ESE & BE Spring Seminar - "Ultra-high-throughput computational imaging: towards a trillion voxels per second"
2024-02-22 11:00 - 12:00 (America/New_York) | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Traditional biomedical imaging techniques face throughput bottlenecks that limit our ability to study complex dynamic samples like cells, organoids, tissues, and organisms. In particular, hardware-only systems have inherent physical limitations preventing the simultaneous improvement of resolution, field of view, and frame rate. In this seminar, I propose that large-scale, machine learning-accelerated computational imaging will be the key to overcoming these throughput bottlenecks. I demonstrate a variety of examples from my research, ranging from resolution-enhanced, speckle-free tissue imaging with optical coherence refraction tomography, to camera array-based gigapixel microscopy and 4D fluorescence tomography of freely-behaving zebrafish and fruit flies. Critical to the computational scalability is the integration of physics-supervised deep learning into my reconstruction algorithms. This approach is inherently robust to generalization errors and does not require labeled data, as it uses the differentiable physical model as the only supervision mechanism. Combined with scalable hardware designs, these high-performance computational imaging systems will continue the trend of my research towards ultra-high imaging throughputs, even approaching 1 trillion voxels per second, which will accelerate scientific discovery, big data generation, and tool development across a broad range of biomedical applications.

BE Seminar: "Endothelial cells and the promise of regeneration on demand" (Brisa Palikuqi, UCSF)
2024-02-22 15:30 - 16:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
In this seminar, I explore the pivotal role of tissue stem cells and their microenvironment, known as the niche, in regeneration. With a focus on the endothelial cell niche, my work introduces an innovative in vitro vascularized perfusable model tailored for human tissue explants and organoids. My findings also highlight the crucial contribution of paracrine factors derived from lymphatic endothelial cells in facilitating intestinal regeneration and repair in vivo. I will also outline future research directions for my independent laboratory, where I aim to unravel the complexities of endothelial cell interactions and paracrine signaling in tissue regeneration. The overarching goal is to leverage this knowledge for engineering vascularized and physiologically relevant organoids, advancing our understanding of regenerative medicine and stem cell biology.

Spring 2024 GRASP on Robotics: Pietro Valdastri, University of Leeds, "Magnetic Surgical Robots: A “Fantastic Voyage” deep inside the human body"
2024-02-23 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom.
ABSTRACT
Magnetic fields offer the possibility of manipulating objects from a distance and are ideal for medical applications, as they penetrate human tissue without inflicting any harm on the patient. Magnetic fields can be harnessed to actuate surgical robots, enhancing the capabilities of surgeons in reaching deep into the human anatomy through complex winding pathways, thus providing minimally invasive access to organs that are out of reach with current technologies. In this talk, we will explore various robotic architectures based on magnetic control, specifically designed for lifesaving clinical applications. These architectures include a magnetic flexible endoscope for painless colonoscopy, soft magnetic tentacles personalized for reaching peripheral areas of the lung and navigating the pancreatic duct, and magnetic “fusilli” robots designed for collaborative bimanual tasks in a confined workspace. We will also discuss enabling technologies, intelligent control, potential levels of computer assistance, the path to first-in-human trials, and highlight the future challenges associated with this ongoing Fantastic Voyage.

PICS Colloquium: "Genetic testing and adverse selection"
2024-02-23 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Technology is dramatically driving down the cost of sequencing genetic data and increasing the quality of predictions made with this data. A standard concern is that these predictions could impair the functioning of insurance markets, either because insurers would abuse genetic information or because of adverse selection.
We make three contributions. First, we develop a methodology to measure how much selection would be created by genetic information in the market for an insurance product. Second, we extend the methodology to measure the amount of selection with future prediction technology, by combining information from heritability studies and empirical regularities from genetic epidemiology. Third, we apply the methodology to critical illness insurance using data from the UK biobank, including genetic information and National Health Service records for 800,000 UK citizens.
The main substantive finding is that selection would make many of these markets untenable unless insurers are allowed to underwrite based on genetic information. However, there are important differences in how the results vary by the type of illness and market.

CBE Doctoral Dissertation Defense: "Synthesis of Enzyme-Powered Motors using Microfluidics" (Jessica O'Callaghan)
2024-02-26 14:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:

This thesis addresses the fundamental questions surrounding the design and functional capabilities of enzyme-powered micromotors synthesized using microfluidic techniques. The research focuses on the development of these motors, made from artificial cell (protocell) scaffolds, and which seek to replicate the motion behavior of biological cells, investigating their propulsion mechanisms, motion directionality, and collective behavior. The thesis first describes the development of a microfluidic platform for the synthesis of polymer and polymer-protein-based protocells. This platform enables precise control over the size, composition, and functional properties of the protocells, demonstrating the versatility of microfluidics in the fabrication of complex microstructures. Next, a novel approach to creating urease-powered micromotors using double emulsion-templated microcapsules is presented. The study explores how surfactants used in the emulsion assembly step that integrate themselves into the microcapsule structure can reliably lead to autonomous motion, providing insights into the design principles that govern the efficiency of enzyme-powered motors prepared by droplet microfluidics. The thesis next investigates the directed motion of urease-powered motors in gradients of urea, revealing how these motors can be directed away from high concentrations of substrate, providing insights into how to control their motion in complex fluids. Finally, the thesis explores interactions between enzyme-powered (active) and passive particles, demonstrating how active particles influence the motion of passive ones. The findings of this dissertation significantly advance our understanding of enzyme-powered motors, offering new strategies for their design and application. The use of microfluidic technology for the synthesis of these motors opens up new possibilities for the precise control of their properties, paving the way for their use in a wide range of scientific and technological applications.

PRECISE Seminar: Image Curation for AI in Ophthalmology
2024-02-26 18:00 - 19:00 | https://upenn.zoom.us/j/93008201901
This presentation will explore the critical process of curating medical imaging data for AI algorithm development in ophthalmology, highlighting the challenges and current limitations in data curation. It will discuss benchmark datasets, reference standards for FDA validation, and innovative strategies to enhance data availability. Attendees will gain insights into best practices and future directions in image curation for advancing AI applications in eye care.

MEAM Seminar: "Harnessing Mechanobiology for Therapeutic Innovations: From Brain Tumors to Kidney Tissues"
2024-02-27 10:00 - 10:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Engineered, personalized tissues are transforming healthcare by accelerating clinical testing and serving as cell-based therapies. The emergence of induced pluripotent stem cells coupled with innovations in biomanufacturing and cellular engineering have rapidly advanced engineered tissue cellular and structural complexity. However, generating functional, mature tissues remains an enormous challenge. Control over biophysical forces governing development and disease is ultimately required to build functional tissue, and engineered tissues can simultaneously illuminate opportunities to therapeutically modulate mechanical cues. In the first part of my talk, I will explain how I leveraged hydrogel-based models to investigate cell-matrix interactions driving brain tumor cell invasion. While studies have traditionally focused on integrin-driven invasion, this work elucidated how the transmembrane receptor CD44 directly contributes to cell motility in the brain and may represent an important therapeutic target. In the second part of my talk, I will describe the biofabrication of a stem cell-derived kidney collecting duct on-chip. Collecting ducts are a major site for kidney disease and dysfunction, and this on-chip model could serve as a platform to study flow-dependent function in patient-derived cells. Moreover, I demonstrate that scalable organoid culture methods combined with bioprinting offers a promising approach to integrating these collecting ducts with biomanufactured kidney tissues. Moving forward, the combination of stem-cell derived tissues and organoids with the ability to control mechanical cues establish a paradigm for investigating the mechanobiology of the urogenital tract, with potential applications in kidney and reproductive health.

ESE & CIS Spring Seminar - "Towards Transparent Representation Learning"
2024-02-27 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Machine learning models trained on vast amounts of data have achieved remarkable success across various applications. However, they also pose new challenges and risks for deployment in real-world high-stakes domains. Decisions made by deep learning models are often difficult to interpret, and the underlying mechanisms remain poorly understood. Given that deep learning models operate as black-boxes, it is challenging to understand, much less resolve, various types of failures in current machine learning systems.
In this talk, I will describe our work towards building transparent machine learning systems through the lens of representation learning. First, I will present a white-box approach to understanding transformer models. I will show how to derive a family of mathematically interpretable transformer-like deep network architectures by maximizing the information gain of the learned representations. Furthermore, I will demonstrate that the proposed interpretable transformer achieves competitive empirical performance on large-scale real-world datasets, while learning more interpretable and structured representations than black-box transformers. Next, I will present our work on training the first set of vision and vision-language foundation models with rigorous differential privacy guarantees, and demonstrate the promise of high-utility differentially private representation learning. To conclude, I will discuss future directions towards transparent and safe AI systems we can understand and trust.

CIS Seminar: "Decision Making with Internet-Scale Knowledge"
2024-02-27 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Machine learning models pretrained on internet data have acquired broad knowledge about the world but struggle to solve complex tasks that require extended reasoning and planning. Sequential decision making, on the other hand, has empowered AlphaGo’s superhuman performance, but lacks visual, language, and physical knowledge about the world. In this talk, I will present my research towards enabling decision making with internet-scale knowledge. First, I will illustrate how language models and video generation are unified interfaces that can integrate internet knowledge and represent diverse tasks, enabling the creation of a generative simulator to support real-world decision-making. Second, I will discuss my work on designing decision making algorithms that are compatible with generative language and video models as agents and environments. Combining pretrained language and video models with decision making algorithms can effectively solve a wide range of tasks such as developing chatbots, learning robot policies, and discovering novel materials

ASSET Seminar: "Large Language Models in Medicine: Opportunities and Challenges" (Mark Dredze, Johns Hopkins University)
2024-02-28 12:00 - 13:15 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
ABSTRACT:
The rapid advance of AI driven by Large Language Models (LLMs), like ChatGPT, has led to impressive results across a range of different use cases. This has included several models developed for the medical domain which have exhibited surprising behaviors, such as answering medical questions and performing well on medical licensing exams. These results have demonstrated the coming transformation of medicine by AI. In this talk, I will provide an overview of some of the recent advances in this area, and discuss challenges and opportunities for the use of these models in medicine.

ZOOM LINK (if unable to attend in-person): https://upenn.zoom.us/j/99469144782

Spring 2024 GRASP SFI: Spring Berman, Arizona State University, "Scalable Control of Distributed Robotic Systems for Environmental Sensing and Interaction"
2024-02-28 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. This week’s speaker will be virtual.
ABSTRACT
Various applications for autonomous multi-robot systems, such as disaster response, infrastructure repair, agricultural operations, contaminant cleanup, and wildfire suppression, will require these systems to act as distributed sensors, sources, and manipulators in uncertain environments, often without global localization or extensive inter-robot communication. This talk will present dynamical model-based approaches to controlling mobile robot collectives and soft modular robots that operate under such constraints using local sensing and local or no communication. By applying feedback control and optimization techniques to models that describe the dynamics of a continuous abstraction of the system and its individually controllable components, including their stochastic behaviors, scalable control strategies can be designed for a variety of objectives. This talk will discuss strategies for the particular objectives of mapping and control of scalar environmental fields by robotic swarms, cooperative object transport by groups of mobile robots, and reconfiguration of multi-segment continuum robots. The control strategies are illustrated in numerical and physics-based simulations and in experiments with robotic hardware.

CBE Seminar: "Deep Learning-Enabled Design of Functional DNA-Binding Properties" (Cameron Glasscock, University of Washington)
2024-02-28 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract
DNA-binding proteins (DBPs) play critical roles in biology and biotechnology, and there has been considerable interest in the engineering of DBPs with new functions or altered specificities. While there has been success in reprogramming and the specificity of naturally occurring DBPs using selection methods, the computational design of new DBPs that engage with DNA remains an outstanding challenge. Addressing this challenge would lead to new solutions for programmable recognition and manipulation of DNA sequence and structure; and ultimately enable new possibilities for synthetic gene regulation, DNA-modifying enzymes, and many other applications. In this talk, I will describe the development and experimental validation of a computational method for the design of small DBPs that recognize specific target sequences through interactions with bases in the major groove. I will then describe progress towards a generalizable framework for deep-learning enabled design of custom DNA-binding proteins. I will conclude by summarizing my view of the future prospects for this new framework.

MSE SEMINAR "Scalable Classical and Quantum Light Sources"
2024-02-29 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Classical and quantum light sources play a fundamental role in science and technology from quantum computing, to communications, manufacturing, defense, sensing, medicine, or imaging. However, scaling the power of lasers has always come at the cost of single mode operation, a scaling question that has been investigated, without success, since the invention of lasers in 1958. In the first part of the talk, I will propose a solution to this question and discuss a “scale-invariant” laser that remains single mode irrespective of its cavity size. I will show that the discovered strategy, named Berkeley Surface Emitting Laser (BerkSEL), goes beyond the Schawlow-Townes two-mirror strategy that is used by all existing lasers. I will conclude that mirrors are bad for the scaling of lasers [1]. I will also briefly discuss topological lasers that my group pioneered [2-4]. In the second part of the talk, I will discuss a scalable quantum optics platform fully based on silicon with potential applications in future quantum networks [5].
References.
1- R. Contractor, W. Noh, W. Redjem, W. Qarony, E. Martin, S. Dhuey, A. Schwartzberg, and B. Kanté, “Scalable single-mode
surface emitting laser via open-Dirac singularities,” Nature 608, 692–698 (2022).
2- B. Bahari, A. Ndao, F. Vallini, A. El Amili, Y. Fainman, B. Kanté, “Nonreciprocal lasing in topological cavities of arbitrary
geometries,” Science 358, 636-640 (2017).
3- B. Bahari, L. Hsu, S. H. Pan, D. Preece, A. Ndao, A. El Amili, Y. Fainman, and B. Kanté, “Photonic quantum Hall effect and
multiplexed light sources of large orbital angular momenta,” Nature Physics 17, 700–703 (2021).
4- A. Kodigala, T. Lepetit, Q. Gu, B. Bahari, Y. Fainman, and B. Kanté, “Lasing Action from Photonic Bound States in
Continuum,” Nature 541, 196 – 199 (2017).
5- W. Redjem, Y. Zhiyenbayev, W. Qarony, V. Ivanov, C. Papapanos, W. Liu, J. Jhuria, Z. Y. Al Balushi, S. Dhuey, A.
Schwartzberg, L. Z. Tan, T. Schenkel, and B. Kanté, “All-silicon quantum light source by embedding an atomic emissive center
in a nanophotonic cavity,” Nature Communications 14, 3321 (2023).

ESE Spring Seminar - "Structuring light to reveal the invisible"
2024-02-29 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
From quantum physics to cosmology, researchers aim to see things which are typically invisible – be it the entanglement of two particles or infrared signatures from space. In these and various other fields, we are confronted by a common challenge: What we can see with our own eyes or observe using standard optical imaging systems is limited to a small fraction of the information that the detected light actually carries. Two-dimensional (2D), flat images, such as a photo, only reveal the intensity and visible color of the light coming to us from an optical scene. However, light contains a wealth of information on the three-dimensional (3D) position, angle of incidence, spectral content, amplitude, phase, polarization, optical angular momenta, and coherence, amongst others. In fact, if light interacts with media, nature will give us structured light that is spatially varying in the named properties in a fashion that depends on the interaction. In this talk, I will present how we can use these kinds of structured light fields to extract information from an optical scene and, vice versa, how structured light can serve as an excitation or probing tool to gain access to usually invisible information. In this context, we will explore “optical vortices” in phase and polarization, their generation, and application. Moreover, we will gain insights into the nanoscale and quantum features of structured light and its leading role for next-generation imaging and sensing techniques.

BE Seminar: "Systems Immunology Approaches for Tissue Repair and Regeneration" (Andres Munoz-Rojas, Harvard)
2024-02-29 15:30 - 16:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The immune system uses a complex network of interacting cells that work together to regulate tissue physiology, homeostasis, and repair. In muscle, a tightly coordinated network of immunocytes and mesenchymal stromal cells (MSCs) is required for adequate skeletal muscle repair after acute injury or disease. Regulatory T cells (Tregs) are important players in regulating excessive inflammation and potentiating regeneration, but the extent of intercellular communications underlying their functions remains poorly understood. In this seminar, I will discuss my efforts in developing systems immunology approaches to dissect the dynamic communication networks between muscle Tregs and MSCs in a time-resolved study of skeletal muscle injury. Bringing together tools from single-cell and computational biology, engineering, and immunology, we uncovered distinct communication pathways important for the recruitment and induction of regenerative Tregs and the potentiation of muscle repair. This work identifies novel regulatory pathways that can inform therapeutic approaches for muscle-related pathologies.

CIS Seminar: " Secure systems from insecure components"
2024-02-29 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
In many computer systems today, an attacker that breaks one system component can steal data from millions of users. In this talk, I will present three systems that can withstand component compromise. I will describe (1) a single sign-on system that protects user security and privacy from a compromised single sign-on server, (2) a secure-hardware-based backup service that protects user backups from compromised secure hardware devices, and (3) a web search engine that protects user queries from a compromised search engine. These systems provide strong security and privacy properties while taking into account practical constraints such as compatibility requirements, hardware limitations, and user expectations. Each splits user secrets across different system components, using new cryptographic tools to provide necessary functionality while protecting user data.

Spring 2024 GRASP on Robotics: Leonidas Guibas, Stanford University, “Compositional Modeling of 3D Objects and Scenes”
2024-03-01 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. This seminar will NOT be recorded.
ABSTRACT
Modeling 3D objects and scenes creates many challenges, both on the analysis and the synthesis sides. The focus of this talk is the compositional structure of objects (into parts) and of scenes (into objects) — and how such structure informs the modeling of 3D geometry, affordances, and functionality. We discuss a number of neural representations for 3D objects and scenes that are, or can be made to be, structure aware, enabling more efficient reconstruction as well as the creation of variations, both discrete and continuous. The talk will cover recent historical developments of modeling ideas through works that address how to leverage 2D and 3D sensor data (static or dynamic), direct human annotations on 2D images or 3D models, free-form language utterances, and finally physical simulation, all towards learning and exploiting this compositional structure for applications ranging from 3D content creation to robotic manipulation.

Research Impact Seminar - Bring Your Research Out of the Lab (Penn Engineering Entrepreneurship)
2024-03-01 16:00 - 17:30 | Towne 327
Learn how to commercialize your research and navigate Penn’s innovation ecosystem with Penn Engineering: Entrepreneurship. This is the first part of a series from Penn Engineering’s Entrepreneurship group.
Featuring:
Andrew Tsourkas, Professor of Bioengineering, Co-Founder, AlphaThera, Inc, Co-Founder, StreamLaunch, Llc
and
Jeffrey Babin, Professor of Practice and Associate Director of Entrepreneurship at Penn Engineering & Engineering Faculty Director for Venture Lab.
Refreshments will be provided.
Who: Faculty, Post-Docs, and PhD students
Where: Towne 327
When: 4-5:30 pm, Friday March 1, 2024
Add to calendar: Apple | Google | Office 365 | Outlook | Outlook.com | Yahoo
RSVP here (not required)
This session provides an introduction to the innovation and entrepreneurship process. In addition to reviewing key considerations for exploring opportunities for research beyond publication, we will discuss alternative approaches to increasing the impact and value of research. Faculty and practitioners will review commercialization, licensing, and venture creation based on technological innovation.

MEAM Seminar: "Dexterous Decision-Making for Real-World Robotic Manipulation"
2024-03-05 10:00 - 11:30 | Towne 337
For a robot to prepare a meal or clean a room, it must make a large array of decisions, such as what objects to clean first, where to grasp each ingredient and tool, how to open a heavy, overstuffed cabinet, and so on. To enable robots to tackle these tasks, I decompose the problem into two interdependent layers: generating a series of subgoals (i.e., a strategy) and solving for the robot behavior that achieves each of these subgoals. Critically, to accomplish a rich set of manipulation tasks, these subgoal solvers must account for force, motion, deformation, contact, uncertainty and partial observability.
My research contributes models and algorithms that enable robots to reason over both the geometry and physics of the world in order to solve long-horizon manipulation tasks. In this talk, I will first discuss how this approach has enabled robots to perform tasks that require reasoning over and exerting force, like opening a childproof medicine bottle with a single arm. Next, I will present an abstraction for the complex physics of frictional pushing and demonstrate its application within the context of in-hand manipulation. Finally, I will illustrate how robots can make robust choices in the face of uncertainty. For example, this empowers robots to reliably chop up fruit of unknown ripeness!

MEAM Seminar: "Active Materials and Devices for Biomedical Applications"
2024-03-07 10:00 - 11:30 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
In this talk, I will discuss our recent work in materials fabrication, manipulation, assembly, and manufacturing tailored towards biomedical and environmental applications. The focus is on active materials and devices enabled by materials control across a wide range of length scales. At the nanoscale, I will discuss 3D electrokinetic tweezers, an ultra-precision tool developed in my lab, which can be used to manipulate nanowires in room-temperature aqueous solutions. With this technique, designed nanostructures are maneuvered as untethered robotic tools for probing single biological cells; the precision reaches 20 nm in position and 0.5° in orientation in water solution with a standard microscope. At a slightly larger, chip-scale, I will describe a recent innovation that permits the light-controlled patterning of soft actuators made of microbubbles, which assemble large arrays of nanoparticles in parallel. The co-assembly of nanosensor-cell hybrids can be further achieved that detect metabolites of bacterial cells. Finally, I will present a rational scheme for developing large-scale, hierarchically porous superstructures for applications in monitoring human health and public-health relevant water treatment.

BE Seminar: "Charting the future of RNA and protein sequence-structure exploration" (Kalli Kappel, MIT/Harvard)
2024-03-07 15:30 - 16:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
RNA and protein sequences dictate their structures, spanning multiple length scales, from molecular conformations to patterns of subcellular localization. In turn, these structures govern biological function. Characterizing sequence-structure relationships is critical for gaining mechanistic understanding, but conventional techniques can be slow and low-throughput. We have developed integrated computational and experimental methods to overcome these limitations and have applied them to resolve the three-dimensional structures of a wide range of RNA molecules and RNA-protein complexes, and to systematically reveal the protein sequence features that drive condensate formation in cells. This work paves the way for the development of transformative predictive models of RNA and protein sequence-structure relationships.

Spring 2024 GRASP Seminar: Yutong Bai, Johns Hopkins University, "Listening to the Data: Visual Learning from the Bottom Up"
2024-03-08 14:00 - 15:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This seminar will be held in-person in Levine 307 with virtual attendance via Zoom.
ABSTRACT
We introduce a novel sequential modeling approach which enables learning a Large Vision Model (LVM) without making use of any linguistic data. To do this, we define a common format, “visual sentences”, in which we can represent raw images and videos as well as annotated data sources such as semantic segmentations and depth reconstructions without needing any meta-knowledge beyond the pixels. Once this wide variety of visual data (comprising 420 billion tokens) is represented as sequences, the model can be trained to minimize a cross-entropy loss for next token prediction. By training across various scales of model architecture and data diversity, we provide empirical evidence that our models scale effectively. Many different vision tasks can be solved by designing suitable visual prompts at test time.

BE Doctoral Dissertation Defense: "Engineering hydrogel microstructure to promote meniscus repair" (Karen Xu)
2024-03-11 12:00 - 14:00 | JMB Reunion Auditorium, 3620 Hamilton Walk, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania along with Drs. Jason Burdick and Rob Mauck proudly announce the Doctoral Dissertation Defense of Karen Xu.
Title: Engineering hydrogel microstructure to promote meniscus repair
Date: March 11, 2024
Time: 12:00pm
Location: Reunion Auditorium in John Morgan Building
If you would like a zoom link, please email: karen.xu@pennmedicine.upenn.edu
The public is welcome to attend.

Spring 2024 GRASP Seminar: Saurabh Gupta, University of Illinois at Urbana-Champaign, "Robot Learning by Understanding Egocentric Videos"
2024-03-11 14:30 - 15:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
*This seminar will be held in-person in Raisler Lounge (Towne 225) with virtual attendance via Zoom.
ABSTRACT
True gains of machine learning in AI sub-fields such as computer vision and natural language processing have come about from the use of large-scale diverse datasets for learning. In this talk, I will discuss how we can leverage large-scale diverse data in the form of egocentric videos (first-person videos of humans conducting different tasks) to similarly scale up policy learning for robots. A central challenge is the gap in embodiment and intentions. I will describe how we can leverage video data in spite of this gap by learning at different levels of abstraction. I will demonstrate applications of this principle for a) acquiring low-level visuomotor subroutines and high-level value functions for navigation, and b) building an interactive understanding of objects, through observation of human hands, for manipulation.

MEAM Seminar: "Lymphocyte Mechano-regulation for Immunotherapies"
2024-03-12 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
In the dynamic field of biomedical engineering and immunotherapy, my recent research unveils the intricate relationship between mechanical forces and immune cell activation, bridging the realms of biology and immunotherapy. This study aims to unearth innovative pathways for adoptive immunotherapies, emphasizing the role of biomedical and mechanobiological insights in broadening our understanding.
The core focus lies in decoding the mechanobiological pathways governing T cell and B cell activation. It explores the interplay between external mechanical cues and the immune cell activation process, with a nod to biomedical concepts for fresh perspectives. In my presentation I will focus on links between mechanical cues, gene expression profiles, and the spatial organization of genomic loci and transcripts within immune cells. Combining optical super-resolution imaging, traction force and molecular force microscopy with functional read-outs – such as single cell transcriptomics and mitochondrial activity – opens possibilities for quality control in chimeric antigen receptor T (CAR-T) cell therapy, with potential applications in clinical contexts.
This interdisciplinary approach holds the potential to revolutionize adoptive immunotherapies, incorporating insights from biomedical and life sciences.

ESE Spring Seminar - "Learning and controlling noisy quantum systems"
2024-03-12 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Two of the main challenges in scaling up quantum systems are noise and control, arising from the systems’ sensitivity to the environment and its exponential complexity. The first step in resolving these challenges is characterizing and learning the noisy dynamics. In this talk, I’ll discuss how the very quantum features that contribute to this complexity, such as entanglement, can actually enhance our ability to learn quantum processes. I’ll then show how, by using information about noise and its interactions with controls, we can efficiently suppress noise processes on a large scale when executing quantum programs. Additionally, I’ll highlight the advantages of newly developed adaptive control techniques with dynamic circuits for performing long-range entangling operations faster and with greater fidelity than non-adaptive circuits. Finally, I’ll discuss future directions and open questions in understanding noisy quantum systems.

CIS Seminar: "Modern Clouds: Side-Channel Attacks and Defenses"
2024-03-12 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Cloud computing, which has seen significant growth over the past decade, fundamentally relies on the sharing of hardware resources among users. This approach enhances resource utilization and reduces operational costs. However, it also enables unintended information leakage through hardware side channels. Despite the threat of side-channel attacks, cloud vendors remain skeptical about the practicality of these attacks in production cloud environments, leading to inadequate side-channel mitigations.

My PhD research focuses on exploring side-channel attacks in realistic cloud settings and developing comprehensive defenses across the computing stack. In this talk, I will first introduce a series of novel attack techniques that address practical challenges in conducting side-channel attacks in clouds. Using these techniques, I demonstrated an end-to-end, cross-tenant side-channel attack on Google Cloud. This demonstration was subsequently recognized by Google as a critical-level bug, prompting a review by their product team. In the second part of this talk, I will introduce Untangle, a novel framework for side-channel defense. Untangle is designed to quantify and reduce information leakage in defense schemes based on dynamic resource-partitioning. Untangle opens up a new defense paradigm that allows a controlled amount of information leakage in exchange for improved performance. To conclude, I will outline future research directions aimed at developing secure and efficient cloud systems resistant to side-channel attacks.

ASSET Seminar: "Making Machine Learning Predictably Reliable" (Andrew Ilyas, Massachusetts Institute of Technology)
2024-03-13 12:00 - 13:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
ABSTRACT:
Despite ML models’ impressive performance, training and deploying them is currently a somewhat messy endeavor. But does it have to be? In this talk, I overview my work on making ML “predictably reliable”—enabling developers to know when their models will work, when they will fail, and why.
To begin, we use a case study of adversarial inputs to show that human intuition can be a poor predictor of how ML models operate. Motivated by this, we present a line of work that aims to develop a precise understanding of the ML pipeline, combining statistical tools with large-scale experiments to characterize the role of each individual design choice: from how to collect data, to what dataset to train on, to what learning algorithm to use.
ZOOM LINK (if unable to attend in-person): https://upenn.zoom.us/j/98699592762

Spring 2024 GRASP SFI: Joseph DelPreto, Massachusetts Institute of Technology, "Using Sensing and AI to Enrich Human Interactions with Machines and Nature"
2024-03-13 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom.
ABSTRACT
Coupling advanced wearable and environmental sensors with dynamic AI frameworks has the potential to transform how we engage with machines and with the natural world. By co-developing intelligent sensors and deployable machine learning pipelines, we can unlock the power of data to address impactful challenges in fields ranging from human-robot collaboration to environmental science. Realizing this vision will require a multifaceted approach including networks that extract insights from large streams of continuous data, algorithms that adapt to new subjects or environments from limited examples, unobtrusive sensing with embedded autonomy, scalable multimodal dataset curation, and paradigms for fluid human interactions with AI systems. Moving towards these goals, this talk will present approaches to creating more intelligent and fluid human-robot interactions by leveraging wearable sensors for brain, muscle, and motion activity combined with adaptive learning pipelines. It will explore how these techniques can scale to curate multimodal datasets of human behavior that aim to support foundational models of physical intelligence. To help improve sensing capabilities, it will also discuss techniques for creating soft wearable sensors with embedded learning pipelines. Finally, recent results of using wearable and deployable sensors to study non-human species will be introduced; combining robust wearable sensor tags, drones, and new machine learning pipelines can reveal exciting insights into the language and culture of sperm whales.

BE Doctoral Dissertation Defense: "Ionizable Lipid Nanoparticles for Solid Tumor Chimeric Antigen Receptor Immunotherapy" (Alvin Mukalel)
2024-03-13 15:00 - 17:00 | Auditorium, LRSM Building, 3231 Walnut Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Michael J. Mitchell are pleased to announce the Doctoral Dissertation Defense of Alvin Mukalel.

Title: Ionizable Lipid Nanoparticles for Solid Tumor Chimeric Antigen Receptor Immunotherapy
Date: March 13, 2024
Time: 3:00 PM
Location: LRSM Auditorium

The public is welcome to attend.
