ASSET Seminar: "Control with Coarse Measurements: Perception Contracts and Indistinguishable Sets"
2024-11-20 12:00 - 13:15 (America/New_York) | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Abstract:
Performance of control systems depend on the nature of available measurements. Perception of edges, keypoints, landmarks and other natural semantic features make certain coarse measurements available to control systems operating in complex environments. This talk explores two problems related to control and estimation with such coarse measurements. First, I will introduce perception contracts—an approach for analyzing visual control systems that rely on Deep Neural Networks for state estimation. A perception contract provides an over-approximation of a state estimator while guaranteeing closed-loop system invariants. These contracts can be automatically synthesized using data and model-based analysis and have been applied to automated landing and lane-keeping systems. The second part of the talk will focus on algorithms for computing indistinguishable sets—sets of states that cannot be distinguished based on available coarse measurements. These sets help define the limits of state estimation and localization. The talk will touch on formal verification, information spaces, and related open problems.
Zoom Link (if unable to attend in-person): https://upenn.zoom.us/j/91934138074

CIS Special Industry Colloquium: "Scaling Paradigms for Large Language Models"
2024-11-20 13:45 - 15:15 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
In this talk I will tell you how scaling has been the engine of progress in AI for the past five years. In the first scaling paradigm, our field scaled large language models by training with more compute on more data. Such scaling led to the success of ChatGPT and other AI chat engines, which were surprisingly capable and general purpose. With the release of OpenAI o1, we are at the beginning of a new paradigm where we do not just scale training time compute, but we also scale test-time compute. These new models are trained via reinforcement learning on chain-of-thought reasoning, and by thinking harder for more-challenging tasks can solve even competition-level math and programming problems. I will conclude with a few remarks on how AI research culture has changed and where the field might go next.

For more information please contact: Mayur Naik (mhnaik@seas.upenn.edu)

GRASP Special Panel featuring the 2024 John Scott Award Recipients
2024-11-20 14:00 - 15:00
This is an in-person event only and is not open to the public. Event Registration and Penncards are required. A link to register for the event will be sent via email.
PANEL DISCUSSION
Please join us for a panel discussion featuring the 2024 John Scott Award Recipients, Dr. Takeo Kanade (CMU), Dr. Vijay Kumar (Penn), & Dr. Daniela Rus (MIT). This panel will be moderated by Dr. Daniel E. Koditschek, GRASP Faculty Member and Penn Engineering’s Alfred Fitler Moore Professor.

CBE Seminar: "Scalable Access to the Hidden Topologies of Biology" (Albert Keung, North Carolina State University)
2024-11-20 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
Biology is characterized by a diversity of phenotypes and functions that outpace the limited molecular diversity encoded in genomes. How this is achieved is a fundamental and enduring mystery of the cell. It is clear that networks defining how biological molecules interact can drive diverse and complex phenotypes, but the intermolecular interactions or edges of these networks are highly multidimensional and difficult to measure at scale. The predictive power of models depends not only on the identities of components and their edges, but on complex properties of those edges ranging from intermolecular specificities, quantitative binding affinities, rate constants for enzymatic reactions, the influence of post-translational modifications, cross-talk between components, and the spatiotemporal organization and dynamics of network components and activities. This talk will describe the development of scalable synthetic biology platforms to comprehensively map these edge properties of protein networks, applied to the human epigenome. We will also describe how these principles need to be considered and engineered in completely abiotic applications that leverage biomolecules; specifically, we will describe the engineering of extremely dense digital information storage and computing systems with DNA as the information medium. We will also touch on how these principles translate upward in spatial scale to biomedical applications in neurological disorders such as Angelman Syndrome and in the engineering of human cerebral organoid models of the developing brain.

Fall 2024 GRASP SFI: Gioele Zardini, Massachusetts Institute of Technology, “Compositional Design of Complex Systems: From Autonomy to Future Mobility”
2024-11-20 15:30 - 16:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This seminar will start at 3:30 PM instead of 3:00. This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom.
ABSTRACT
When designing complex systems, we need to consider multiple trade-offs at various abstraction levels and scales, and choices of single components need to be studied jointly. For instance, the design of future mobility solutions (e.g., autonomous vehicles, micromobility) and the design of the mobility systems they enable are closely coupled. Indeed, knowledge about the intended service of novel mobility solutions would impact their design and deployment process, while insights about their technological development could significantly affect transportation management policies. Optimally co-designing sociotechnical systems is a complex task for at least two reasons. On one hand, the co-design of interconnected systems (e.g., large networks of cyber-physical systems) involves the simultaneous choice of components arising from heterogeneous natures (e.g., hardware vs. software parts) and fields, while satisfying systemic constraints and accounting for multiple objectives. On the other hand, components are connected via collaborative and conflicting interactions between different stakeholders (e.g., within an intermodal mobility system). In this talk, I will present a framework to co-design complex systems, leveraging a monotone theory of co-design and tools from game theory. The framework will be instantiated in the task of designing future mobility systems, all the way from the policies that a city can design, to the autonomy of vehicles as part of an autonomous mobility-on-demand service. Through various case studies, I will show how the proposed approaches allow one to efficiently answer heterogeneous questions, unifying different modeling techniques and promoting interdisciplinarity, modularity, and compositionality. I will then discuss open challenges for compositional systems design optimization, and present my agenda to tackle them.

MEAM Ph.D. Thesis Defense: "Tribosintering of Metal Oxide Nanocrystals"
2024-11-21 09:00 - 10:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Machinery relies on lubrication to regulate friction and wear at contacting interfaces. As lubricants become less viscous to save energy and cost, and as new technologies like electric vehicles operate in harsher conditions, the risk of surface-initiated failure grows. We show that metal oxide nanocrystals (NCs) dispersed in lubricants form protective coatings, or tribofilms, in situ at contacting interfaces via tribosintering. Compared to state-of-the-art antiwear additives and surface coatings, metal oxide tribofilms have several advantages, but the lack of fundamental knowledge about the growth and wear processes of these tribofilms is a key factor hindering adoption of NCs in lubricants. We reveal mechanisms behind metal oxide tribofilm formation through macro-scale, application-relevant experiments.
We use a benchtop tribometer capable of commercially relevant conditions — the mini-traction machine (MTM) with spacer layer imaging (SLIM) — to refine experimental study of metal oxide tribofilm formation. First, we consider the nanocrystals as anti-wear additives, demonstrating that the SLIM technique captures and quantifies local wear events during tribofilm growth. The competition wear and growth can be tuned by, e.g., the addition of S- and P-based co-additives, which increase the initial rate of tribofilm growth while contributing to a more polished steady-state tribofilm morphology. We then use the nanocrystals to form in situ metal oxide surface coatings at low homologous temperatures in a variety of realistic conditions. We show that ZrO2, TiO2, and BaTiO3 all form durable, anti-scuffing coatings near room temperature, offering robust practical benefits. We then generalize an under-appreciated feature of SLIM, disaggregating tribofilm thickness measurements to correlate pixels of data with local contact stress and contact time in contact. Local tribofilm thickness variations at a given time are best explained by differences in exposure to interfacial sliding, not differing contact stresses — an unacknowledged driver of tribosintering. We then show that a property-dependent critical length scale explains the differing wear behavior of ZrO2 and TiO2 tribofilms, providing a physically motivated design criterion for application. Finally, we discuss data-driven efforts to model tribofilm formation, demonstration unique benefits including correction of corrupted data, and a process to iteratively test analytical models.

THIS EVENT HAS BEEN CANCELLED: ESE Fall Seminar - "A changing grid powered by the new generations of power conversion, control, and energy management"
2024-11-21 10:30 - 11:30 | Towne 337
The electric grid is undergoing a transformative paradigm shift, driven by sweeping changes in generation, demand, and energy storage. By 2035, solar PV alone is expected to supply 40% of U.S. electricity, with substantial additional contributions from wind, geothermal, and hydroelectric sources—creating a renewable-dominant energy landscape. Meanwhile, electricity demand is accelerating due to rapid growth in electric vehicle (EV) charging, data centers, industrial manufacturing, and universal electrification across sectors. By 2050, EV charging is anticipated to represent 23% of the nation’s electricity demand. Energy storage system installations are also expanding to manage the variability of renewable sources, support dynamic loads, and ensure grid stability.
This seminar will discuss the pivotal role of high power, high voltage, and high frequency power converters in creating a flexible, efficient, and resilient grid. We will examine integration challenges for 15kV-class converters within the AC grid, as well as the opportunities these converters present for real-time voltage stabilization, frequency regulation, and dynamic grid management. High-bandwidth converters are key enablers of a smart, adaptable grid, facilitating higher renewable penetration, dynamic load management, and enhanced compatibility with energy storage. A few projects on grid-connected power electronics will highlight how these advancements can drive the evolution of a robust and versatile grid architecture to meet the demands of a power electronics-driven energy future.

MSE Seminar: "Nano to Mesoscale: Structure, Composition, and Transport Processes in Human Dental Enamel"
2024-11-21 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Mineralized tissues are paradigmatic hierarchical materials that reap synergy from structural and compositional gradients at multiple length scales in ways that are challenging to reproduce by conventional means. My laboratory studies the formation, functional properties, and degradation of mineralized tissues. We use model systems ranging from single crystalline endoskeletal elements deposited by single cells to the formation of dental tissues that comprise nanocrystalline and amorphous minerals deposited in complex organic matrices. Applications include the development of bio-inspired materials, sequestration of 90 Sr from nuclear waste, and improving prophylaxis and minimally invasive intervention in dental care.
Herein, I will focus on dental tissues that are optimized to withstand the forces of mastication and the challenging chemical environment of the oral cavity. Human dental enamel is composed of hydroxylapatite (Ca 5 (PO 4 ) 3 OH) nanocrystallites, thousands of which are bundled into rods that are organized in a three-dimensional weave; this provides great fracture resistance and a much-enhanced fatigue life but leaves our teeth vulnerable to erosive tooth wear and tooth decay (caries). I will discuss how chemical imaging using UV-laser pulsed atom probe tomography (APT), electron microscopy, and synchrotron X-ray techniques has provided deep new insights into the chemistry of nanoscale organic/inorganic interfaces, presence of amorphous intergranular phases, and complex dopant gradients that are integral to properties of teeth and their resistance to corrosion.[1-5] I will further report on development of correlative elemental imaging using X-ray diffraction at the mesoscale (here: 0.25-20 µm) that allows us to extend the field of view beyond what APT can deliver.[6] Finally, I will provide an update on our investigation of diffusive transport processes in enamel using APT and ToF-SIMS, and discuss my vision for integrating this information to enable predictive modeling of enamel dissolution.
[1] Gordon and Joester, Nature 2011, 469, 194-197. [2] Gordon, Tran, and Joester, ACS nano 2012, 6, 10667-10675. [3] Gordon, Cohen, MacRenaris, Pasteris, Seda, and Joester, Science 2015, 347, 746-750. [4] Gordon, Joester, Front Physiol 2015, 6. [5] DeRocher, Smeets, Goodge, Zachman, Balachandran, Stegbauer, Cohen, Gordon, Rondinelli, Kourkoutis, Joester, D. Nature 2020, 583, 66-71. [6] Free, DeRocher, Cooley, Xu, Stock, and Joester, Proc Natl Acad Sci USA 2022, 119, e2211285119.
This work was in part supported by: NIH-NIDCR R03 DE025303-01 and R01 DE025702-01; NSF DMR-1508399 and DMR-1539918; and DOE DE-AC02-06CH11357.

BE Seminar: "Making Every Penny Count: Copper Conducted Kinase Signaling & Metabolism in Cancer"
2024-11-21 15:30 - 16:30 | 216 Moore Building
This seminar will be held in Moore 216 and remotely via zoom (check email for zoom link). Light refreshments will be served.

Fall 2024 GRASP on Robotics: Robert Katzschmann, ETH Zürich, "Building Life-like Robots: From Musculoskeletal Designs to Biohybrid Innovations"
2024-11-22 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom.
ABSTRACT
Nature’s musculoskeletal design can inspire both artificial and living robots to create systems that can better interact within our unstructured world. There is value in rethinking how we design and control robots by replacing traditional designs centred around electromagnetic motors and gearboxes with a bio-inspired approach that uses contractive muscles, ligaments, tendons, and skeletons. Taking it even a step further, living robots represent the next frontier in engineering materials for robotic systems, incorporating biological living cells and synthetic materials into their design. These bio-hybrid robots are dynamic and intelligent, potentially harnessing living matter’s capabilities, such as growth, regeneration, morphing, biodegradation, and environmental adaptation. Such attributes position bio-hybrid devices as a transformative force in robotics development, promising enhanced dexterity, adaptive behaviours, sustainable production, robust performance, and environmental stewardship. In this talk, we will explore recent advances in artificial electrohydraulic musculoskeletal robots, which employ electrohydraulic actuators to produce lifelike muscle contractions and adaptive motions, as demonstrated in our recent work published in Nature Communications. We will also dive deeper into our breakthroughs in vision-controlled inkjet printing for robotics from our Nature and xolographic biofabrication techniques, which enabled our biohybrid swimmers presented at RoboSoft. Additionally, we will discuss the computational optimisation of musculoskeletal robotic hands from our recent work presented at Humanoids. The talk will showcase how musculoskeletal, bio-hybrid, and computational techniques open new frontiers in robotics interaction and manipulation.

ESE PhD Thesis Defense: "A Dynamical Systems Perspective on Optimization Algorithms"
2024-11-22 12:00 - 13:30 | Zoom – Meeting ID: 946 6798 0381
The intersection of machine learning (ML) and dynamical systems and control (S&C) has become a prominent area of research in recent years. While most work applies ML to S&C problems, this dissertation explores the reverse direction: using S&C tools to address challenges in ML and optimization. This thesis is comprised of three parts:
In part I, we examine connections between continuous-time dynamics and iterative optimization algorithms. Motivated by the matching rates observed by various optimization algorithms and their continuous-time counterparts, we seek to gain a better understanding of the fundamental limits behind these matching rates. First, we show that a simple rescaling of the gradient flow achieves finite-time stability, which is clearly not preserved by its simplest discretization — the Forward Euler discretization — as it simply yields gradient descent. In fact, this property is not exactly preserved by any explicit discretization as it relies on instantaneous corrections in the speed of the trajectories of the system, which is not possible in discrete-time due to overshooting. Next, we show that the rate of any continuous-time optimization system can be approximately preserved, under sufficient regularity conditions, by any sufficiently high order off-the-shelf ODE solver.
In part II, we re-examine the relationship between convexity and smoothness and the role they play on the convergence rate of gradient-based optimization algorithms. Using and extending tools from part I, we show that a rescaled form of gradient descent achieves a rate that explicitly depends on given lower and upper bounds on the Bregman divergence of the cost function, which collectively quantify convexity and smoothness. In particular, we establish linear convergence with a generalized condition number, generalizing the case of L-smooth and mu-strongly convex functions minimized via gradient descent.
In part III, we discuss applications of S&C in two ML problems. The first is to re-examine the convergence of the expectation-maximization (EM) algorithm with a prior using Lyapunov stability theory. Next, we consider the conformal training (ConfTr) method of Stutz et al (2022) and show that, in its current form, suffers from severe sample inefficiency. We propose a simple fix and provide a preliminary theoretical analysis using tools from linear systems theory. We also use the principles established in part II to guide the training procedure.

Innovative Approaches in Data-Driven Chemistry and Reaction Optimization
2024-11-22 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Research in the Zahrt group focuses on creating new tools to advance organic synthesis by integrating automation and machine learning workflows to enhance molecular function, reaction efficiency, and sustainability. We develop and use active learning strategies for catalyst design, reaction conditions, and other molecular properties. To accelerate the implementation of these algorithms, we pair them with automated experimentation platforms. Applications of these approaches include the exploration of higher order solvent mixtures as a new optimization domain in organic chemistry, a new algorithmic approach to catalysts design paired with on-demand catalyst synthesis, and automated design and synthesis of biologically active molecules, and the exploration of the new synthetic methodology. Current methodology exploration includes innovations in the cation flow technology, using engineering solutions to overcome chemical incompatibilities to achieve one-pot transformations that would not typically be viable through other means.

ESE PhD Thesis Defense: "Software-like Incremental Refinement on FPGA using Partial Reconfiguration"
2024-11-26 11:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
To improve FPGA design productivity, our goal is to create a development experience for FPGAs that aligns closely with widely accepted software design principles. Software programmers quickly test their minimally completed design, identify the bottleneck, and incrementally refine the design. In FPGA design, however, such incremental refinement is not currently supported. (1) FPGA compilation is long, (2) a minor refinement leads to another long compilation, and (3) FPGA developers cannot easily identify a bottleneck of the design to know where to focus optimization effort to improve the application execution time. We introduce a divide-and-conquer strategy in FPGA compilation, proposing a fast separate FPGA compilation using a Network-on-Chip (NoC) and Partial Reconfiguration (PR). Building upon this separate compilation framework, in this thesis, we take the next step to support variable-sized pages using Hierarchical PR to provide flexibility to the users. With variable-sized pages, users can quickly test the design on the hardware, just like software programmers start from a barely functional design. In addition, we propose a bottleneck identification scheme based on FIFO counters to provide profiling capability in FPGA design. Finally, we introduce a fast incremental refinement strategy that integrates our fast compilation framework and bottleneck identification scheme. The idea is to quickly map the design on the FPGA using the fast compilation framework and incrementally refine the design based on our bottleneck identification. The fast compilation with the NoC and PR pages iterates many initial yet important design points quickly, and for the final, optimized design, our strategy migrates to the monolithic system that does not have the area and bandwidth overhead of the NoC. Throughout the design tuning, we always have a hardware-mapped design whose performance we can measure to provide feedback to the users or automation script to identify the next bottleneck. We evaluate our fast incremental strategy with design tuning for realistic High Level Synthesis applications. Our framework, fully compatible with AMD Vitis, achieves 1.3–2.7× faster tuning time than a monolithic flow where the vendor tool monolithically compiles each design point.

MSE Doctoral Dissertation Defense: "Polymer Infiltrated Nanoporous Gold: Kinetics and Optical Properties of Novel Polymer Nanocomposites" (Weiwei Kong)
2024-12-02 11:30 - 13:30 | LRSM Reading Room, 3231 Walnut St., Philadelphia, PA, 19104, United States
Abstract: One of the biggest challenges in the field of polymer nanocomposites (PNCs) is to disperse high nanofiller loadings into the polymeric matrix. The high loading and uniform dispersion are limited by the unfavored polymer/nanofiller thermodynamics and the tendency for nanofiller to aggregate. In this thesis, these are circumvented by using nanoporous gold (NPG) as a scaffold for polymers to fill. The ultra high loading (>50 vol%) is achieved by infiltrating polymer melts into NPG to produce a polymer infiltrated nanoporous gold (PING) composite . This novel composite provides promise for the next generation of advanced materials for coating, optical sensors, actuators, and batteries.
This thesis contributes to our understanding of polymer kinetics under moderate confinement by varying the interfacial energy between polymer and pore wall, and investigating the temperature dependence of infiltration. The confinement ratio in this thesis is defined by Γ = Rg/Rp. For polystyrene (PS) infiltrating into the NPG (Γ = 0.47 – 0.77), a weakly attractive interaction, the infiltration time scales with molecular weight (Mw) as ???? ~ Mw1.30, weaker than bulk predictions. Moreover, PS infiltration is much faster compared to the bulk behavior because confinement reduces the number of entanglement and the effective polymer-wall friction decreases as Mw decreases. For poly(2-vinylpyridine) (P2VP) infiltration into the NPG (Γ = 0.18 – 0.78), a strongly attractive interaction, infiltration time also exhibits a weak dependence as ???? ~ Mw1.43. However, compared at similar conditions, P2VP infiltration is slower than PS which is attributed to the formation of a physisorbed layer during P2VP infiltration, which is supported by the MD simulations. Lastly, the temperature dependence of P2VP:NPG infiltration at moderately confined (Γ = 0.55) conditions follows the bulk WLF behavior, while more confined P2VP (Γ = 0.97) exhibits a weaker temperature dependence than predicted by WLF. This deviation is attributed to a confinement induced reduction in thermal expansion coefficient. Those fundamental studies on polymer kinetics enable the optimization of preparing PING composites so they can be used for previously mentioned applications.
The optical response of the NPG during polymer infiltration is studied using UV-Vis spectroscopy. As the dielectric constant of the gold nanopores increases during filling, the absorbance spectra intensity increases and the plasmon peak undergoes a red shift. The extent of infiltration measured by the evolution of the absorbance spectra is in good agreement with in-situ ellipsometry measurements. In Discrete Dipole Approximation (DDA) simulations are used to model the absorbance spectra at various stages of annealing time. Importantly, a “T” shaped gold structure is found to better represent the plasmonic absorption of the NPG ligaments compared to a nanorod used in a prior study. These optical absorption studies demonstrate that UV-Vis is a facile method for studying polymer infiltration in metal scaffolds.
This thesis advances the understanding of polymer infiltration kinetics for polymers that weakly and strongly attract to the pore walls, and show that confinement reduces thermal expansion of the polymer. To complement ellipsometry, a new approach is presented to follow polymer infiltration using UV-vis spectroscopy. These advancements enable scientists to better understand polymers under confinement and advance the tool box for creating interconnected polymer/filler systems at high filler concentrations.

CBE Doctoral Dissertation Defense: "Utilization of Atomic Layer Deposition for Heterogeneous Catalysis in Biomass Upgrading Applications" (Mengjie Fan)
2024-12-02 13:30 - 15:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Abstract:
The need for sustainable energy sources has intensified interest in biomass upgrading, where biomass-derived feedstocks are transformed into fuels and valuable chemicals. A major challenge in biomass upgrading is the development of highly active, selective, and stable catalysts for complex reactions. Traditional synthesis methods often result in heterogeneous catalysts with poor dispersion of active sites, limiting their efficiency. This thesis explores the use of Atomic Layer Deposition (ALD) as a precise technique for synthesizing catalysts with controlled composition and uniform structure, aimed at understanding correlation between structure and reactivity as well as improving catalyst performance in biomass upgrading applications.
To investigate this, I studied a few biomass upgrading reactions by depositing metal oxides and metals on various support materials by ALD. The formation of uniform thin films or highly dispersed particles with ALD was confirmed by XRD, TEM, and FTIR. Catalytic performance was evaluated for biomass upgrading reactions in flow reactor and TPD system. Our results demonstrated that ALD was capable of producing catalysts with well-defined structure, thus enhanced selectivity and stability compared to those produced by conventional methods. This research highlights the effectiveness of ALD in producing single-site and highly dispersed catalysts that improve biomass upgrading efficiency. By enabling precise control over catalyst structure and composition, ALD presents a promising approach for advancing sustainable catalytic processes in renewable energy applications. Future work will explore further optimization of ALD conditions to enhance the scalability and economic feasibility of ALD-synthesized catalysts in industrial biomass conversion.

MEAM Seminar: "Differentiable Algorithms for Non-differentiable Robotics: Dexterous Manipulation via Implicit Learning and Control"
2024-12-03 10:15 - 11:15 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
As we ask our robotic systems to become more capable, with the ultimate aim of deploying robots into complex and ever-changing scenarios, the vast space of potential tasks drives the need for flexibility and generalization. For all the promise of big-data machine learning, what will happen when robots deploy to our homes and workplaces and inevitably encounter new objects, new tasks, and new environments? A core challenge in generalizable robotics lies in the making and breaking of contact, where non-smooth dynamics clashes with typical assumptions in gradient-based optimization and learning. With the goal of rapid adaptation to novel settings, I’ll discuss our progress on real-time multi-contact MPC for dexterous manipulation, where we can realize dynamic motions which dynamically and intelligently make and break contact, with only a simple goal as the given objective. Control, however, requires a model, and so I will present our recent results on contact-inspired implicit model learning learning, where, by embedding convex optimization, we reshape the loss landscape and enable more accurate training, better generalization, and ultimately data efficiency. Lastly, given time, I’ll discuss how model learning and control can synergize in interesting ways: via online adaptation or by synthesizing task-relevant models which identify key aspects of multi-contact dynamics necessary to achieve a goal.

Fall 2024 GRASP Seminar: Anand Bhattad, Toyota Technological Institute at Chicago, "Are Generative Image Models Physically Grounded?"
2024-12-03 12:00 - 13:00 | 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 as well as virtually via Zoom.
ABSTRACT
Computer vision has transformed from simple edge detection in the 1980s to modern generative models that generate uncannily realistic images: objects are in sensible places, lighting seems realistic, and textures appear accurate. But how do they achieve this understanding of our visual world?
Probing their internal representations reveals that these models encode fundamental aspects of physical reality. Within these models, we discovered classical computer vision concepts like intrinsic images — decomposing scenes into color, shape, and lighting — learned without explicit training. These discoveries allow us to manipulate real photographs in physically plausible ways. However, we also find surprising gaps in their understanding, such as their limitation of replicating principles of projective geometry, which provides reliable signatures for detecting generated images.
This talk explores what knowledge emerges within generative image models, revealing their strengths and weaknesses. I will discuss how these insights drive new applications and open challenges, pushing us closer to building generative models grounded in the physical world.

BE Fall 2024 Demos
2024-12-04 - 2024-12-09 | Skirkanich 225
The Department of Bioengineering Fall 2024 Student Demos.
Location: The Stephenson Foundation Bio-Makerspace (aka the BE Labs) in Skirkanich Hall 225.
BE 3090, aka BE MAD: Human-Cockroach Machine Interface. December 4th from 1:30-2:30 PM, and December 5th from 3:15-4:15.
BE 4950 Senior Design: Minimum Viable Product. December 9th, 3:30-5:00 PM.

ASSET Seminar: "Curious Embeddings, Hazy Oracles, and the Path to Safe, Cooperative AI"
2024-12-04 12:00 - 13:15 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Abstract:
Cooperation through safe and trustworthy communication and interaction is fundamental to how human teams accomplish complex tasks. Yet, despite significant–and sometimes revolutionary–advances in AI, we have barely begun to unlock the potential of safe, cooperative AI. This may stem from our limited understanding of how multimodal, large-scale AI models function, the one-sided nature of contemporary, fully-supervised AI approaches, or social concerns about human-AI collaboration. In this talk, I will dive into these layers of inquiry, beginning with a principled exploration of what the embeddings in large-scale foundation models reveal about the underlying problem and data, including new results disentangling sample-size from Bayes error and decision-boundary complexity. I will then introduce the concept of the human collaborator as a “hazy oracle”–a fallible partner rather than an omniscient information source–and establish a framework for modeling human-supplied error during collaboration. Building on these foundational insights, I will conclude with applications of these ideas to foster safe and effective human-AI collaboration in the health sciences.
Zoom Link (if unable to attend in-person): https://upenn.zoom.us/j/99385572884

Fall 2024 GRASP SFI: Dylan Shell, Texas A&M University, "Robot situatedness and information requirements for tasks"
2024-12-04 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
This talk describes investigations into the nature of robot–environment interaction and “niche fit” through the lens of state (or memory) minimization. The idea is that by limiting what a robot can store, much like so-called bottleneck methods, one hopes to uncover the information needed to perform specific tasks. We study a setting in which robots are able to exploit structural regularity within the environment. Doing so alters the minimization problem from classical reduction problems (i.e., those of Myhill–Nerode or bisimulation relations) in an important, fundamental way: it changes computational complexity class. The later part of the talk will try to explore interpretations and intuitions behind the (multiple) extra sources of this complexity. Touching briefly upon intriguing ways in which nondeterminism and casualty manifest themselves, the final part of the talk will describe how we are now approaching sensors within this theoretical framework too.

CBE Seminar: "Creating a New Circular Carbon Economy via Carbon Capture, Utilization and Storage" (Alissa Park, UCLA)
2024-12-04 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
To meet the ever-increasing global energy demands while addressing climate change, the development of carbon capture, utilization and storage (CCUS) technologies is one of the critical needs. In particular, there have been significant efforts to develop innovative CO 2 capture materials and CO 2 conversion technologies to create a new circular carbon economy based on renewable energy. The next-generation CO 2 capture materials, which are often water-free or water-lean, have unique structural and chemical properties that allow their applications in a wide range of reactive separation systems. Nanoparticle Organic Hybrid Materials (NOHMs) are organic-inorganic hybrids that consist of a hard nanoparticle core functionalized with a molecular organic corona that possesses a high degree of chemical and physical tunability. It has recently been discovered that NOHMs have interesting electrolyte properties that allow the CO 2 capture to be pulled by the in-situ CO 2 conversion reactions. The development of these unique nanoscale hybrid materials will not only advance CO 2 capture materials design but also introduce unique research opportunities in various sustainable energy and environmental fields. This seminar will discuss the challenges and opportunities of different CO 2 capture and conversion pathways including Negative Emission Technologies (e.g., Direct Air Capture) that can allow the development of circular carbon and hydrogen economy using renewable energy.

MSE Seminar: "Single Metal Site Catalysts for Sustainable and Clean Hydrogen Energy"
2024-12-05 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Fossil fuels have been overwhelmingly used in many industry sectors in past decades, causing significant CO2 and other pollutant emissions, low efficiency, and nonsustainability. Clean and efficient energy storage and conversion via electrochemical reactions associated with hydrogen, oxygen, and water have attracted substantial attention for energy and environmental sustainability. Among compelling energy technologies, hydrogen proton exchange membrane fuel cells (PEMFCs) are a promising zero-emission power source for transportation to mitigate environmental pollution and reduce fossil-fuel dependence. Meanwhile, water electrolyzers have been clearly identified as the sustainable pathway to produce cheap green hydrogen efficiently using renewable electricity. However, current materials, including catalysts, membranes, and ionomers, cannot meet the challenging targets of high-efficiency, low-cost, and long-term durability of hydrogen fuel cells and water electrolyzers. Developing high-performance catalysts from earth-abundant elements to replace current precious metals is crucial for making these hydrogen technologies viable for large-scale clean energy applications. U.S. DOE has continuously supported his research group in the past decade, aiming to address materials issues by designing and scaling up innovative and highly efficient catalysts and electrodes. This talk discusses recent understanding, progress, achievement, and perspective on developing low-cost and high-performance catalysts based on newly emerging atomically dispersed metal-nitrogen-carbon materials for sustainable and clean hydrogen technologies.

BE Doctoral Dissertation Defense: "High-throughput and high-dimensional single-cell analysis of antigen-specific CD4+ T cells" (Yuwan Guo)
2024-12-05 11:00 - 13:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Jenny Jiang are pleased to announce the Doctoral Dissertation Defense of Yuwan Guo.

Title: High-throughput and high-dimensional single-cell analysis of antigen-specific CD4+ T cells
Advisor: Dr. Jenny Jiang

Date :Thursday, Dec 5, 2024
Time: 11am – 1pm
Location: Glandt Forum, 3rd floor Singh Center

The public is welcome to attend.

ESE PhD Seminar: "Multiferroic MEMS Magnetic Field Sensors for Biomedical Applications"
2024-12-05 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The human body produces magnetic fields wherever ion exchange occurs. Detecting these pico-Tesla level magnetic fields enables non-invasive monitoring of brain and heart health, but medical-grade sensing methods require large equipment with high power consumption. This talk will detail a solution using microelectromechanical systems (MEMS) composed of a magnetostrictive and piezoelectric material. After an introduction to the sensor design and operation, we will discuss the design process, electrical and magnetic characterization, and results.

BE Doctoral Dissertation Defense: "Understanding the genome's structure-function relationship in early neural lineage commitment" (Katelyn Titus)
2024-12-05 15:30 - 16:30 | CRB Auditorium, 415 Curie Boulevard, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Jennifer Cremins are pleased to announce the Doctoral Dissertation Defense of Katelyn Titus.

Title: Understanding the genome’s structure-function relationship in early neural lineage commitment
Date: December 5, 2024
Time: 3:30 PM
Location: CRB Austrian Auditorium

The public is welcome to attend.

Fall 2024 GRASP on Robotics: Bill Smart, Oregon State University, "Privacy-Sensitive Robotics"
2024-12-06 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom.
ABSTRACT
As robots become more and more prevalent, both in the workplace and outside it, they will have greater access to the details of our lives. Sensors used by these robots to make intelligent decisions about what to do can also be used to record the people and things around them. These sensors are fundamentally different from existing fixed infrastructure, such as surveillance cameras, because they are attached to a mobile system, capable to operating autonomously. How should we think about the new privacy risks that such systems bring with them? How can we mitigate these risks, while still reaping the benefits offered by the widespread use of robots? What do we even mean when we say the word “privacy”? In this talk, we’ll give a framework for how to think about privacy in the context of mobile robot systems, outline some of the potential risks introduced by this new technology, and show some examples of technical mitigations that can preserve privacy, while still allowing the robot to do its job.

ESE Fall Seminar - "Quantum information processing stack: from bottom to top and back"
2024-12-06 11:00 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Quantum processors have become quite large and sophisticated machines over the last several years, with many tech companies racing to develop the first quantum computer of practical utility. While the progress has been impressive, quantum processors still face significant hurdles such as short coherence times and high error rates. They are not yet able to compete with classical information processing technologies in solving problems of practical interest. I will review some of the recent advances in the field and discuss my group’s contributions across the quantum information processing stack, from the control of quantum hardware to quantum algorithm development and back.

BE Doctoral Dissertation Defense: "Clonal differences underlie differential responses to initial, sequential, and prolonged drug treatment" (Dylan Schaff)
2024-12-06 13:00 - 15:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Sydney Shaffer are pleased to announce the Doctoral Dissertation Defense of Dylan Schaff.

Title:”Clonal differences underlie differential responses to initial, sequential, and prolonged drug treatment”
Date:December 6, 2024
Time: 1pm-3pm
Location: Wu and Chen auditorium, Levine Hall

The public is welcome to attend.

PICS Colloquium: Lipid Membrane Remodeling by Proteins and Peptides: Mechanistic insights from multi-scale analysis
2024-12-06 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
We will discuss the analysis of membrane remodeling by proteins and peptides using multi-scale computational methods; these include mainly molecular dynamics simulations at atomistic and coarse-grained levels, although we will also touch upon analyses using lattice models and a mean- field theory. The discussions will cover several systems that we have analyzed in recent studies, which include the SAR1 protein from the COPII machinery and the ESCRTIII complex; we will also briefly discuss how protein condensates interact with lipid membranes, especially in terms of their mutual influence on morphology and phase behaviors. These examples illustrate different molecular properties and mechanisms that are potentially relevant to membrane remodeling, as well as the values and limitations of various computational methodologies in such context.

MEAM Seminar: "Leveraging Impedance Properties for Free Self-Sensing in Actuators for Compact Robots"
2024-12-12 12:00 - 13:00 | Towne 319, 220 S. 33rd Street, Philadelphia, 19104, United States
Self-sensing actuators provide a compelling approach to designing compact robotic systems by integrating sensing capabilities directly into the actuator, eliminating the need for external sensors. This presentation, titled “Leveraging Impedance Properties for Free Self-Sensing in Actuators for Compact Robots,” highlights how the intrinsic impedance properties of actuators—resistance, inductance, and induced EMF—can be harnessed to achieve low-volume solutions of self-sensing actuators. Evidence for this approach is demonstrated through three projects: a self-sensing I-cord knitted SMA actuator that uses resistance measurements to monitor its state, applied in an inchworm robot and a gripper; a custom PET solenoid actuator that utilizes induced EMF to sense movement and velocity, enabling applications such as an origami-inspired bistable gripper and a facial reanimation device acting as an artificial muscle; and a custom acrylic linear solenoid actuator that leverages inductance to self-sense plunger position, demonstrated as an active valve in underwater swimming robots. These examples illustrate the potential of impedance-based self-sensing to streamline actuator design, enhance functionality, and enable new possibilities in robotics across domains.
