Penn Engineering Events

Fall 2025 GRASP SFI: Deepti Ghadiyaram, Boston University, "Interpreting and Leveraging Generative Representations"
2025-09-24 15:00 - 16:00 (America/New_York) | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Levine 307 and virtual attendance via Zoom.
ABSTRACT
Generating high-quality photo-realistic visual content is a thriving area of research. In this talk, I will focus not on the generation process, but on understanding how rich visual semantic information is represented within generative models. Specifically, I will present our work that uses mechanistic interpretability tools like k-sparse autoencoders to probe various layers and denoising timesteps of different diffusion architectures. Next, I will present how to leverage interpretable concepts to control the generation process towards more safer and creative outcomes.

CBE Seminar: "Imaging Genetics: Enhancer-mediated Dynamic Gene Control in Space and Time" (Bomyi Lim, University of Pennsylvania)
2025-09-24 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
Canonical models suggest that regulatory enhancers function independently of genomic distance, position, and orientation to activate the target gene. Indeed, a wide range of genomic distances and relative enhancer positions exist in endogenous contexts. However, systematic analysis of how specific enhancer-promoter configurations affect transcriptional dynamics has been limited by technical constraints. Here, we employ single-cell MS2/MCP-based live imaging in Drosophila embryos to systematically analyze transcriptional dynamics driven by varying enhancer-promoter configurations. Our analyses reveal that while linear enhancer-promoter distance moderately tunes transcriptional output, downstream enhancer positioning relative to the promoter reduces mRNA output by 70%. Each configuration modulates distinct transcriptional parameters: linear distance governs initiation kinetics, while relative enhancer positioning dictates transcriptional stability. Although the downstream enhancer positioning destabilized the enhancer-promoter interactions, transcription factor hub properties remained comparable between two configurations, revealing a clear dissociation between TF hub dynamics and E-P configuration-dependent transcriptional activity. These effects are consistent across varied enhancer and reporter sequences, revealing configuration-dependent cis-regulatory element arrangement as an intrinsic mechanism for transcriptional fine-tuning. This work challenges the paradigm of configuration-independent enhancer function and establishes a framework to dissect the interplay between genome architecture and trans-acting factors.

MEAM Ph.D. Thesis Defense: "The Role of YAP and TAZ in Regulating Load-induced Bone Adaptation and Osteocytes Mechanosensing"
2025-09-25 10:00 - 11:00 | Towne 305, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Mechanical loading is essential for skeletal growth, maintenance, and repair, yet the mechanisms that regulate bone mechanoadaptation remain incompletely understood. Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ), downstream of the Hippo pathway, are emerging regulators of bone cell biology, but their in vivo role in skeletal mechanoadaptation has not been fully defined.
To address this, we combined pharmacological inhibition of YAP/TAZ with models of prenatal and postnatal C57BL/6 mice. We began with a short in vivo study to test the effectiveness of verteporfin (VP) in suppressing YAP/TAZ activity and to optimize dynamic histomorphometry and high-resolution osteocyte imaging. VP is a small-molecule inhibitor that interferes with YAP/TAZ–TEAD transcriptional activity. Next, we examined prenatal load-induced bone formation using an ex vivo bioreactor system, in which E15.5 embryonic hindlimbs were subjected to cyclic compression to induce ossification of the primary centers. Samples were also cultured in media containing VP to test whether YAP/TAZ inhibition suppresses load-induced prenatal bone formation.
Finally, we investigated adult mechanoadaptation using a cyclic compressive in vivo tibial loading model in C57BL/6 mice. Animals were injected with DMSO (vehicle), VP, or MGH-CP1 (CP1) and loaded over two weeks. CP1 is a TEAD autopalmitoylation inhibitor that suppresses YAP/TAZ–TEAD transcriptional activity.
Our results demonstrated that YAP/TAZ inhibition abrogated load-induced bone formation. Prenatally, rudiment mineral lengthening was suppressed. In adults, the anabolic effects of loading—increased periosteal and endosteal bone formation parameters, cortical thickness, and trabecular architecture were supprerssed when YAP/TAZ were inhibited. Mechanical loading increased the fraction of positively labeled osteocyte lacunae and enhanced osteocyte cytoskeletal branching, but these effects were abolished under VP or CP1 treatment. Finally, we confirmed the mechanosensitivity of bone marrow cells: loading upregulated Cyr61 and Ctgf, well-established YAP/TAZ target genes, but this response was suppressed by VP or CP1.
These findings establish YAP/TAZ as critical regulators of load-induced bone formation across developmental stages. By coordinating mechanosensitive responses among osteoblasts, osteoclasts, osteocytes, and marrow stromal cells, YAP/TAZ act as central regulators of skeletal mechanotransduction. This work not only provides mechanistic insight into the cellular basis of bone mechanoadaptation but also highlights YAP/TAZ as potential therapeutic targets in conditions of skeletal fragility, including osteoporosis and osteogenesis imperfecta.

MSE Seminar: Designing Biomaterials With Spatially Tunable Properties - Lesley Chow - Lehigh University
2025-09-25 10:30 - 12:00 | Wu & Chen Auditorium
Biological tissues are complex materials where the spatial arrangement of multiple components (i.e., extracellular matrix, cells) is tightly linked to their function. For example, osteochondral tissues contain discrete biochemical and physical gradients across the bone-cartilage interface that are critical for functional load transfer in our articulating joints. Our lab is focused on strategies to fabricate biomaterials with spatially tunable biochemical and physical properties to engineer tissues with native-like organization. To achieve this, we have developed a versatile approach using end-functionalized polymer conjugates that enable us to
independently control surface chemistry, scaffold architecture, and scaffold stiffness. Functional groups become displayed on the surface during fabrication, eliminating the need for post-processing modification steps. Multiple chemistries can therefore be spatially presented by using multiple printer heads during a single 3D printing session. In parallel, we can independently and simultaneously control scaffold architecture and stiffness by changing print patterns and polymer molecular weight ratios, respectively. This seminar will describe our platform and how we are developing 3D-printed materials to guide tissue regeneration for
complex tissues like the osteochondral interface.

ESE Fall Seminar - "Physics-Aware, Full-Stack Software to Accelerate Practical Quantum Computing"
2025-09-25 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Quantum software can be a force multiplier that can significantly shorten the timeline for utility-scale results from quantum hardware. In particular, several key research directions will help realize practical quantum advantage. Physics-aware, cross-layer optimizations will continue to yield important efficiencies to allow applications to make the most of quantum resources. Software-directed noise-aware optimization and error correction, in particular, will be key to increasing gate depths and maintaining acceptable output fidelity. Pulse-level optimizations and specialized native gates will also be key enablers. Additionally, applications will be hybrid computations involving high-performance classical resources as well as quantum hardware serving as special-purpose accelerators. Effectively partitioning computations between these classical and quantum resources will be necessary to support realistic applications. Additionally, deep compiler optimization and classical simulation of Clifford and near-Clifford circuits can also be important classical investments towards more efficient quantum computations.

FOLDS seminar: Propagation-of-Chaos in Shallow Neural Networks beyond Logarithmic Time.
2025-09-25 12:00 - 13:00 | Amy Gutmann Hall, Room 414, 3333 Chestnut Street, Philadelphia, 19104, United States
Zoom link: https://upenn.zoom.us/j/98220304722
The analysis of gradient-based learning of Neural Networks remains an outstanding challenge, even for the simplest shallow architectures.
A powerful mathematical framework that has emerged over recent years lifts the optimization in the space of probability measures, and captures important empirical phenomena such as the ‘blessing of overparametrization’. However, the resulting learning guarantees remain mostly qualitative.
In this talk, we study the fluctuations between idealized mean-field dynamics and polynomially-sized networks over suitable time horizons — the so-called Propagation of Chaos. We provide a novel analysis that goes beyond traditional Gronwall-based PoC by exploiting certain geometric properties of the optimization landscape, and apply these results to representative models such as single-index models, establishing polynomial learning guarantees.
Joint work with Margalit Glasgow and Denny Wu.

BE Seminar - Bozhi Tian, "Physical Biology Strategies for Translational Bioelectrical Interfaces"
2025-09-25 15:30 - 16:30 | 216 Moore Building

CBE Doctoral Dissertation Defense: "Mechanical Confinement as a Driver of Aneuploidy in Cancer" (Steven Phan)
2025-09-26 10:30 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Abstract:

Cell confinement and mechanical stress are common in solid tumors, but any impact on genetic changes remains unclear. Using chromosome reporters (ChReporters) that reveal heritable losses of chromosomes in live cells, we discover that ChReporter losses are surprisingly equivalent when cells are subjected to either mild confinement (6-10µm) or strong confinement (2µm). Strong confinement causes interphase nuclear rupture in most cells, whereas mild confinement suffices to perturb mitotic spindles, prolong pro/metaphase, and induce micronuclei. However, micronuclei that form upon chromosome mis-segregation in mitosis do not emerge during mild confinement but do emerge following release – indicating a mitotic memory of the confined state. Live cell imaging post-confinement revealed that mitotic cells and their daughters also tend to arrest or die. Delayed induction of micronuclei and ChReporter loss are phenocopied by transient disruption of microtubules. Inhibition of cell cycle entry using a clinically deployed CDK4/6-inhibitor further shows ChReporter loss requires mitosis and inhibitor washout increases ChReporter loss. Consistent with a memory of spindle confinement, single cell RNA-sequencing demonstrates enrichment of chromosome segregation factors long after confinement.

MEAM Ph.D. Thesis Defense: "Pneumatic Actuation in Soft Robotic System"
2025-09-26 15:00 - 16:00 | CTA
Soft robotic systems, constructed from compliant and adaptive materials, offer advantages such as safe interaction with humans, flexibility in motion, and the ability to conform to unstructured environments. These capabilities make them promising for applications in healthcare, manufacturing, and exploration. A central challenge, however, is the development of actuation strategies that are versatile, efficient, and capable of integrating sensing and control.
This dissertation investigates pneumatic actuation as a broad platform for advancing soft robotic systems. Pneumatic systems naturally couple deformation with pressure signals, enabling not only motion generation but also embedded feedback and logic. Three representative studies are presented: the design of pneumatic actuators that support diverse motion behaviors, the development of stimuli-responsive valves that achieve autonomous environmental interaction, and the creation of pneumatically controlled lattices that demonstrate tunable mechanical properties.
Together, these works highlight the role of pneumatic actuation as more than a source of force, showing how it can support adaptability, responsiveness, and structural intelligence in soft systems, while pointing toward future directions in miniaturization and simplified pneumatic control.

MSE PhD Defense: "Integrated Photonics for Intelligent Parameter Retrieval"
2025-09-29 11:30 - 12:30 | Room 313, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Thesis Committee:
Prof. Liang Feng (Chair)
Prof. Firooz Aflatouni
Prof. Ritesh Agarwal
Prof. I-Wei Chen

Zoom: https://upenn.zoom.us/j/2449152154

CBE Doctoral Dissertation Defense: "Gas Encapsulating Microcapsules (GEMs)" (CK Yeh)
2025-09-29 12:00 - 14:00 | Vagelos Institute for Energy Science and Technology, Room 121, 231 S 34th Street, Philadelphia, PA, 19104, United States
Abstract:

Microcapsules that can respond under hydrostatic pressure would open a new avenue of application in ultrasound- or impact-induced release of therapeutic agents. While microcapsules that are designed to release cargo under uniaxial compressive loadings have been developed, they are filled with liquid, rendering them insensitive to hydrostatic pressure. To overcome this limitation, bubbles can be introduced into the core of the capsule that can impart hydrostatic pressure sensitivity. Although microcapsules that contain bubbles have been reported, the methods for their fabrication make it difficult to control the size of the bubble and microcapsule. In this work, we use microfluidics to create uniform microcapsules while also utilizing osmosis-induced-cavitation to convert microcapsules into gas-encapsulating microcapsules (GEMs). Following GEMs formation under high salt concentrations, the size of the bubble can be modulated by placing the GEMs back into relatively lower salt concentrations. GEMs with a well-defined thickness to diameter ratio (t/D) and volume fraction of gas are subjected to a known hydrostatic pressure through the means of a drop tower. These data establish a relationship between how the thickness to diameter ratio and volume fraction of bubble influence the rupture pressure and drug release, helping to establish the foundation for a new class of on-demand therapeutics that take advantage of pressure inputs.

CBE Doctoral Dissertation Defense: "Engineering Multiphasic Processes to Enhance Droplet Microfluidics and Biofuel Conversion" (Owen Land)
2025-09-29 14:00 - 16:00 | Vagelos Institute for Energy Science and Technology, Room 121, 231 S 34th Street, Philadelphia, PA, 19104, United States
Abstract:

Multiphasic processes underpin nearly every aspect of modern life; from the food we eat and the clothes we wear to the medicines that sustain us and the energy systems that power our world. This thesis presents three contributions to the advancement of multiphasic processes by developing intelligent control, scalable processing, and reactor design. First, artificial intelligence is applied to droplet and bubble microfluidics through convolutional neural networks (CNNs) in the form of soft-sensors. Coupled with proportional–integral–derivative (PID) feedback loops, these sensors enable autonomous control of droplet size and flow regimes, maintaining stable operation under disturbances and recovering from failure modes without operator intervention. The framework is further extended to complex geometries, including double emulsions and anisotropic hydrogel rods, demonstrating adaptability across several multiphase microfluidic systems. Second, a sliding film evaporator (SFE) is developed as a continuous method for solvent removal from PLGA emulsions. By spreading emulsions into thin films across temperature-controlled channels, the SFE accelerates chloroform removal while maintaining particle uniformity, overcoming the inconsistency and scalability limitations of traditional evaporation techniques. Finally, bubble-mediated transesterification reactors are developed for biodiesel synthesis from algae-derived triglycerides. Methanol microbubbles enhance interfacial mass transfer and lower the apparent activation energy, enabling >95% conversion under moderate conditions. Kinetic studies coupled with ASPEN PLUS simulations demonstrate reactor scalability, while highlighting the importance of diffuser design and continuous glycerol removal. Together, these contributions provide a pathway to the continual improvement of multiphasic process engineering.

MEAM Seminar: "Taking Advantage of Coherent Vortex Wakes: Formation Flight and High Density Tidal Energy Harvesting"
2025-09-30 10:15 - 11:15 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Wake flows – the fluid mechanical “debris” shed behind an aerodynamic body – are often characterized by unsteady, turbulent, low-momentum fluid. Usually these wakes are to be avoided, but in several situations the wake can exhibit an organized structure consisting of well-defined high energy vortices. Examples of these coherent, or structured, wakes include trailing vortex flows behind animals in flight or swimming fish as well as the vortices shed behind wings pitching to high angles of attack. In this talk I will illustrate several examples of structured wakes in both natural and engineered systems, drawing from several projects from our lab including measurements of enhanced renewable energy harvesting using arrays of oscillating flow turbines, and energy savings experienced by birds flying in small flocks.

ASSET Seminar: "Title TBD"
2025-10-01 12:00 - 13:15 | Amy Gutmann Hall, Room 414, 3333 Chestnut Street, Philadelphia, 19104, United States
Abstract TBD

Zoom: https://upenn.zoom.us/j/98963621993

Fall 2025 GRASP SFI: Binghao Huang, Columbia University, "Scaling Touch: Flexible Tactile Skin for Dexterous Manipulation"
2025-10-01 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 via Zoom.
ABSTRACT
Tactile and visual perception are crucial for fine-grained human interactions with the environment. Developing similar multimodal sensing capabilities for robots can significantly enhance and expand their manipulation skills. This talk presents a scalable tactile stack that couples flexible, large-area tactile skin with multimodal perception and simulation-driven learning. (1) Hardware. I will first introduce a low-cost, flexible tactile “skin,” outline the associated design choices, explain why I value it over other sensors in different contexts, and describe how I integrate it into the system to ensure high-quality tactile data. (2) Learning. Vision and touch have distinct natures yet are both important for robot decision making; I will explain how we encode tactile and visual data so that both contribute effectively to the decision-making process. (3) Scaling up Tactile Data. I will present two directions: (i) using portable tactile devices to collect large-scale real-world tactile data and leveraging this dataset to enhance policy learning, and (ii) leveraging tactile simulation to increase policy robustness. We use a real-to-sim-to-real pipeline that calibrates a GPU-parallel tactile simulation and uses RL fine-tuning to let policies explore with the small corrective “wiggling” behaviors required for tight-fit bimanual assembly.

MSE Seminar: "Quantum Technologies with Atom-Light Interaction" Chuanwei Zhang - Washington University in St. Louis
2025-10-02 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
From knotted cords to contemporary computers, the revolution in information technologies has been a major driving force of human civilization. Since its emergence in the early 1900s, quantum mechanics has played a foundational role in enabling many
transformative technologies—such as lasers and transistors—that are now recognized as hallmarks of the first quantum revolution. Over the past two decades, the focus has shifted to the second quantum revolution, which aims to develop novel quantum
technologies that harness the creation, manipulation, and measurement of quantum superposition and entanglement in physical systems. In this talk, I will provide an overview of this rapidly evolving field and highlight the transformative potential of
quantum technologies through two illustrative examples involving ultracold atoms and trapped ions controlled by light: (i) quantum simulation of topological quantum matter, such as triply-degenerate fermions; and (ii) quantum squeezing and sensing via
exceptional points in nonlinear optical media. Despite significant technological challenges, these emerging quantum technologies hold great promise to revolutionize computing, communication, security, materials science, and sensing in the near future.

FOLDS seminar: Theory and practice of LLM quantization
2025-10-02 12:00 - 13:00 | Amy Gutmann Hall, Room 306, 3317 Chestnut Street, Philadelphia, PA, 19104, United States
Zoom link: https://upenn.zoom.us/j/98220304722

Modern LLMs process information by repeatedly applying a basic primitive of matrix multiplication. Estimates show that about 60-84% of the energy consumed by LLMs goes into memory load/store operations. How can we reduce this power consumption? Tokens start as about 16-bit integers but get mapped to vectors of floats of length in the 1000s, suggesting very low information density per dimension. Thus, unsurprisingly there has been much success in reducing precision of both weights and activations without much loss in LLM performance. In this talk we will present information-theoretic analysis of quantized representations and show how it lead us to creating NestQuant, a new SOTA algorithm for weight/KV-cache/activations (ICML’2025).

Fall 2025 GRASP on Robotics: Jiatao Gu, University of Pennsylvania, “Towards Robust World Models”
2025-10-03 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This event will be in-person ONLY in Wu and Chen Auditorium.
ABSTRACT
Autonomous agents need a world model that explains observations, predicts what comes next, and chooses actions over long horizons. Think of catching a ball: the robot must infer where it is now and where it will be next—even when it slips out of view—and move to intercept. Recently, large diffusion-based video models trained on internet-scale data have shown promising results for world modeling; however, they remain brittle—forecasting errors accumulate over time, especially during long open-loop rollouts without geometric grounding or collective feedback. In this talk, we present our recent research toward a more robust video generation foundation. Instead of diffusion, we build on scalable normalizing flows–a different family of generative models based on invertible transformations. We will detail the mathematical formulation, explain how these models can be trained end to end, and describe how we construct a practical video model from this framework. We will conclude by outlining research directions derived from this approach and steps toward a truly robust world model.

ESE Ph.D. Thesis Defense: "Microscopic Surface Electrochemical Actuators for Voltage-Tunable Optical Elements"
2025-10-03 12:30 - 13:30 | Brand Details
Surface electrochemical actuators (SEAs) harness ion-induced surface stress changes to produce large bending deformations at the microscale. They have previously been applied in microrobot locomotion and microbattery validation, demonstrating their versatility as low-voltage microscopic actuators. Here, we extend their functionality by showing that ultra-thin platinum membranes (10 nm thick, 10–100 µm wide), fabricated via low-temperature lithographically patterned atomic layer deposition, can undergo voltage-driven buckling displacements of several hundred nanometers in aqueous electrolyte. These out-of-plane motions, controlled within ±150 mV of applied bias, span the full visible wavelength range when integrated as the movable membrane of an optical resonator. The buckling mechanics are characterized using atomic force microscopy and finite element analysis, while we also develop a hyperspectral imaging method to optically reconstruct the device topology. The actuators operate with response times on the order of tens of milliseconds and exhibit static power consumptions below a nanowatt, while remaining directly compatible with CMOS circuitry. By coupling surface-stress–driven mechanics with electronic control, these buckling-enabled actuators (BEAs) provide a pathway toward compact, low-power, voltage-tunable optical elements for applications in reflective displays and holography.

PICS Colloquium: Flow and heat transfer over rough walls: fundamental physics, numerical simulations, and bulk parametrizations with Elie Bou-Zeid
2025-10-03 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Understanding the physical processes modulating the transport of scalars, such as heat, over very rough surfaces is essential for understanding the thermal environment of
cities, how wind and solar farms modify heat and water exchanges between the
atmosphere and Earth surface, and parameterizing surface physics in coarser Earth
systems models. This talk examines this problem in the urban context. Since passive
scalars such as water vapor are advected with the flow, broad similarity is expected
between the widely-studied momentum transfer problem and its scalar counterpart.
However, unlike momentum that is dominated by form drag over very rough walls,
scalar transport must occur through the viscous exchanges at the solid-fluid interface.
This results in transport dissimilarity, as well as in a continuous dependence on the
Reynolds number. In addition, the spatial variability of the geometry gives rise to the so-
called dispersive fluxes that can be larger than conventional turbulent fluxes in the
roughness layer. In this talk we will use large eddy simulations to examine the role of
surface topography, the resulting transport dissimilarity, and novel approaches for
parametrizing scalar exchanges using the surface renewal theory.

MEAM Seminar: "Self-assembly of Colloidal Diamond by Multiple Routes"
2025-10-07 10:15 - 11:15 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
There has been considerable interest in the colloidal self-assembly of photonic crystals with a diamond structure, owing to their exceptional optical properties, such as a wide photonic bandgap and relative insensitivity to disorder. These materials are valuable for applications in optical circuits, low-threshold lasers, sensors, and solar cells. Given the three-dimensional nature of photonic crystals, colloidal self-assembly is a favored fabrication method.
In this context, we outline several different approaches for the self-assembly of colloidal diamond and zincblende. Some methods utilize specific DNA interactions, while others rely on depletion interactions. One notable advantage of the depletion interaction is its capacity to guide particles that come into contact at any point on their surfaces toward the desired interlocking configuration. This funneling mechanism significantly accelerates crystallization kinetics, allowing for crystallization at lower particle concentrations. The most effective routes may involve a combination of both types of interactions.

CBE Doctoral Dissertation Defense: "Exploring Liquid-Liquid Phase Separation Across Length Scales: From Atomistic Bias Potentials To Phase-Field Models" (Alexander M. Johnson)
2025-10-07 10:30 - 12:00 | Amy Gutmann Hall, Room 306, 3317 Chestnut Street, Philadelphia, PA, 19104, United States
Abstract:

Liquid–liquid phase separation is a fundamental thermodynamic process that governs structure and function in biological systems, chemical separations, and multiphase materials. Within this broad field, computational studies play a critical role in advancing understanding of this phenomenon by enabling investigation of phase behavior across multiple length scales. In this thesis, liquid–liquid phase separation is explored across scales ranging from atomistic simulations to phase-field models. At the atomistic level, concepts from phase-field theory are used to derive a bias potential that enables direct control of liquid–liquid phase separation in molecular simulations. Within this enhanced sampling framework, macroscopic thermodynamic quantities such as excess free energy, interaction parameters, and activity coefficients are obtained, as demonstrated using binary Lennard–Jones mixtures as model systems. Furthermore, biasing liquid–liquid phase separation under different environmental conditions provides a pathway to relate free energies of phase separation to the stimuli response of Lennard–Jones mixtures and aqueous monomer solutions. Beyond the atomistic scale, liquid–liquid phase separation is examined through simulations of bicontinuous morphologies to generate machine learning–ready datasets for autonomous materials fabrication. In addition, phase-field modeling is applied to examine equilibrium partitioning in ternary liquid mixtures and their dynamics of liquid–liquid phase separation arising from solvent transfer methods. Altogether, this thesis develops computational strategies that extend from atomistic simulations to phase-field modeling, establishing a foundation for linking molecular-level features of liquid–liquid phase separation with macroscopic thermodynamic descriptions. These tools open opportunities to design, optimize, and control multiphase processes and materials across diverse applications.

Zoom Information:
Meeting ID: 979 8424 1614
Passcode: [REDACTED]

BE Doctoral Dissertation Defense: Ryan Friedman
2025-10-07 13:00 - 15:00 | PA

CIS Seminar: "Reliable and Socially Aligned LLMs: Are We There Yet?"
2025-10-07 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Large language models (LLMs) are powerful but not yet reliable: they hallucinate, misalign with human values, and struggle with social reasoning. In this talk, I will trace a path from diagnosing failure modes such as hallucinations, to uncovering the pitfalls of aligning models with noisy human preferences and diverse values, and finally to emerging frontiers in socially grounded reasoning. Along the way, I will highlight design principles, empirical findings, and open questions that reveal both how far we’ve come—and how far we still have to go—toward building reliable and socially aligned LLMs.

ASSET Seminar: "Robust and Uncertainty-Aware Decision Making under Distribution Shifts"
2025-10-08 12:00 - 13:15 | Amy Gutmann Hall, Room 414, 3333 Chestnut Street, Philadelphia, 19104, United States
Abstract TBD

Zoom: https://upenn.zoom.us/j/92346171614

Fall 2025 GRASP SFI: Tianjiao Ding, University of Pennsylvania, "Learning Parsimonious Representations for Efficient Analysis and Synthesis"
2025-10-08 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This presenter is one of the winners of the 2025 GRASP vote for internal PhD or postdoc SFI Speakers!
This is a hybrid event with in-person attendance in Levine 307 and virtual attendance via Zoom.
ABSTRACT
The automatic discovery of structures in data (analysis) and generation of data (synthesis) are two core problems in machine learning. Since data is high-dimensional and complex, a common paradigm is to learn a low-dimensional representation for data to facilitate both analysis and synthesis. However, existing methods are challenged by restrictive data assumptions and lack of semantic compositionality. We address these challenges by a unifying paradigm, which is to learn/leverage latent spaces supported on low-dimensional linear subspaces. Encoders and decoders then map between data and latent spaces. Such paradigm enables us to push multiple frontiers in data analysis and synthesis, including clustering images, aligning the semantics of text generation, and efficient image generation.

CBE Seminar: "Using NMR to Probe Functionality at Electrochemical Interfaces in Beyond Lithium Batteries" (Lauren Marbella, Columbia University)
2025-10-08 15:30 - 16:30 | Wu & Chen Auditorium
Abstract:
Beyond lithium-ion batteries, like sodium and potassium, are more abundant in the Earth’s crust and alleviate geopolitical concerns surrounding the materials inside of lithium-based batteries. However, both sodium and potassium batteries display unique interfacial chemistry that develops during electrochemical cycling in conventional electrolytes, preventing performances that are on par with current lithium systems. In the region between the electrodes and the electrolyte, a solid electrolyte interphase (SEI) is produced by the spontaneous breakdown of electrolyte compounds that dictates these inefficiencies. In my talk, I will discuss how we use nuclear magnetic resonance (NMR) spectroscopy to probe the structure and dynamics of the SEI as well as the reactions that occur at these interfaces to correlate these features with battery degradation. Insight from these methods allow us to determine the precise mechanisms of failure that arise inside of functional devices as well as develop new approaches to mitigate performance decline.

The Penn AI Symposium: Global Ideas Shaping Humanity
2025-10-10 - 2025-10-11 | Jon M. Huntsman Hall, 3730 Walnut Street, Philadelphia, PA, 19104, United States
The inaugural Penn AI Symposium is a landmark event that gathers leading thinkers who will share their explorations at the frontiers of artificial intelligence.
The symposium is hosted by Penn AI, a University-wide initiative driving responsible AI innovation at Penn. The launch of Penn AI and the upcoming symposium signal a new chapter in Penn’s commitment to pioneering the future of AI, fostering interdisciplinary collaboration, and addressing the most significant scientific and societal questions of our time.
The symposium is open to faculty, students, and thought leaders, both internal and external to Penn. Penn AI is an interdisciplinary initiative, and speakers will address topics in Penn AI’s core themes: AI Foundations, AI+Business, AI+Education, AI+Health, AI+Science, and AI+Society.
Speakers from Penn Engineering will include:

Vijay Kumar, Nemirovsky Family Dean
René Vidal, Rachleff University Professor, ESE, CIS, Radiology
Konrad Kording, Nathan Francis Mossell University Professor, BE, CIS, Neuroscience
Paris Perdikaris, Associate Professor, MEAM

Register Now

Climate Week at Penn
2025-10-13 - 2025-10-17 | PA
Now in its sixth year, Climate Week at Penn offers opportunities for every member of the Penn community to learn about and act on the climate crisis. The theme for 2025 is “Hot Spots,” be they literal (wildfires and extreme heat) or figurative (political, cultural, interpersonal, or scholarly hot topics). The Climate Week core organizing committee looks forward to working with partners across campus on this year’s lineup. Events marked in red below have been organized by a committee member. Questions or ideas about this year’s programming? Write us at contact@environment.upenn.edu.

ESE Ph.D. Thesis Defense: "Safeguarding AI Systems Against Unexpected Inputs"
2025-10-14 09:30 - 10:45 | Greenberg Lounge (Room 114), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
Artificial intelligence systems powered by deep neural networks have achieved remarkable success across a broad range of applications. However, perturbations such as natural image corruptions or crafted malicious queries, can cause significant performance degradation. This poses severe risks in safety-critical applications, such as autonomous driving and clinical decision-making. A key vulnerability of machine learning models is their inability to handle data outside the training distribution or knowledge. When facing unseen or otherwise challenging inputs, models often make incorrect decisions without warning users.
This thesis improves the safety of machine learning systems by building three stages for handling challenging inputs: (1) rejecting unexpected inputs with an explanation, (2) providing statistical guarantees on rejection, and (3) enabling models to adapt to challenging inputs. We consider two distinct scenarios: models with known training distributions (e.g., in cyber-physical systems) where challenges are out-of-distribution data, and models with unknown training distributions (e.g., large language models in a multilingual context) where challenges are defined by standards like harmful content or deficits in knowledge across languages. We further investigate how to address challenging inputs for two clinical applications, autism diagnosis and acne classification.
