dynamic and uncertain environments to enable safe and intelligent decision-making in hazardous or sensitive environments.

Spring 2023 GRASP on Robotics: John Suh, Hyundai New Horizons Studio, "Ultimate mobility vehicles or what happens when you combine robotics and car design"
2023-03-24 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. This week’s presenter will be in-person as well.

ABSTRACT
New Horizons Studio is a team that is focused on the design, technology, and engineering of ultimate mobility vehicles. NHS believes that the combination of robotics and car design will result in vehicles the overcome the limitations of cars with conventional suspension systems. A brief history covering the beginnings of the idea and the current state of development will be presented. In addition to the core technical challenges, how such a vehicle could be used will also be discussed.

CEMB IRT meeting: Andras Kapus (Toronto)
2023-03-24 13:30 - 15:00 | LRSM 112C, 3231 Walnut Street, Philadelphia, PA, 19104, United States

PSOC Seminar: “The application of cell free DNA in pediatric acute lymphoblastic leukemia and single cell technology in preimplantation genetic testing” (Yuntao Xia)
2023-03-27 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Spring 2023 Hybrid-Seminar Series
Mondays 1.00-2.00 pm (EST)
Towne 225 / Raisler Lounge
“For Zoom link, please contact <manu@seas.upenn.edu>”

MEAM Seminar: "Multiscale Mechano-Medicine: from Mechanobiology to Tissue-Interfacing Stimulating Medical Devices"
2023-03-28 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Many human health problems are associated with alteration of tissue mechanics and often require mechanical stimulation to promote the healing process. While it is now well established that the mechanics of the cellular microenvironment regulate various biological processes, most studies have focused only on the effect of stiffness, leaving other mechanical parameters such as viscoelasticity unexplored. In addition, a large gap still remains between fundamental mechanobiological research and translational medicine. My talk will focus on how we can leverage mechanobiology for translational medicine from the cellular level to the tissue/animal level.
First, I will present the broad impacts of matrix viscoelasticity on biological processes in the context of tumor growth. These findings reveal unexplored molecular pathways involved in tumor growth and substantial force generation during cell division, suggesting novel molecular targets for cancer treatment. Then, I will talk about the use of mechanical stimulation as a means of therapeutic intervention, named mechanotherapy. To this end, we developed several designs of robotic biomedical devices capable of generating mechanical stimulation to the target tissue through highly controlled actuation. Interestingly, mechanical stimulation was found to improve the healing process in animal models of muscle injury and atrophy through immuno-modulation and direct activation of mechanosensors. These mechanobiological approaches for medicine will open new avenues for novel therapeutics for patients and find broad utility in regenerative medicine.

MSE Seminar: "Engineering 2D Quantum Materials with Atomic Precision" (University of California - Berkeley and Lawrence Berkeley National Laboratory)
2023-03-28 10:30 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Two-dimensional (2D) materials offer a rich platform for studying quantum phenomena, because their properties can be profoundly altered through heterostructure stacking and defect manipulation, while the resulting electronic and magnetic structure can be directly imaged via surface-sensitive probes. I will discuss several examples that highlight the remarkable potential of engineered two-dimensional (2D) materials for exploring novel quantum phases of matter driven by strong correlation and non-trivial topology using scanning tunneling microscopy (STM). I will first discuss our recent work on visualizing and manipulating 1D chiral edge states in a moiré quantum anomalous Hall (QAH) insulator of twisted monolayer-bilayer graphene (tMBLG). Here spectroscopic mapping allows us to directly identify QAH edge states, while combining electrostatic gating and tip-induced doping enables us to create and manipulate QAH edge states on-demand. I will also discuss the interplay between quantum confinement and strong correlation in engineered 1D twin-boundary defects of semiconducting 1H-MoSe2 , which allows direct spectroscopic imaging of spin-charge fractionalization due to the formation of a 1D Tomonaga-Luttinger liquid. I will conclude by providing a glimpse into new avenues of 2D materials engineering involving advanced atomically-precise characterization in the growing field of quantum materials.

ESE Spring Seminar - "Agile Robot Autonomy"
2023-03-28 12:30 - 13:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Quadcopters are among the most agile and dynamic machines ever created. In this talk, I’ll show how data-driven sensorimotor controllers can push quadcopters with only onboard sensing and computation to their physical limits. Such controllers enable quadcopters to fly faster and more agile than what was possible before in unstructured environments like cities, forests, and disaster scenarios. The insights acquired from quadcopter flight transfer to other domains, including legged locomotion and bio-inspired vision. However, fundamental research questions still need to be addressed to make agile robots adaptable, robust, and safe, and enable their wider application in homes, search and surveillance, and inspection. Teaser videos of the results I will present are Deep Drone Acrobatics (https://youtu.be/2N_wKXQ6MXA) and Agile Autonomy (https://youtu.be/m89bNn6RFoQ).

CIS Seminar: "Collaborative, Communal, & Continual Machine Learning"
2023-03-28 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Pre-trained models have become a cornerstone of machine learning thanks to the fact that they can provide improved performance with less labeled data on downstream tasks. However, these models are typically created by resource-rich research groups that unilaterally decide how a given model should be built, trained, and released, after which point it is never updated. In contrast, open-source development has demonstrated that it is possible for a community of contributors to work together to iteratively build complex and widely used software. This kind of large-scale distributed collaboration is made possible through a mature set of tools including version control and package management. In this talk, I will discuss a research focus in my group that aims to make it possible to build machine learning models in the way that open-source software is developed. Specifically, I will discuss our preliminary work on merging multiple models while retaining their individual capabilities, patching models with cheaply-communicable updates, designing modular model architectures, and tracking changes through a version control system for model parameters. I will conclude with an outlook on how the field will change once truly collaborative, communal, and continual machine learning is possible.

Reflections by 50 Years of Women CIS Faculty
2023-03-28 17:00 - 18:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Please join Ruzena Bajcsy, Susan Davidson, Stephanie Weirich and Linh Phan for a panel discussion.
Reception to Follow
ABSTRACT:
Women have always been part of computing at Penn, from the women who programmed the ENIAC, to the first woman faculty member, Ruzena Bajcsy, who arrived in 1972 as the CIS department was being formed, to new faculty members joining this year. This panel, consisting of women CIS faculty members from different decades over the past fifty years, will discuss what their experiences have been like, addressing the department and research environment, teaching and climate for women.
Additional information about this event, including full speaker bios, is available on the Computer and Information Science website.

Ruzena Bajcsy
Professor Emeritus
Electrical Engineering and Computer Sciences, University of California, Berkeley;
Computer and Information Science, Penn Engineering

Susan Davidson
Weiss Professor
Computer and Information Science
Penn Engineering

Stephanie Weirich
ENIAC President’s Distinguished Professor
Computer and Information Science
Penn Engineering

Linh Phan
Associate Professor
Computer and Information Science
Penn Engineering

BE Doctoral dissertation Defense: "Understanding the Cellular and Gene-regulatory Mechanisms Underlying the Mesenchymal Transition of Ependymoma Tumor Cells Using Omics Data" (Rachael Aubin)
2023-03-29 09:30 - 11:30 | Class of 62 Auditorium, John Morgan Building, 3620 Hamilton Walk, Philadelphia, PA, 19104
The Department of Bioengineering at the University of Pennsylvania and Dr. Pablo Camara are pleased to announce the Doctoral Dissertation Defense of Rachael Aubin.

Title: UNDERSTANDING THE CELLULAR AND GENE-REGULATORY MECHANISMS UNDERLYING THE MESENCHYMAL TRANSITION OF EPENDYMOMA TUMOR CELLS USING OMICS DATA

Date: Wednesday, March 29
Time: 9:30am
Location: Reunion Auditorium, John Morgan Building

Zoom link: https://upenn.zoom.us/j/97229075338

The public is welcome to attend.

ASSET Seminar: , Dinesh Jayaraman (University of Pennsylvania)
2023-03-29 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
An important goal of the field sensorimotor robot learning is to do away with cumbersome expertise-intensive task specification, so that general-purpose robots of the future might learn large numbers of new skills. In this talk, I will discuss our recent work on algorithms that exploit goals as a versatile and accessible task specification interface. Goals might be specified through images, language, or physical objects, and may either be provided by a layperson or even discovered autonomously by a robot exploring its environment. I will show how unsupervised learning from large human action datasets can train goal-conditioned value functions for robots, how learned verification behaviors can in turn help to evaluate and acquire new skills, and how careful model-based reasoning can help a robot discover interesting goal-based tasks in an environment with no supervision.

Spring 2023 GRASP SFI: Ram Vasudevan, University of Michigan, "Can't Touch This: Real-Time, Provably Safe Motion Planning and Control for High Dimensional Autonomous Systems"
2023-03-29 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Levine 307 and virtual attendance via Zoom. This week’s presenter will be in-person as well.
ABSTRACT
A key challenge to the widespread deployment of robotic manipulators is the need to ensure safety in arbitrary environments while generating new motion plans in real-time. This talk describes a technique that constructs a parameterized representation of the forward reachable set that it then uses in concert with predictions to enable certified, collision checking. To improve computational speed, this talk describes how to represent this parameterized reachable set using a neural implicit representation without sacrificing any safety guarantees. This approach, which is guaranteed to generate safe behavior, is demonstrated across a variety of different real-world platforms including ground vehicles, manipulators, and walking robots.

MSE Seminar: "Natural Structural Materials: Lessons on Toughening Mechanisms, Weight Reduction, and Multifunctionality" (Virginia Tech University)
2023-03-30 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Structural materials that are damage tolerant, lightweight, multifunctional, and sustainable are highly desirable for many engineering applications. Such combinations of properties are often found in the biological world. Organisms from nature construct a variety of different biological structural materials for protection, predation, body support, camouflage, etc. Despite the fact that these materials are made from limited constituent materials with usually poor intrinsic mechanical properties, such as brittle minerals and soft biopolymers, biological materials are often able to achieve remarkable mechanical properties while offering additional functionalities simultaneously, such as low density, coloration, transparency, flexibility, visual sensitivity, etc. In this talk, I will present our recent work in elucidating the fundamental structure-property relationships in some natural structural materials by focusing on their strategies in achieving damage tolerance, weight reduction, and multifunctionality. In particular, I will present a unique damage-tolerant, dual-scale, single-crystalline, low-density microlattice that we recently discovered in an echinoderm skeletal system. Our research combines quantitative multiscale 3D structural analysis, in-situ mechanical analysis, theoretical and computational modeling, and design and manufacturing of bio-inspired materials. I hope this talk can stimulate more discussions among research areas such as material synthesis, biomimetics, mechanics, biology, and manufacturing.

ESE & MEAM Seminar - "Enabling Self-sufficient Robot Learning"
2023-03-30 12:30 - 13:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Autonomous exploration and data-efficient learning are important ingredients for helping machine learning handle the complexity and variety of real-world interactions. In this talk, I will describe methods that provide these ingredients and serve as building blocks for enabling self-sufficient robot learning.
First, I will outline a family of methods that facilitate active global exploration. Specifically, they enable ultra data-efficient Bayesian optimization in reality by leveraging experience from simulation to shape the space of decisions. In robotics, these methods enable success with a budget of only 10-20 real robot trials for a range of tasks: bipedal and hexapod walking, task-oriented grasping, and nonprehensile manipulation.
Next, I will describe how to bring simulations closer to reality. This is especially important for scenarios with highly deformable objects, where simulation parameters influence the dynamics in unintuitive ways. The success here hinges on finding a good representation for the state of deformables. I will describe adaptive distribution embeddings that provide an effective way to incorporate noisy state observations into modern Bayesian tools for simulation parameter inference. This novel representation ensures success in estimating posterior distributions over simulation parameters, such as elasticity, friction, and scale, even for scenarios with highly deformable objects and using only a small set of real-world trajectories.
Lastly, I will share a vision of using distribution embeddings to make the space of stochastic policies in reinforcement learning suitable for global optimization. This research direction involves formalizing and learning novel distance metrics on this space and will support principled ways of seeking diverse behaviors. This can unlock truly autonomous learning, where learning agents have incentives to explore, build useful internal representations and discover a variety of effective ways of interacting with the world.

BE Seminar: "Engineering therapeutic immunity using (nano)biomaterials" (Natalie Artzi, Harvard Medical School)
2023-03-30 15:30 - 16:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
This seminar will be held in person only; snacks will be provided.
Immunomodulatory therapies have advanced to clinical trials over the past decade for the treatment of a range of diseases and disorders, from cancer to diabetes to transplant rejection. However, the efficacy of these therapies remains limited, as challenges associated with off-target drug toxicity, poorly controlled drug pharmacokinetics, and an incomplete understanding of real-time therapy responses prevent effective therapeutic windows from being realized. Here, I will highlight some of our work on the design, fabrication, and characterization of biomaterial-based delivery technologies for the controlled delivery of combination immunotherapies and for the non-invasive monitoring of their associated immune responses for cancer therapy. We show that the design of materials and their delivery context can influence therapeutic outcomes and alter the spatiotemporal characteristics of the incited immunomodulatory responses. By adroitly designing and utilizing our material delivery platforms, we can deliver immunotherapies with tailorable pharmacokinetics and enhanced efficiency to improve long-term therapeutic outcomes and tolerability and enable studying basic questions in immunobiology as we seek to generate a ‘living’ therapeutics.

Spring 2023 GRASP on Robotics: Pulkit Agrawal, MIT, "Fun with Robots and Machine Learning"
2023-03-31 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. This week’s presenter will be in-person as well.

ABSTRACT
Robots are getting smarter at converting complex natural language commands describing household tasks into step-wise instructions. Yet, they fail to actually perform such tasks! A prominent explanation for these failures is the fragility and inability of the low-level skills (e.g., locomotion, grasping, pushing, object re-orientation, etc.) to generalize to unseen scenarios. In this talk, I will discuss a framework for learning low-level skills that surpasses limitations of current systems at tackling contact-rich tasks and is real-world-ready: generalizes, runs in real-time with onboard computing, and uses commodity sensors. I will describe the framework using the following case studies:
(i) a dexterous manipulation system capable of re-orienting novel objects.
(ii) a quadruped robot capable of fast locomotion and manipulation on diverse natural terrains.
(iii) learning from a few task demonstrations of an object manipulation task to generalize to new object instances in out-of-distribution configurations.

Spring 2023 GRASP Seminar: Larry Matthies, Jet Propulsion Laboratory, California Institute of Technology, "Autonomous mobility in Mars exploration: recent achievements and future prospects"
2023-03-31 13:30 - 14:30 | Berger Auditorium (Room 13), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Berger Auditorium (Skirkanich Floor B) and virtual attendance via Zoom. This week’s presenter will be in-person as well.

ABSTRACT
This talk will summarize key recent advances in autonomous surface and aerial mobility for Mars exploration, then discuss potential future missions and technology needs for Mars and other planetary bodies. Among recent advances, the Perseverance rover that is now operating on Mars includes new autonomous navigation capability that dramatically increases its traverse speed over previous rovers. Perseverance also carried the Ingenuity helicopter to Mars, which is a technology demonstration of the first heavier-than-air aircraft ever to operate on another planet. The current mission objective for Perseverance involves driving a total distance of about 60 kilometers in about 10 Earth years. Rover mission concepts recently suggested for the Moon would drive about 1500 to 2000 km in under 4 years, which requires significant advances in autonomy. Successors to the Ingenuity helicopter are now under development for use in a mission planned for later this decade to return Mars samples to Earth that Perseverance is collecting. Much larger helicopter concepts are being studied to enable carrying larger science instrument payloads for potential future Mars missions. Robotic surface and aerial vehicles, as well as drilling systems for subsurface access, potentially could play a role in NASA’s goals for a human mission to Mars roughly two decades from now.

MEAM Seminar: "Wall-modeled Large-eddy Simulation of the Turbulent Boundary Layer with Mean-flow Three-dimensionality"
2023-04-03 14:00 - 15:00 | Towne 309, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
The capability to predict high-Reynolds-number turbulent flows is essential for many natural and engineering flows such as external aerodynamics of wind turbines and aircraft wings, flow over the hull of marine vehicles, atmospheric boundary-layer flow over complex landscapes and cityscapes. However, due to extreme disparity of scales present in high-Reynolds-number wall-bounded turbulent flows, any attempt to simulate these flows directly on a computational grid without resorting to modeling of some sort results in prohibitively large computational cost. Wall-modeled large-eddy simulation (WMLES) show perhaps the most promise in being able to capture more of the relevant flow physics while keeping computational cost tractable in simulating these flows. There have been many novel wall models being developed during the last decades. However, the applications of most of the models are limited to canonical two-dimensional turbulent flows such as the turbulent channel flow where non-equilibrium effects including pressure gradient and mean-flow three-dimensionality are missing.
In this talk, I will present a comparative study of WMLES of a turbulent boundary layer with mean-flow three-dimensionality developing on the floor of a bent square duct which mimics the flow over the swept wing of the aircraft. The predictive capabilities of three widely used wall models, namely, a simple equilibrium stress model, an integral nonequilibrium model, and a PDE nonequilibrium model, have been investigated. These models potentially span the complete spectrum of wall models with varying physical details and complexity. While the wall-stress magnitudes predicted by the three wall models are comparable, the PDE nonequilibrium wall model produces a substantially more accurate prediction of the wall-stress direction, followed by the integral nonequilibrium wall model. The wall-stress direction from the wall models is shown to have separable contributions from the equilibrium stress part and the integrated nonequilibrium effects, where how the latter is modeled differs among the wall models. Budget analyses have been conducted to elucidate precise mechanisms by which the three wall models produce different predictions of the wall shear stress directions given almost identical inputs. The physical characteristics of the three-dimensional turbulent boundary layer including the generation mechanism of mean-flow three-dimensionality and the anisotropy of turbulence will also be discussed in the talk.

5th Annual Mechanobiology Symposium
2023-04-04 - 2023-04-05 | Smilow Center Auditorium, 3400 Civic Center Blvd, Philadelphia, PA, 19104, United States
This two-day symposium is organized by the Center for Engineering MechanoBiology (CEMB) with support from the National Science Foundation. The theme will be MechanoImmunology and Epigenetics.
The CEMB is a Science and Technology Center funded by the National Science Foundation; our research focus is to advance the study of mechanical forces in molecules, cells, and tissues in plants and animals. The theme of this 5th symposium will be the role of forces on immunology and epigenetics. We are inviting leaders in these fields to join a relatively small group environment where new state-of-the-art research can be presented and discussed.
This meeting will be in-person at University of Pennsylvania in Philadelphia, PA. While we encourage in-person attendance, this meeting will also be streamed for registrants that cannot attend in person.

Please register by March 1, 2023 to gain access to the meeting.
We are currently accepting poster abstracts for our poster session. If you are interested in presenting a poster, please submit a title and abstract (1500 character limit) HERE by March 1, 2023.
Invited speakers:

Adelin Barbacci, French National Centre for Scientific Research, National Institute for Agriculture, Food, and Environment
Marco Fritzsche, Rosalind Franklin Institute, Kennedy Institute for Rheumatology, University of Oxford
Claire Hivrov, Institut Curie
Lance Kam, Columbia University
Matthew Lang, Vanderbilt University
Song Li, University of California, Los Angeles
Yekaterina Miorshnikova, National Institutes of Health
Maeli Melotto, University of California, Davis
Guilherme Nader, Children’s Hospital of Philadelphia
Verena Ruprecht, Centre for Genomic Regulation

For inquiries, please contact:
Symposium logistics: Annie Jeong, CEMB Managing Director (annjeong@seas.upenn.edu)
Scientific content: Vivek Shenoy, CEMB Director (vshenoy@seas.upenn.edu)
CEMB event website: https://cemb.upenn.edu/research/mechanobiology-annual-symposium/

MEAM Seminar: "Material-Enabled Technologies for Soft and Fluidic Robots"
2023-04-04 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The emerging field of soft robotics, which incorporates unconventional or compliant materials in autonomous systems, has simultaneously reshaped traditional robotics applications and introduced new use cases for robots. However, many useful classes of materials remain relatively unexplored, and furthermore, the vast majority of soft robotics research has targeted actuation and sensing, with power and control schemes still relying on bulky, rigid electronic components. My research program addresses open questions in these domains by applying our expertise in energy, fluids, and materials. For instance, biotic materials—non-living materials derived from living organisms—have remained underutilized in robotics, despite having played a role in human development since the times our early ancestors wore animal hides as clothing and used bones for tools. In the first part of my talk, I describe how we repurposed an inanimate spider as a ready-to-use actuator requiring only a single fabrication step, initiating the area of “necrobotics” in which biotic materials are used as robotic components. The second part of my talk focuses on assistive wearable robots, which currently rely on bulky and hard control systems and power supplies, or alternatively require cumbersome tethers to external infrastructure. To address this limitation, my group has developed completely soft fluidic digital logic components fabricated entirely from textiles. Our fluidic logic platform enables integrated memory, decision making, and the ability to interact with and adapt to stimuli and the environment, all without the use of rigid valves or electronics. Meanwhile, we address limitations in power delivery by developing “self-powered” textile-based wearable robots that harvest energy from the motion of the human body. The integration of fluidic logic and energy harvesting in textile architectures represents an important step toward fully soft, self-sufficient wearable robots that are as comfortable, resilient, and practical as everyday clothing.

(Re)Connecting in the Classroom: Evan C Thompson Lecture on Excellence in Teaching
2023-04-04 16:00 - 17:00 | Van Pelt Library, Kislak Center, 6th Floor, 3420 Walnut Street, Philadelphia, 19104, United States
Lately there has been much talk in universities and the public about “the great disengagement.” As we emerge from the pandemic era, many students and instructors alike are experiencing a lack of energy and motivation, and we are seeking encounters in the classroom that are transformative, rather than simply transactional.
In this talk, Daeyeon Lee will reflect on his own evolution as a teacher, from his early focus on content delivery to his current practice of infusing classes with intrigue, storytelling and humor. Speaking from his own experiences, Lee will argue that creative exchanges with our students are just as important as content coverage in today’s classrooms. He will share some of his strategies for engaging students, practices that have enabled him to establish meaningful relationships with his students while also maintaining high academic standards. He shows us that taking time to connect with each other socially and emotionally is an essential part of revitalizing our intellectual culture and community.

MEAM Ph.D. Thesis Defense: "Towards Digital Twins for Cardiovascular Flows: A Hybrid Machine Learning and Computational Fluid Dynamics Approach"
2023-04-05 09:00 - 10:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
To design personalized treatment strategies, a number of measurable quantities (biomarkers) that relate a patient’s clinical representation to the existence, progress, and outcome of a disease need to be identified and measured. In cases where a biomarker is strongly correlated with the disease outcome, e.g. vascular pressure for hypertension, changes to the biomarker will perfectly describe changes of the disease outcome. However these ofter require invasive procedures to be measured. When the desired biomarkers correspond to physical properties, computational mechanics can be leveraged to obtain predictions in-silico. Unfortunately, computational models require a list of patient specific parameters, such as precise boundary conditions, which also cannot be easily measured in-vivo. Inaccurate calibration of these parameters is often the cause of poor predictions, therefore hindering the translational impact of computational methods. These challenges motivate the need flexible and computationally efficient frameworks that can operate under uncertain model assumptions and partial measurements.
The goal of this thesis is to introduce a novel approach to precision medicine by synthesizing artificial intelligence (AI) and computational modeling. We start by exploring how one can use available patient data to estimate parameters in computational fluid dynamics models of arterial blood flow, and show that this is prohibitively expensive. Then we accelerate the prediction of biomarkers by training surrogates to reconstruct available measurements by building physics-informed machine learning models to infer correlations between measurable (e.g., blood velocity) and unmeasurable quantities (e.g., vascular pressure) through underlying laws of fluid mechanics. We show that even though this is a successful approach it also faces challenges in generalizing to new clinical scenarios. Finally we propose a purely data-driven approach for making online biomarker predictions. In many biological scenarios the data acquisition process can be expensive and time consuming, limiting the amount of available training data. For this purpose, we propose creating a virtual patient database via computational fluid dynamics to train a neural operator model which we then use to make online predictions for new patients and clinical conditions. This computational efficiency that this brings has the potential to bridge the gap between modeling and clinical decision making.

ASSET Seminar: Lockout: Sparse Regularization of Neural Networks, Gilmer Valdes (UCSF)
2023-04-05 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
Many regression and classification procedures fit a function f(x;w) of predictor variables x to data 〖{x_i,y_i}〗_1^N based on some loss criterion L(y,f(x;w)). Often, regularization is applied to improve accuracy by placing a constraint P(w)≤t on the values of the parameters w, where P is a monotonic increasing function of the absolute values of the parameters (e.g. Lasso, Ridge). Although efficient methods exist for finding solutions to these constrained optimization problems for all values of t≥0 in the special case when f is a linear function, none are available when f is non-linear (e.g. Neural Networks). Here we present a fast algorithm that provides all such solutions (path) for any differentiable function f and loss L, and any differentiable constraint P that is an increasing monotone function of the absolute value of each parameter. Applications involving sparsity inducing regularization of arbitrary Neural Networks are discussed. Empirical results indicate that these sparse solutions are usually superior to their dense counterparts in both accuracy and interpretability (sometimes strikingly better). This improvement in accuracy can often make Neural Networks competitive with, and sometimes superior to, state-of-the-art methods in the analysis of tabular data. Specific applications to Medicine, in particular, Microarray data are discussed.

Spring 2023 GRASP SFI: Matt Zucker, Swarthmore College, "Robotics education and research at a liberal arts college"
2023-04-05 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. This week’s presenter will be in-person as well.
ABSTRACT
In this talk, I will describe the transition from a research-intensive PhD to a position at a teaching-focused undergraduate institution in the context of my own career trajectory. Key topics include connections between robotics and the liberal arts, and guidelines for graduate students who are curious about pursuing teaching-focused faculty jobs.

MSE Seminar: "Designing Quantum Properties and Functionalities in Heterostructures" (MIT)
2023-04-06 10:30 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Interfaces in heterostructures often exhibit emergent physical properties that are absent in the constituent layers. These heterostructures, together with their compatibility with nanofabrication, are promising for constructing functional quantum devices. I will illustrate the capability of such heterostructure engineering by taking two examples. I will first explain our discovery of a versatile method for synthesizing ferroelectric materials from non-ferroelectric two-dimensional (2D) materials: by physically stacking two monolayer boron nitrides at controlled angles, novel types of ferroelectricity emerge at the interface. I will demonstrate its functionality as one of the world’s thinnest ferroelectric non-volatile memories at room temperature. As another example, I will demonstrate the versatile spintronic functionalities of topological insulator heterostructures synthesized by a thin film growth method. I will conclude by discussing how we can overcome the limits of existing heterostructure engineering for the future design of quantum materials and functionalities.

BE Doctoral Dissertation Defense: "Investigating the Role of Lipid Droplets as Intracellular Mechanical Stressors in Non-alcoholic Fatty Liver Disease" (Abigail Lonker)
2023-04-06 13:00 - 15:00 | Smilow Center for Translational Research in SCTR 11-146AB
The Department of Bioengineering at the University of Pennsylvania and Dr. Rebecca Wells are pleased to announce the Doctoral Dissertation Defense of Abigail Lonker.
Title: Investigating the Role of Lipid Droplets as Intracellular Mechanical Stressors in Non-alcoholic Fatty Liver Disease
Date: April 6, 2023
TIme: 1:00 PM
Location: Smilow Center for Translational Research in SCTR 11-146AB
The public is welcome to attend.

IoT4Ag Seminar: Sensing and Robotics for Specialty Crop Production
2023-04-06 14:30 - 15:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Register to attend via Zoom

PICS Colloquium: "Deep Anomaly Detection using Coincident Learning"
2023-04-07 14:00 - 15:00 | https://upenn.zoom.us/j/96715197752
Anomaly detection is a crucial task in the operation of complex systems such as industrial facilities, manufacturing plants, and large-scale science experiments. Failures in a sub-system can result in low yield, faulty products, or damage to components, making it essential to detect anomalies as quickly as possible. Despite the abundance of data available for complex systems, labeled anomalies are rare and expensive to obtain. To address this issue, we present a novel approach called CoAD that trains anomaly detection models on unlabeled data by leveraging the correlation between sub-systems and products. CoAD works by analyzing two data streams, s and q, which represent subsystem diagnostics and final product quality, respectively. We define an unsupervised metric, akin to the supervised classification F_beta statistic, to assess the performance of independent anomaly detection algorithms on s and q based on their coincidence rate. Our method is demonstrated in four cases, including a synthetic outlier data set, a synthetic imaging data set generated from MNIST, a metal milling data set, and a data set obtained from a particle accelerator. By using CoAD, we can detect anomalies in complex systems more effectively, even when labeled anomalies are scarce.
Email jnespos@seas.upenn.edu for the Zoom link.

ESE Spring Seminar - "Towards Scalable Multi-User Wireless Networking in mmWave and Terahertz Spectrum"
2023-04-10 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Millimeter-wave and terahertz bands are emerging as the most promising spectrum to meet the data-rate and latency demands of future wireless applications, including virtual reality and autonomous cars. Moreover, the large spectral availability together with the mm-scale wavelength, opens the opportunity of scaling the capacity of future wireless networks by supporting highly directional, high data rate multi-user transmission and reception. My research builds a foundation for scalable multi-user wireless systems in such high-frequency regimes yielding a paradigm shift in the design and development of future wireless systems. In this talk, I will begin by presenting emerging transceiver architecture that can enable directional sub-THz steering without traditional multi-antenna arrays. I will discuss how to exploit the key characteristics of sub-THz signals and the proposed architecture to enable the first scalable single-shot single-antenna multi-user system in THz bands with angularly dispersive links that are robust to client and environmental mobility. By exploiting electro-magnetics of antenna to protocol design, signal processing, and end-to-end system design with analytical model-driven evaluations and over-the-air experiments, I will show how the multi-user performance of an angularly dispersive THz link fundamentally depends on frequency, angle, and bandwidth utilized by users, through non-linear mechanisms and achieving close to Tb/s aggregate data rates using just a single-element antenna link. I will then discuss the opportunities offered by this platform to enhance next-generation communication and sensing capabilities in unprecedented ways. In particular, we tackle the mobility, blockage, and scalability challenges of highly directional wireless networks by efficiently adapting steering direction for mobile users. Finally, I will share several research directions in wireless networking, sensing, and security in mmWave and THz networks that I would like to pursue in the future.
