Penn Engineering Events

BE Seminar: "Robust CRISPR/Cas-based epigenome editing technologies for precision human cell engineering and mechanistic dissection of pathological gene expression" (Isaac Hilton, Rice University)
2023-10-19 15:30 - 16:30 (America/New_York) | 216 Moore Building
Recent advances in CRISPR/Cas-based epigenome editing technologies have enabled programmable control over human gene expression, chromatin states, and genomic organization. Consequently, these emerging technologies have created new opportunities to engineer human cells for therapeutic benefit and catalyzed innovative ways to functionally interrogate gene regulatory mechanisms in situ. Toward these ends, we have recently developed new capabilities in the context of CRISPR/Cas-based transcriptional activation (CRISPRa) modalities. First, we have identified and repurposed key segments from natural human transcription factors to build potent and compact multipartite transactivation modules and in turn build the CRISPR-DREAM platform. CRISPR-DREAM is specific, robust across mammalian cell types, efficacious at diverse human regulatory elements, and well tolerated in therapeutically important primary cells – including T cells, MSCs, neurons, and iPSCs. We have also leveraged the small size and potency of CRISPR-DREAM components to generate all-in-one CRISPRa AAV systems that expand opportunities for in vivo gene control. Second, in unpublished studies, we have isolated intrinsically disordered regions (IDRs) from oncogenic fusion proteins associated with therapeutically intractable hematologic malignancies and nuclear phase separation. We find that different IDR compositions exhibit distinct propensities for nuclear import and biomolecular condensation in human cell nuclei. We demonstrate using precision CRISPR-based targeting of IDRs to human loci, that levels of phase separation can be directly proportional to target gene activation. Interestingly we also find that while core transcriptomic network changes are shared among certain oncogenic IDR fusion proteins, phase separation behaviors and genomic engagement occur in discrete ways – suggesting divergent IDR-driven routes to cellular oncogenesis, the control over which could create new possibilities for tailored therapeutic approaches.

PRECISE Seminar: "Co-Optimizing Imaging, Computer Systems, and Biological Perception for Next-Generation Visual Computing Platforms"
2023-10-20 10:00 - 11:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract
Emerging platforms such as Augmented Reality (AR), Virtual Reality (VR), and autonomous machines, while are of a computing nature, intimately interact with both the environment and humans. They must be built, from the ground up, with principled considerations of three main components: imaging, computer systems, and human perception. This talk will make a case for this tenet and discuss some of our recent work on this front.
I will first talk about in-sensor visual computing, the idea that co-designing the image sensor with the computer systems will significantly improve the overall system efficiency and, perhaps more importantly, unlock new machine capabilities. We will show a number of case studies in AR/VR and autonomous machines. I will then discuss our work on human-systems co-optimizations, where we computationally model biological (human) vision to build energy-efficient AR/VR devices without degrading, sometimes even enhancing, human perception.
If time permits, I will briefly discuss how we build fast and robust computing systems for autonomous machines, many of which are now deployed by a self-driving car start-up.

Fall 2023 GRASP on Robotics: Leslie Kaelbling, Massachusetts Institute of Technology, "Doing for our robots what nature did for us"
2023-10-20 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
We, as robot engineers, have to think hard about our role in the design of robots and how it interacts with learning, both in “the factory” (that is, at engineering time) and in “the wild” (that is, when the robot is delivered to a customer). I will share some general thoughts about strategies for robot software design that combine machine learning with insights from natural intelligence and from classical engineering design. I will describe several research projects, both in the design of an overall architecture for an intelligent robot and in strategies for learning to integrate new skills into the repertoire of an already competent robot.

BE Doctoral Dissertation Defense: "Uncovering Structure-function Relationships in Chromatin Architecture" (Daniel Emerson)
2023-10-20 13:00 - 15:00 | BRB 253
The Department of Bioengineering at the University of Pennsylvania and Dr. Jennifer Phillips-Cremins are pleased to announce the Doctoral Dissertation Defense of Daniel Emerson.

Title: Uncovering Structure-function Relationships in Chromatin Architecture

Date: October 20, 2023
Time: 1:00 PM
Location: BRB 0253

Zoom link

The Public is welcome to attend.

MEAM Seminar: "Granular and Photoelastic Avalanches"
2023-10-24 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Flowing granular materials arise everywhere around us, in industry from pharmaceutical processes to bulk good transport lines, and in nature from snow avalanches to captivating dune fields.
In landslides, we have an interesting interplay between microscale (grain-grain contacts) and macroscale processes (continuum behavior). In order to understand critical macroscale processes such as stability of a slope, creep and failure, we need to be able to visualize and characterize the microscale interactions.
In this talk, I will introduce a laboratory technique called photoelasticity to visualize grain-grain contacts in time and space. Collisions between grains create a fascinating network of so-called force chains, which are responsible for the inhomogeneous distribution of stresses in a granular medium. We discover stress distributions in 2D granular avalanches, visualized with bespoke, superior-quality birefringent photoelastic particles. This technique gives us for the first time access to the full velocity, density and stress fields inside of a dynamic avalanche, and allows us to experimentally validate granular rheological models.

ESE Fall Seminar - "Acceleration by Stepsize Hedging"
2023-10-24 11:00 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Can we accelerate convergence of gradient descent without changing the algorithm — just by optimizing stepsizes? Surprisingly, we show that the answer is yes. Our proposed Silver Stepsize Schedule optimizes strongly convex functions in $k^{log_p 2} = k^{0.7864}$ iterations, where $p=1+sqrt{2}$ is the silver ratio and $k$ is the condition number. This is intermediate between the textbook unaccelerated rate $k$ and the accelerated rate $sqrt{k}$ due to Nesterov in 1983. The non-strongly convex setting is conceptually identical, and we obtain an analogous accelerated rate $eps^{-log_p 2} = eps^{-0.7864}$. We conjecture and provide partial evidence that these rates are optimal among all possible stepsize schedules.
The Silver Stepsize Schedule is an explicit non-monotonic fractal. Why should such stepsizes help? The core intuition is “hedging” between individually suboptimal strategies — short steps and long steps — since bad cases for the former are good cases for the latter, and vice versa. Properly combining these stepsizes yields faster convergence due to the misalignment of worst-case functions. This talk is based on joint work with Pablo Parrilo that publishes and extends my 2018 Master’s Thesis — which established for the first time that judiciously chosen stepsizes can enable accelerated convex optimization. Prior to this thesis, the only such result was for the special case of quadratics, due to Young in 1953.

ASSET Seminar: "Towards a Design Flow for Verified AI-Based Autonomy" (Sajit A. Seshia, University of California, Berkeley)
2023-10-25 12:00 - 13:15 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
Verified artificial intelligence (AI) is the goal of designing AI-based systems that have strong, ideally provable, assurances of correctness with respect to formally specified requirements. This talk will review the main challenges to achieving Verified AI, and the initial progress the research community has made towards this goal. A particular focus will be on AI-based autonomous and semi-autonomous cyber-physical systems (CPS). Building on this initial progress, there is a need to develop a new generation of design automation techniques, rooted in formal methods, to enable and support the routine development of high assurance AI-based autonomy. I will describe our work on formal methods for Verified AI-based autonomy, implemented in the open-source Scenic and VerifAI toolkits. The use of these tools will be demonstrated in industrial case studies involving deep learning-based autonomy in ground and air vehicles

Fall 2023 GRASP SFI: Matthew D. Kvalheim, University of Maryland, Baltimore County, "Discovering engineering (im)possibilities with geometry and topology"
2023-10-25 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 on Zoom.
ABSTRACT
I will describe engineering (im)possibilities discovered with geometry or topology. These provide or revoke “hunting licenses” for the search of quantities of interest in three contexts: feedback control, applied Koopmanism, and deep neural network autoencoders.
Control-Lyapunov or barrier functions yield sufficient conditions for stability or safety to be achievable with feedback control, but cannot determine if this is not achievable. I will present user-friendly “tests” to determine this, along with ongoing work on sufficient conditions for periodic orbit stabilizability.
An open problem for Koopman methods has been to determine the class of dynamical systems that are globally linearizable in the sense of admitting an embedding into a linear system on a Euclidean space. I will present a solution for the case of linearizing compact invariant sets or attractor basins.
Topological obstructions dictate that autoencoders cannot provide nonlinear dimensionality reductions with small errors, and yet, the wide practical applicability of the method evidences remarkable empirical success. I will offer a resolution to this apparent paradox.
This is joint work with P. Arathoon, A. M. Bloch, D. E. Koditschek, and E. D. Sontag.

CBE Seminar: "Transformer-based Hybrid Modeling and Control of Evolving, Nonlinear Processes" (Kwon, Texas A&M University)
2023-10-25 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Traditionally, the dynamic modeling of chemical processes has relied on first-principles models grounded in fundamental physics and chemistry laws. These models, primarily formulated through differential equations with constant parameters, enable the calculation of control actions optimizing process operations, taking both process and actuator limitations into account. However, the ever-evolving and nonlinear nature of chemical processes frequently calls for models with time-varying parameters. Motivated by these challenges, we have developed hybrid models that integrate system-agnostic first-principles dynamics with system-specific data-driven, time-varying parameters. Our hybrid modeling framework incorporates a recent innovation: attention-based time-series transformers (TSTs) coupled with positional encoding. This marks a pioneering venture into applying the transformer algorithm – a cornerstone in ChatGPT’s triumph – to nonlinear, time-varying processes. By analyzing data across both current and preceding time steps, the TST captures both immediate and historical changes in process states, granting a contextual insight on process dynamics, mirroring ChatGPT’s textual context understanding. This TST-based hybrid model identifies correlations between process parameters and state variables. Its versatility is evident as it adapts to a spectrum of models – from density function theory to computational fluid dynamics -and scales, spanning from laboratory to extensive industrial environments. We will present applications of this hybrid modeling and control architecture, showcasing its utility from labs to industrial processes, made possible through partnerships with leading chemical process enterprises.

MSE OPEN HOUSE: "Photonics: From Probing Fundamental Physics to Enabling Computing at the Speed of Light” Liang Feng, University of Pennsylvania
2023-10-25 17:30 - 19:00 | LRSM Reading Room, 3231 Walnut St., Philadelphia, PA, 19104, United States

MSE Seminar: "Advanced Analytical Characterization of Next Generation Energy Storage Systems" - Nik Singh - Toyota Research Institute of North America
2023-10-26 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Advances in hybrid and electric vehicle technologies combined with a demand for green initiatives have recently motivated necessary diversification in energy storage research. To achieve customer expectations for hybrid and electric vehicles, new battery systems with higher energy densities, power densities and cycle life than the current state-of-art Lithium (Li)-ion battery are needed. Further, to achieve necessary standards for green initiatives for hybrid and electric vehicles, a closer examination of the processes and materials involved in battery systems is also critical. Examples of such Li-ion battery systems are those focused on the utilization of Silicon (Si) or Li metal as the anode, or the use of low-Cobalt (Co) or Co-free cathodes, or the move towards closed-loop battery ecosystems. However, the development of such systems is complicated at the fundamental level by process-driven impurities and chemical incompatibilities in current liquid battery systems.
Among additional strategies under consideration for energy storage diversification, the use of solid-state electrolytes (inclusive of polymers, gels and conducting ceramics) stands out since the implementation of solid-state electrolytes can also serve as a mechanical barrier towards Li dendrite formation (and hence potentially subdue thermal runaway events). However, solid-state electrolytes exhibit lower ionic conductivities and display poor interfacial stability towards higher energy Li metal anodes. While optimizations to overcome such intrinsic challenges in both liquid and solid-state battery materials continue, even less is known about the interfacial interactions between both types of electrolytes and anodes/cathodes. Since battery system interfaces eventually govern the performance of the battery, studies into understanding these interactions remains essential. Here, we present an overview of select studies undertaken for the interfacial interactions between various liquid and solid electrolytes under consideration for metal battery systems today. The studies cover interfacial observations, nucleation and growth of the metal anode and the chemo-mechanical transformations within electrolytes, and at their interfaces with metal anode materials. Tandem analytical ex-situ and in-situ studies via transmission electron microcopy (TEM) and X-ray absorption spectroscopy (XAS) can reveal the interfacial interactions and failure modes between metal anodes and commonly used liquid and solid battery electrolytes. The presented studies allow for comparisons of metal anode properties for each electrolyte material and stand to help clarify interfacial, morphological and failure evolution mechanisms during battery cycling from them. Further, we present the need for bridging length scales across multiple analytical techniques when analyzing energy storage system materials, to be able to better correlate model studies and commercial products.

PRECISE Seminar: Machines that Talk to the Brain and Think Like the Mind
2023-10-26 11:00 - 12:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract

Communicating with the brain enables us to advance our understanding of brain function, treat disorders, restore lost function, and when combined with artificial cognitive frameworks, can push the frontier of human capabilities. Key to realizing brain communication and replicating cognition are new computer architectures– systems that directly sense and stimulate the brain, and those capable of running complex cognitive frameworks. In this talk, I will present recent work on the first brain-computer interfacing platform, SCALO, that can sense, process and stimulate neural activity from multiple regions of the brain with millisecond latency and milliwatts of power. SCALO flexibly supports many neuroscientific applications, enabling for the first time, study of brain-wide behavior and diseases. I will also share how new quantum and classical platforms are needed to accelerate cognitive neuroscience modeling, and outline an end to end design that connects such platforms with brain interfaces.

PRECISE Seminar: "Communication and Sensing with Laser Light"
2023-10-27 10:00 - 11:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract

The physical properties of laser light make it a perfect medium for a plethora of applications. Examples include high-bandwidth data communication thanks to its fast modulation speed, efficient power delivery given its high energy density, and fine-grained human sensing and object tracking because of its nanometer-level wavelength. Despite its potential, laser light still faces numerous challenges in emergent mobile applications, given its high directionality, sensitivity to environmental dynamics, and constraints in laser hardware.
In this talk, I will describe our effort of realizing robust communication and sensing with laser light for mobile applications. I will begin with realizing robust air-water communication and sensing with laser light. The ability to communicate and sense across the air-water boundary is essential for efficient exploration and monitoring of the underwater world. I will present our systems to allow an aerial drone to communicate with and locate underwater robots. I will also introduce our latest work Lasertag that overcomes laser’s high directionality to enable laser tethering with highly mobile targets using portable hardware. Finally, I will overview our years-long endeavor of noninvasive glucose sensing with laser light and conclude with future work.

Fall 2023 GRASP on Robotics: Nick Gravish, University of California, San Diego, "Adaptive robots through reconfiguration, compliance, and contact"
2023-10-27 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
Recent advances in robot materials and algorithms have enabled new levels of adaptive and versatile behavior. In this talk I will describe my lab’s efforts to create robots, mechanisms, and control algorithms capable of adaptive behaviors in response to perturbations from the environment or body morphology. I will first describe how the modulation of material curvature can enable reconfigurable robot appendages and bodies, culminating in new modes of robot manipulation and locomotion. Next, I will describe our work on flapping wing actuation through bioinspired autonomous oscillators with adaptive and responsive dynamics. Lastly, I will describe how to design adaptive proprioceptive feedback laws which can enable robot groups to synchronize locomotion purely through contact interactions. In total this work illustrates how simple mechanisms and algorithms can give rise to a rich design space for dynamic and responsive robots.

ESE Fall Seminar - "Quantum sensing and imaging with diamond spins"
2023-10-27 11:00 - 12:00 | Berger Auditorium (Room 13), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
Solid state spin qubits, in particular the nitrogen vacancy (NV) center in diamond, offer a path towards truly nanoscale imaging of condensed matter and biological systems with sensitivity to single nuclear spins. Here I discuss our NV-based magnetic imaging experiments as applied to condensed matter systems, where we have imaged current flow patterns in graphene in order to reveal the transition from ohmic to electron-collision-dominated flow regimes. A grand challenge to improving the spatial resolution and magnetic sensitivity of the NV is mitigating surface-induced quantum decoherence, which I will discuss in the second part of this talk. Decoherence at interfaces is a universal problem that affects many quantum technologies, but the microscopic origins are as yet unclear. Our studies guide the ongoing development of quantum control and materials control, pushing towards the ultimate goal of NV-based single nuclear spin imaging.

PICS Colloquium: "Modeling Assembly of Colloids with Charges and with Mobile Binders"
2023-10-27 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
In this talk, I will present our recent efforts in probing the physical processes underlying self-assembly of colloidal gels and crystals. Nano-meter to micron sized particles in suspension can be a powerful platform for assembly novel functional materials, but the challenge is to design interactions such that desired functionality is achieved. Moreover, for practical purposes this must be done on a large scale. First, I will discuss our work on using particles with many mobile binding sites, where particles can ‘choose’ their number of neighbors by assembling adhesion patches between particles. Second, I will discuss nucleation and growth of crystals formed from pairs of charged colloidal particles in suspension.

MEAM Seminar: "Hardware / Controls Co-design to Overcome Challenges for Aerial Robots"
2023-10-31 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Aerial robotics have become ubiquitous, but (like most robots) they still struggle to operate at high speed in unstructured, cramped environments. By considering a vehicle’s mechanical design simultaneously with the design of controls and automation algorithms, we have more degrees of freedoms to find creative solutions to problems. In this talk I will present some of my group’s work on enhancing aerial robots, including purely algorithmic approaches (“how can I do more with the hardware I already have?”) and with hardware co-design (“how can I change the vehicle so that the hard problem is actually easy?”). Two challenges for aerial robots will motivate us: first: flight through narrow, unstructured environments, and second: long duration and range flight within the constraints of battery-electric power.
For flight through narrow environments, I will present an algorithmic approach for high speed path planning that incorporates perception uncertainty, and can be used on a standard drone. We will then present two alternative approaches that modify the system design: one a vehicle that can change its shape to fit through narrower spaces, and a second that is highly collision resilient, and for whom collisions are therefore neither mission- nor safety-critical.
For overcoming energetic challenges, we will present a strategy for real-time optimization of flight characteristics for a vehicle, specifically using extremum seeking control to modify the system airspeed and yaw angle; an algorithm that can be applied to any aerial robot. We then again show two design modifications to work around the problem — first, a morphing system that can reduce its drag area at speed, and secondly a system capable of mid-air battery replacement for indefinite flight.

CIS Seminar: "Modeling Atoms to Address Our Climate Crisis"
2023-10-31 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Climate change is a societal and political problem whose impact could be mitigated by technology. Underlying many of its technical challenges is a surprisingly simple yet challenging problem; modeling the interaction of atoms. In this talk, we motivate the problem and provide insights into how this opens up new intriguing directions for machine learning and AI researchers. Recent large-scale datasets released by the Open Catalyst Project enable the training of ML models that generalize across a broad range of the chemical space. Analogies are drawn to computer vision to map recent state-of-the-art approaches for atomic modeling to a more familiar domain. We conclude by exploring the numerous open problems and their potential for wide ranging impact beyond climate change.

ASSET Seminar: "Copyright, Machine Learning Research, and the Generative-AI Supply Chain" (A. Feder Cooper, Cornell University)
2023-11-01 12:00 - 13:15 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
“Does generative AI infringe copyright?” is an urgent question. It is also a difficult question, for two reasons. First, “generative AI” is not just one product from one company. It is a catch-all name for a massive ecosystem of loosely related technologies. These systems behave differently and raise different legal issues. Second, copyright law is notoriously complicated, and generative-AI systems manage to touch on a great many corners of it. They raise issues of authorship, similarity, direct and indirect liability, and fair use, among much else. These issues cannot be analyzed in isolation, because there are connections everywhere.
In this talk, I will discuss recent work that aims to bring order to the chaos. In a forthcoming law review article, Talkin’ ‘Bout AI Generation, my co-authors and I introduce the generative-AI supply chain: an interconnected set of stages that transform training data into generations. The supply chain reveals all of the places at which companies and users make choices that have copyright consequences. It enables us to trace the effects of upstream technical designs on downstream uses, and to assess who in these complicated sociotechnical systems bears responsibility for infringement when it happens. For examples of these complexities, I will also draw on joint work with MosaicML/Databricks that attempts to train a text-to-image generative model with openly licensed, Creative-Commons images. I will close with the key decisions that courts will need to make as they grapple with copyright issues, and point out the consequences that would likely flow from different liability regimes.
This talk reflects joint work with Katherine Lee, James Grimmelmann, and colleagues from MosaicML/Databricks.

Fall 2023 GRASP SFI: E. Farrell Helbling, Cornell University, “Autonomy for insect-scale robots”
2023-11-01 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 on Zoom.
ABSTRACT
Countless science fiction works have set our expectations for small, mobile, autonomous robots for use in a broad range of applications. The ability to move through highly dynamic and complex environments can expand capabilities in search and rescue operations and safety inspection tasks. These robots can also form a diverse collective to provide more flexibility than a multifunctional robot. Advances in multi-scale manufacturing and the proliferation of small electronic devices have paved the way to realizing this vision with centimeter-scale robots. However, there remain significant challenges in making these highly-articulated mechanical devices fully autonomous due to the severe mass and power constraints. My research takes a holistic approach to navigating the inherent tradeoffs in each component in terms of their size, mass, power, and computation requirements. In this talk I will present strategies for creating an autonomous vehicle, the RoboBee – an insect scale flapping-wing robot with unprecedented mass, power, and computation constraints. I will present my work on the analysis of control and power requirements for this vehicle, as well as results on the integration of onboard sensors. I also will discuss recent results that culminate nearly two decades of effort to create a power autonomous insect-scale vehicle. Lastly, I will outline how this design strategy can be readily applied to other micro and bioinspired autonomous robots.

CBE Seminar: "Structure-Independent Peptide Binder Design via Generative Language Models" (Chatterjee, Duke University)
2023-11-01 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The ability to modulate pathogenic proteins represents a powerful treatment strategy for diseases. Unfortunately, many proteins are considered “undruggable” by small molecules, and are often intrinsically disordered, precluding the usage of structure-based tools for binder design. To address these challenges, we have developed a suite of algorithms that enable the design of target-specific peptides via protein language model embeddings, without the requirement of 3D structures. First, we train a model, SaLT&PepPR, that leverages ESM-2 embeddings to efficiently select high-affinity peptides from natural protein interaction interfaces. Next, we develop a generator-discriminator model, PepPrCLIP, based on the CLIP architecture, to generate and screen de novo peptides with selectivity to a specified target protein. As input to the discriminator, we create a Gaussian diffusion generator to sample an ESM-2 based latent space, fine-tuned on experimentally-valid peptide sequences. Finally, to enable target-conditioned de novo generation of binding peptides, we train a masked language model, PepMLM to discontinuously unmask peptides given target sequences. Our final model demonstrates low perplexities across both existing and generated peptide sequences. We experimentally fuse model-derived peptides to E3 ubiquitin ligase domains and reliably identify candidates exhibiting functionally potent degradation of undruggable, disordered targets in cancer models. Overall, our work enables generation of programmable modulators to any target protein, without the requirement of conformationally stable three-dimensional structures.

MSE Seminar: "Nonlinear and Topological Quantum Photonics" University of Central Florida
2023-11-02 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
In this talk we will discuss how to engineer the dispersion relation of photonic platforms to provide robust propagation of classical and quantum states of light.
In the first part of this talk, we will unveil how to leverage the interaction of nonlinearity with higher orders of dispersion to create novel types of solitons, wave packets that propagate unperturbed for long distances. These objects have advantageous energy-width scaling laws with respect to conventional nonlinear Schrodinger solitons and show promise for applications in ultrafast lasers and integrated frequency combs.
Subsequently, we will cover recent developments in topological quantum photonics. Topological photonics studies topological phases of light and leverages the appearance of robust topological edge states. We will emphasize our experimental demonstration of nonlinearly generated and topologically protected photon pairs and path-entangled biphoton states in silicon waveguide arrays. Further, we will detail our latest experiments demonstrating entanglement between topologically distinct modes, highlighting topology as an entanglement degree of freedom.

Fall 2023 GRASP on Robotics: Julie Shah, Massachusetts Institute of Technology, "Effective Human-Machine Partnerships in High Stakes Settings"
2023-11-03 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a HYRBID event with a VIRTUAL SPEAKER. The GRASP on Robotics Seminar will be streamed for in-person attendees in Wu and Chen and virtual attendees may join the talk via Zoom.
ABSTRACT
Every team has top performers — people who excel at working in a team to find the right solutions in complex, difficult situations. These top performers include nurses who run hospital floors, emergency response teams, air traffic controllers, and factory line supervisors. While they may outperform the most sophisticated optimization and scheduling algorithms, they cannot often tell us how they do it. Similarly, even when a machine can do the job better than most of us, it can’t explain how. The result is often an either/or choice between human and machine. In this talk I share the Situational Awareness Framework for Explainable AI (SAFE-AI), and discuss the ways in which traditional XAI methods can promote or undermine human situation awareness. I also share our lab’s latest research in employing the framework to effectively blend the unique decision-making strengths of humans and LLM- and RL-enabled machines.

PICS Colloquium: "Micro-organism Locomotion in Viscoelastic Fluids"
2023-11-03 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Many microorganisms and cells function in complex (non-Newtonian) fluids, which are mixtures of different materials that exhibit both viscous and elastic stresses. For example, mammalian sperm swim through cervical mucus on their journey through the female reproductive tract, and they must penetrate the viscoelastic gel outside the ovum to fertilize. In micro-scale swimming the dynamics emerge from the coupled interactions between the complex rheology of the surrounding media and the passive and active body dynamics of the swimmer. We use computational and analytical models of swimmers in viscoelastic fluids to investigate and provide mechanistic explanations for emergent swimming behaviors. I will discuss a few examples that highlight the role of fluid elasticity in micro-organism locomotion.

MEAM Seminar: "Advancing the Versatility of Legged Robots and Assistive Devices"
2023-11-07 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Recent years have witnessed tremendous growth in the capabilities of legged robots, with quadrupeds and humanoids demonstrating athletic behaviors that even five years ago were out of reach. Likewise, actively powered lower-limb assistive devices have made great strides in their maturity, with hardware such as the Open-Source Leg broadening access for future breakthroughs.
Despite this progress, the wide variability of real-world environments and users remains a pressing challenge to practical applications. It is fundamentally impossible to train our robots in the lab for anything they may encounter in an open world! As steps toward addressing this challenge, the talk will first discuss recent work on the control of the MIT Mini Cheetah, which considers new computational methods for the robot to reason through its actions on the fly in complex environments. The second part of the talk will then present ongoing research on improving user interfaces for lower-extremity prosthetic limbs to make human/robot interaction more fluid. Collectively, this work expands the ability of these systems to tailor their motions to new environments and users, paving the way for broader adoption in the “wild.”

BE Doctoral Dissertation Defense: "Physiologically Induced High Gaussian Curvature Drives Nuclear Lamina Rupture and Cytoskeletal Displacement—Contributing to Downstream Dysfunction" (Michael Tobin)
2023-11-07 10:00 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Dennis Discher are pleased to announce the Doctoral Dissertation Defense of Michael Tobin.

Title: Physiologically Induced High Gaussian Curvature Drives Nuclear Lamina Rupture and Cytoskeletal Displacement—Contributing to Downstream Dysfunction

Date: Tuesday, November 7, 2023
Time: 10AM
Location: Glandt Forum at the Singh Center.

There is a zoom option for virtual listeners.

Topic: Michael Tobin Thesis Defense
Time: Nov 7, 2023 10:00 AM Eastern Time (US and Canada)

Join Zoom Meeting
https://upenn.zoom.us/j/93613731189?pwd=[REDACTED]
Meeting ID: 936 1373 1189
Passcode: [REDACTED]

The public is welcome to attend.

BE Doctoral Dissertation Defense: "Reversing Engineering the Anesthetic State: Insights from Behavior and CNS Circuit Cracking" (Andrzej Wasilczuk)
2023-11-07 13:30 - 14:30 | Jordan Medical Education Center, Room 505EW, 3400 Civic Center Blvd
The Department of Bioengineering at the University of Pennsylvania and Dr. Max Kelz are pleased to announce the Doctoral Dissertation Defense of Andrzej Wasilczuk
Reversing Engineering the Anesthetic State: Insights from Behavior and CNS Circuit Cracking
November 7th, 1:30-2:30pm
Jordan Medical Education Center, Room 505EW
3400 Civic Center Blvd
Philadelphia, PA 19104
A hybrid option is available using this link:
https://pennmedicine.zoom.us/j/94632129951?pwd=[REDACTED]
Meeting ID: 946 3212 9951
Passcode: [REDACTED]

ASSET Seminar: "The Future of Algorithm Auditing is Sociotechnical" (Danaë Metaxa, Penn)
2023-11-08 12:00 - 13:15 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
Algorithm audits are powerful tools for studying black-box systems without direct knowledge of those systems’ inner workings. While they have been effectively deployed to identify harms and biases in algorithmic content, algorithm audits’ narrow focus on technical components stop short of considering users themselves as integral and dynamic parts of the system, to be audited alongside its algorithmic components.
After an overview of the state of the art in algorithm auditing, this talk will introduce sociotechnical auditing: evaluating algorithmic systems at the sociotechnical level, focusing on the interplay between algorithms and users as each impacts the other over time. I will also present Intervenr, a platform we developed to conduct browser-based, longitudinal sociotechnical audits, and a case study in which we deployed Intervenr to investigate the central claim of online targeted advertising systems: that targeted ads perform better with users. Finally, I will conclude by discussing some of my group’s current work, expanding the auditing method to novices and youth, and developing post-auditing tools for collective action.

Fall 2023 GRASP SFI: Margaret Coad, University of Notre Dame, "Soft and Continuum Robots for Unstructured Environments"
2023-11-08 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 on Zoom.
ABSTRACT
Soft and continuum robots have immense potential to assist humans with tasks that require navigation and manipulation in unstructured environments. In this talk, I present my group’s research on the design, modeling, and control of a variety of soft and continuum robots. I begin by discussing soft vine-inspired robots, which move through their environment by extending from their tip and are well suited for navigation and manipulation within confined spaces. In particular, I discuss our research on vine robot field deployment, shape sensing, force sensing, and collapse modeling. I then present our research on two other bioinspired robots: spider monkey tail-inspired robots for grasping objects, and amoeba-inspired robots for navigation in confined spaces. Finally, I discuss our research on soft wearable robots for replacing or assisting the motion of the upper limbs. This research helps make robots more capable of assisting humans in the unstructured environments of everyday life.

ESE Fall Seminar - "Approximate symmetries in machine learning"
2023-11-09 11:00 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
In this talk, we explain different roles that symmetries and approximate symmetries can play in machine learning models. We define approximately equivariant graph neural networks and we show a bias-variance tradeoff when selecting the symmetries to enforce. We explain how to see equivariant functions as gradients of invariant functions, and we show how to use these ideas in self-supervised learning.
