Penn Engineering Events

CBE Special Guest Lecture: "Preventing, Understanding and Reducing End-Customers' Power Supply Outages with Digital Twins" (Panayiotis Moutis, City College of New York)
2025-04-29 10:30 - 11:30 (America/New_York) | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Abstract:
Blackouts have become rarer in the last decade. However, equipment wear and faults (some predictable)affect smaller scales but many parts of Distribution Networks (DNs) more frequently and add up to several hours of interruptions per customer per year. Also, utilities will preemptively de-energize thousands of customers in the path or vicinity of forest fires and floods to minimize damages and loss of life. The limited, if not zero, visibility into the medium and low voltage DNs is partly to blame for the causes, length and extent of these disruptions, as also their recurrence, due to lack of insights. Monitoring DNs, however, is hard, because they are spatially dispersed with hundreds of critical points. This talk, first introduces the digital twin of DN transformers to identify load behaviors, effects of distributed resources and power quality issues leading to DN grid faults. Secondly, we present the digital twin of overhead conductors to detect approaching forest fires and, thus, enable utilities to interrupt customers’ service only when it otherwise unavoidable. Digital twins rely on the rising use of synchrophasor measurements within DNs, that enable highly granular and time-synchronized sensing of power system assets.

Steering Higher Ed Through Rough Seas: Three Bold Strategies to Navigate the Future
2025-04-29 16:00 - 17:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Higher education is navigating intense political pressure, shifting demographics, rising costs and evolving workforce demands. This session will detail three strategies for sustaining academic excellence while lowering administrative costs, expanding reach and impact, and regaining public trust.

Benjamin Franklin Medal in Electrical Engineering Symposium Honoring Kurt Petersen: "Small Tech, Big Impact: The Development and Commercialization of MEMS Sensors & Actuators"
2025-04-30 08:30 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
For two centuries, The Franklin Insitute has honored pioneering achievements in science, engineering, and industry. As the oldest comprehensive science awards program in the United States. The Franklin Insitute Awards celebrates Benjamin Franklin’s legacy by honoring the Franklins of today. Through their remarkable contributions, our laureates inspire the Franklins of tomorrow.
The 2025 Benjamin Franklin Medal in Electrical Engineering is awarded to Kurt Petersen, Co-Chair at the HardTech Group of the Silicon Valley Band of Angels. This Symposium celebrates Kurt for his pioneering research and development of micro-electromechanical systems (MEMS) technology – microscopic systems that merge mechanical and electrical functionality and which have wide ranging applications such as medical devices, inkjet printers, IoT, optical projectors, and automotive sensors.
Click here for more information and to register.

Franklin Awards Symposium: Honoring Professor Naomi J. Halas - Rice University - Recipient of the 2025 Franklin Medal in Chemistry
2025-04-30 08:30 - 12:00 | Vagelos Institute for Energy Science and Technology, Room 121, 231 S 34th Street, Philadelphia, PA, 19104, United States
This symposium will feature cutting-edge contributions in plasmonics and nanonphonics research that are enabling advances in life sciences, energy sustainability, and information technology.
Event Schedule
8:50 am: Welcome
9:00 am: Prof. Rizia Bardhan, Iowa State University.
9:35 am: Prof. Stephan Link, University of Illinois Urbana-Champaign (UIUC)
10:10 am: Break
10:30 am: Prof. Peter J. A. Nordlander, Rice University
11:05 am: Prof. Naomi J. Halas, Rice University (2025 Laureate in Chemistry)

ASSET Seminar: "Neurosymbolic Program Synthesis: Bridging Perception and Reasoning in Real-World Applications"
2025-04-30 12:00 - 13:15 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
Neurosymbolic Program Synthesis (NSP) integrates neural networks and symbolic reasoning to tackle complex tasks requiring both perception and logical reasoning. This talk provides an overview of the NSP framework and its applications in domains such as image editing, data extraction, and robot learning from demonstrations. We will delve into the key ideas behind NSP learning algorithms, focusing on the synergistic interplay between neural guidance and symbolic reasoning. Finally, we will discuss recent advances in ensuring the correctness of synthesized neurosymbolic programs, paving the way for robust and reliable AI systems.
Zoom Link (if unable to attend in-person): https://upenn.zoom.us/j/95763386582

JOHN A. QUINN DISTINGUISHED LECTURE IN CHEMICAL ENGINEERING: "Sticky Nanoparticles: Electrostatic Assembly of Targeted Delivery Agents" (Paula Hammond, MIT)
2025-04-30 15:30 - 16:30 | Wu & Chen Auditorium
Abstract:

Electrostatic assembly can be used to engineer coatings that yield release of different drugs, DNA or protein, resulting in highly tunable multi -agent delivery nanolayered release systems for tissue engineering, biomedical devices, and wound healing applications. Most recently, we have developed a modular nanoparticle approach using liposomal core particles and layering them with an electrostatic layer-by-layer (LBL) process in a simple and elegant method of constructing highly tailored ultrathin polymer coatings. The resulting LbL nanoparticles (LbL NPs) have negatively charged outer layers that present polyelectrolytes such as dextran sulfate or hyaluronic acid in a hydrated brush arrangement that enables hydration, steric repulsion, colloidal and serum stability, and specific or non-specific targeting. We have demonstrated that these particles have long systemic plasma blood half-lives and good tumor accumulation over time, and demonstrate efficacy in advanced breast and lung cancer models in which siRNA targets have been delivered with chemotherapy drugs in the same nanoparticle system.
By staging the release of different drug components via the adaptation of the nanoparticle structure, we can achieve highly synergistic release behavior in these systems. We have found that certain LbL nanoparticle formulations traffic differently in cells based on the negatively charged polypeptide, and we are exploring ways to utilize these differences in affinity for more selective tumor cell binding and deliver within cells.
Ongoing work includes addressing barriers to transport of these nanoparticles relevant to tumor or other tissue penetration, and will be discussed, including new work involving the understanding of these trafficking patterns and a means to leverage them toward the delivery of cytokines for activation of the immune system against ovarian cancer, a cancer which has not previously benefitted from immunotherapeutic approaches. In vitro and in vivo results will be discussed, as well as release mechanisms, toxicity studies and clinical outlook for these targeted systems. Ongoing work includes examination of how these LbL NP systems might be adapted to enhance delivery across the blood-brain barrier for glioblastoma, or modified to enhance tumor accumulation and penetration. These and other uses of controlled polyelectrolytes and their complexes for delivery within tissues and across barriers will be addressed.

Energy-Efficient AI: The Franklin Institute Awards Laureate Symposium Honoring William James Dally
2025-05-01 13:00 - 15:00 | Amy Gutmann Hall, Auditorium, 3333 Chestnut Street, Philadelphia, PA, 19104, United States
The Franklin Institute Awards Laureate Symposium is dedicated to honoring William James Dally, recipient of the 2025 Benjamin Franklin Medal in Computer and Cognitive Science
The event will feature Margaret Martonosi (H. T. Adams ’35 Professor of Computer Science, Princeton University), Yakun Sophia Shao (Associate Professor in Electrical Engineering and Computer Sciences, UC Berkeley), Joe Devietti (Computer and Information Science, Penn Engineering) and Benjamin Lee (Computer and Information Science; Electrical and Systems Engineering, Penn Engineering).
Awards Week Sponsors: JPMorganChase, Morgan Lewis, Marsha and Jeffrey Perelman
This event is part of AI Month 2025, which will explore AI’s impact on human well-being.
Click here to RSVP.

MEAM Master's Thesis Defense: "A Computational Model of Caenorhabditis elegans Locomotion"
2025-05-01 15:00 - 16:00 | Towne 319, 220 S. 33rd Street, Philadelphia, 19104, United States
Since discovered in 1897, the nematode Caenorhabditis elegans has surfaced as an excellent model organism for medical and genetic research. The worm propels itself through viscous-dominated creeping flows via undulatory motion. Moreover, experiments have revealed that the netamode’s swimming gait alters as a function of fluid viscosity. In the current research, we proposed a new solid-mechanics-based auto-propulsion model featuring a closed-form displacement field that better captures the nematode’s swimming gait in water. A series of decoupled/coupled (Fluid-Structure Interaction) finite-element simulations exploiting the Arbitrary Lagrangian-Eulerian (moving mesh) technique were then conducted to investigate how different gaits affect the free-swimming speed, and how the interaction with fluids of various viscosities and the presence of wall boundaries deviate the swimming gait from the solid-mechanics-based closed-form solution.

PICS Colloquium: Learning to Model the World (and Yourself) from Vision
2025-05-02 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 discuss recent publications from my group that attempt at learning models of the world and the effect of the actions of an agent within that world self-supervised, solely via interaction. In particular, I will discuss the potential and challenges of video generative models as a candidate for such a world model, the role of inductive biases using our recent work that discovers the kinematics of a robot as an example, and finally a new research direction in which we attempt to discover the physical rules underlying our world without any inductive biases whatsoever.

ESE Ph.D. Thesis Defense: "Multiferroic Resonators for Wireless Power Transfer and Magnetic Field Sensing in Biomedical Systems"
2025-05-06 10:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Micro-electromechanical systems (MEMS) composed of magnetostrictive and piezoelectric materials can translate information between the electrical and magnetic domains while exploiting mechanical resonance enhancement. Multiferroic MEMS devices such as these can be designed to perform magnetic field sensing and wireless power transfer (WPT) while maintaining device sizes on the order of 0.125 mm 2 . This thesis will focus on the theory, design, and characterization of these MEMS magnetometers and WPT devices.

Spring 2025 Robotics MSE Thesis and Capstone Lightning Talks and Poster Session
2025-05-06 14:00 - 16:00 | Wu & Chen Auditorium
This is an in-person event with in-person attendance in Wu and Chen Auditorium for Lightning Talks and Levine Lobby for Poster Session.
This year we will have an “Audience Choice” for best Lightning Talk and Poster. Please be sure to vote for your favorite! Voting will take place during the Poster Session using a QR code.
2:00pm – Lightning Talks
Welcome Remarks
Dr. Cynthia Sung – ROBO Program Chair
Rahul Aggarwal
Advised By: Dr. Rahul Mangharam
Generalizable Visual Prediction Via Disentangled Diffusion

Jack Campanella
Advised By: Dr. Vijay Kumar
Integrated Hardware and Software Codesign for Controlling Underactuated Aerial Robots

Satrajit Chatterjee
Advised By: Dr. Rahul Mangharam
World Modeling via Sparse Conditioning of Temporal Context

Michaela Feehery
Advised By: Dr. Eric Eaton
Event-Based Respiration Detection for Autonomous Robotic Triage

George Gao
Advised By: Dr. Nadia Figueroa
OCR: Out-of-Distribution Recovery with Object-Centric Keypoint Inverse Policy for Visuomotor Imitation Learning

Frank Gonzalez
Advised By: Dr. Vijay Kumar
Risk-aware MPC Planning for Unmanned Ground Vehicles

Pei-An Hsieh
Advised By: Dr. Ani Hsieh
Stable and Robust Tight Formation Flights of Quadrotors with MPC

Royina Jayanth
Advised By: Dr. Kostas Daniilidis
Exploring Generalization and Robustness of Neural Inertial Odometry

Alexander Kyimpopkin
Advised By: Dr. Pratik Chaudhari
Magic-8-Ball: World Models for Vision-Based Quadruped Path Planning

Sanghyub Lee
Advised By: Dr. Nadia Figueroa
Human-Robot Interactive Muscle-in-the-loop Upper Limb Training Using Real-time Muscle Dynamics Tracking via AI-driven Wearable Ultrasound Processing

Ruirui Ma
Advised By: Dr. Linh Thi Xuan Phan
Connectivity Constrained Multi-Robot Sparse Coverage

Lee Milburn
Advised By: Dr. Rahul Mangharam
Cluster-Funk: Clustering for Friction Estimation Under Nonlinear Knowledge

Emily Paul
Advised By: Dr. Vijay Kumar
Multi-Agent Reinforcement Learning with Reward Shaping for Coverage Control

Nishanth Rao
Advised By: Dr. Kostas Daniilidis and Dr. Vijay Kumar
Exploring Symmetries and Equivariance in Robot Learning

Hungju Wang
Advised By: Dinesh Jayaraman
Foundation Models for Realworld Robotics

Brice Diomande, Chris Lee, Henry Licht
Advised By Ani Hsieh
Sponsored By: Saint Gobain CertainTeed
Autonomous Mobile Robot for Installing Blown-In Insulation
2:30pm – Poster Session in Levine Lobby
4:00pm – Awards for Best Lightning Talk and Poster Announced

MEAM Ph.D. Thesis Defense: "Real-Time Perception and Mixed-Integer Footstep Control for Underactuated Bipedal Walking on Rough Terrain"
2025-05-06 15:00 - 16:00 | Towne 319, 220 S. 33rd Street, Philadelphia, 19104, United States
The promise of bipedal robots is to go where people go, serving as surrogates for human labor in dangerous, unstructured environments. For the most part, this promise remains unrealized. The primary challenge for controlling bipedal locomotion is underactuation. Standing on a single leg limits control authority, requiring appropriate foot placement to generate or absorb momentum and maintain balance. Rough terrain exacerbates this challenge by introducing restrictions on where the robot can step. These restrictions must be identified from onboard sensing modalities and accounted for in the footstep plan, all while meeting the strict real-time requirements of feedback control. In this thesis, we examine systems, modeling choices, and algorithms for solving this problem, ultimately enabling dynamic bipedal walking over previously unseen discontinuous terrain.
Conventional approaches decouple the problem of walking over rough terrain into separate modules for footstep planning and motion control, limiting walking speed and online adaptability. The beginning of this thesis introduces a new model-predictive-control-style footstep planner which eliminates this decomposition. We jointly optimize over the robot’s dynamics and discrete choice of stepping surface in real time to stabilize underactuated walking over constrained footholds.
Our footstep controller depends on approximating the safe terrain as a union of convex planar polygon “stepping stones”. In order to generate such an approximation from onboard sensors in real time, we propose novel safe terrain segmentation and convex decomposition algorithms. Our segmentation approach avoids the common design choice of plane segmentation, which we argue makes segmentation algorithms slower and less reliable. Instead, we classify terrain as safe based only on local features, yielding a segmentation which is both fast to compute and temporally consistent. We present full stack perceptive locomotion experiments on the underactuated biped Cassie, leveraging our novel footstep controller and perception pipeline to walk over previously unseen discontinuous terrain.
Finally, we present an exploratory study of a cascaded-fidelity model predictive footstep controller, which combines elements of our first footstep planner with whole-body model predictive control in order to navigate even more challenging terrains.

AI at the Crossroads: Ethics, Innovation and Impact
2025-05-07 14:00 - 15:30 | Amy Gutmann Hall, Auditorium, 3333 Chestnut Street, Philadelphia, PA, 19104, United States
As part of Philly Tech Week and AI Month, this panel explores the balance between cutting-edge AI advancements and responsible development, with a focus on the broader societal impact of artificial intelligence.
Panelists:

Chris Callison-Burch, Professor, CIS; Program Director, Online Master of Science in Engineering in Artificial Intelligence
Melissa Kelly, Deputy Managing Director, Penn Center for Innovation
Aaron Roth, Henry Salvatori Professor of Computer and Cognitive Science, CIS

CBE Seminar: "Redox-responsive Interfaces for Selective Electrochemical Separations" (Xiao Su, University of Illinois, Urbana-Champaign)
2025-05-07 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
Electric fields and electrochemical reactions can unlock new separation pathways. While electrochemical separations have been explored previously for water desalination, their translation to value-added chemical manufacturing or resource recovery has been hampered by the lack of molecular selectivity. Here, we present the molecular design of redox-responsive materials for enabling selective electrochemical separations.
Redox electron-transfer can be leveraged to tune interfacial selectivity, reversibility, and even synergistic coupling of reaction and separations. We combine synthetic design, in-situ interfacial measurements, and computational simulations to investigate the binding mechanisms of target ions at electrodes, and elucidate the contributing effects of charge-transfer, electrostatics, and solvation. These mechanistic insights can guide the discrimination of structurally similar ions, for applications ranging from critical element recovery to even enantioselective separations. Separately, we demonstrate how copolymer design and electrochemical systems engineering can innovate redox-electrodialysis. These integrated processes can have an impact on multicomponent separations, including the simultaneous abatement of ultra-short-, short-, and long-chain PFAS from semiconductor manufacturing.
Finally, we highlight the generalizability of the redox-mediated separations beyond adsorption, and extend the concepts to electrochemical liquid-liquid extraction platforms. We discuss how these continuous technologies can be scalable, and provide a path for industrial translation in e-waste recycling and mineral processing.

Spring 2025 GRASP Seminar: Mike Shou, National University of Singapore, "Video intelligence in the era of multimodal"
2025-05-08 10:00 - 11:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This will be a hybrid event with a VIRTUAL speaker. The GRASP seminar will be streamed for in-person attendance in Levine 307 and virtual attendance on Zoom.
ABSTRACT
The past few years have witnessed great success in video intelligence, as supercharged by multimodal models. In this talk, I will start with a brief sharing of our efforts, in building video-language models for understanding and diffusion models for video generation. Yet, video understanding and generation have always been two separate research pillars, despite their strong synergy. This motivates us to develop Show-o, one unified single transformer that can do both multimodal understanding and generation. Show-o is the first to unify autoregressive and discrete diffusion modeling, flexibly supporting a wide range of vision-language tasks of any input/output format, including visual question-answering, text-to-image/video generation, and generation of video keyframes with captions, all within one single 1.3B transformer. Show-o sheds light for building the next-generation multimodal video foundation model, and has sparked many follow-up works already.

CPE4H Seminar: “Engineering Native Biological Complexity from the Inside–out and Outside–in” (Cole A. DeForest, University of Washington)
2025-05-08 10:30 - 11:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
Engineering heterogenous multicellular tissue with native complexity remains one of the holy grails of regenerative medicine and basic biological research. As success in this regard would yield powerful bioengineered constructs useful in functional transplantation, high-throughput drug screening, and fundamental biology investigation, research efforts in our lab have centered around developing and implementing tools to spatiotemporally customize living cell function both from the “outside–in” and from the “inside–out”. In this talk, I will discuss some of our group’s recent successes in reversibly modifying the chemical and physical aspects of synthetic cell culture platforms with user-defined and grayscale control, regulating cell-biomaterial interactions through user-programmable Boolean logic, engineering microvascular networks that span nearly all size scales of native human vasculature (including capillaries), irreversibly photoassembling bioactive proteins within living cells, and driving biomolecular condensate formation using de novo-designed proteins. Results will highlight our ability to modulate intricate cellular behavior including stem cell differentiation, protein secretion, and cell-cell interactions in 4D.

CBE Doctoral Dissertation Defense: "Bridging Transcription and Signaling to Study c-MYC Function and Regulation in Cancer Cells" (Reshma Kalyan Sundaram)
2025-05-13 13:30 - 15:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Abstract:
The transcription factor c-MYC (MYC) is a master regulator of gene expression and is frequently deregulated in human cancers. Despite the prevalent role of MYC in cancers, no MYC inhibitors are currently available for clinical use. In this work, we investigated the molecular mechanisms underlying MYC’s transcriptional function and deregulation using an integrated approach combining bioinformatics analyses and kinetic modeling. In studying MYC’s regulation of transcriptional function, we analyzed publicly available next-generation sequencing datasets (ChIP-seq and RNA-seq) in various cancer cell lines to characterize MYC’s DNA binding patterns and gene targets. We discovered that MYC indirectly binds the TRE sites specifically at enhancers over promoters. We also found that MYC co-occupied these TRE enhancer sites synergistically with the AP-1 family of TFs, and that MYC binding to these sites varied with MYC levels. Gene Ontology analysis revealed that MYC binding to TRE sites contributes to transcriptional rewiring of cells by modulating several cancer hallmarks like proliferation, apoptosis, and cell adhesion. We also investigated upstream regulatory mechanisms contributing to MYC deregulation. We built an Ordinary Differential Equation (ODE) based systems model incorporating extracellular growth and matrix signals (received by EGFR and integrins, respectively) and intracellular signaling pathways (MAPK, Rho/ROCK, and PI3K/Akt) that regulate MYC. The modeling results revealed that MYC regulation is primarily driven by EGFR in normal cells, whereas both EGFR and integrin signaling play a combined role in regulating MYC in cancerous conditions. Our findings highlight a novel role played by extracellular matrix (ECM) based microenvironmental cues in addition to the well-known growth signaling cues on MYC regulation. In summary, we identify an enhancer-specific mechanism through which MYC functions in concert with AP-1 to regulate gene expression, and demonstrate how extracellular cues, including ECM signaling, contribute to MYC regulation. These newly uncovered mechanisms provide deeper insights into MYC’s oncogenic functions, and suggest potential avenues for therapeutic targeting of MYC-driven cancers.

ESE Guest SEminar - "Dynamical control of tip-induced quantum light-matter interactions at the nanoscale"
2025-05-22 11:30 - 12:30 | Greenberg Lounge (Room 114), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
The controllable manipulation of bandgap, radiative emission, and energy transfer in low-dimensional quantum materials provides a versatile platform for a range of quantum photonic devices. Moreover, the understanding and precise regulation of nanoscale behaviors exhibited by excitonic quasiparticles, such as excitons and trions, in low-dimensional semiconductors are paramount for the development of highly efficient nano-excitonic devices. In this talk, we introduce a tip-induced nano-spectroscopic approach for dynamically controlling light-matter interactions at the nanoscale. We then demonstrate a series of tip-induced nano-engineering experiments exhibiting plasmon-exciton interactions in quantum dots and atomically thin semiconductors. Our research shows a novel strategy for the creation of robust, tunable, and ultracompact nano-excitonic devices utilizing low-dimensional semiconductors.

MEAM Seminar: "The Role of YAP and TAZ in Regulating Mechanical Load-induced Bone Adaptation and Osteocytes Mechanosensing"
2025-06-03 10:15 - 11:15 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Fetal movements and physical activities generate mechanical signals that regulate musculoskeletal development. It is widely accepted that a bone’s adaptive response occurs within an optimal strain range that stimulates bone formation, exceeding typical daily activity levels. This principle has led to models predicting how bones respond to mechanical loads, as insufficient mechanical signals can result in bone loss, while high signals can stimulate new bone tissue formation.
The discussions on the mechanical adaptation of tissue have primarily focused on changes in size or shape under load. However, a key question remains: how do cells sense these loads and convert them into biochemical events leading to bone gain or loss? Osteocytes, the primary mechanosensors in bone, detect mechanical and hormonal stimuli, coordinating osteoblast and osteoclast activities. Mechanical signals activate osteocyte mechanosensors, triggering pathways that regulate transcription factors like YAP (Yes-associated protein) and TAZ (Transcriptional co-activator with PDZ-binding motif). These factors induce gene expression by binding to transcription factor TEAD, directing the signaling that regulates osteoblast and osteoclast function—a process known as mechanotransduction. In this study, we hypothesize that mechanical loading regulates prenatal bone development and adult bone remodeling through YAP/TAZ signaling and osteocyte mechanosensing. Therefore our goal is to determine the roles of YAP and TAZ in mechanical load-induced prenatal and postnatal bone formation.

CBE Doctoral Dissertation Defense: "Leveraging confinement and surface effects to control polymer phase behavior and transport phenomena in polymer-infiltrated nanoparticle films" (Trevor Devine)
2025-06-03 14:00 - 15:30 | Vagelos Institute for Energy Science and Technology, Room 121, 231 S 34th Street, Philadelphia, PA, 19104, United States
Abstract:

Highly loaded, polymer-infiltrated nanoparticle films (PINFs) enable the synergistic combination of polymers with the functionality of nanoscale fillers. Extensive studies have found that their behavior deviates markedly from bulk polymers due to extreme confinement and high interfacial area within the interstitial pore network. However, incorporating polymer blends in these PINFs (blend-PINFs) is unexplored. Confinement and nanoparticle surface interactions may substantially alter phase behavior from bulk expectations. Additionally, the prevalence of adsorbed polymer layers within PINFs present an opportunity to engineer a polymeric material dominated by interfacial effects, with little or no bulk region. In this thesis, we investigate how confinement and polymer-nanoparticle interaction asymmetry impact phase behavior, solvent resistance, and transport phenomena in blend-PINFs. Using a combination of optical microscopy, spectroscopic ellipsometry, scanning electron microscopy, small-angle neutron scattering (SANS), and resonant soft X-ray scattering (RSoXS), we examine how blend morphology deviates under nanoconfinement. To probe solvent resistance, we employ ex situ solvation experiments to track polymer removal and determine how confinement and surface chemistry influence polymer retention. We also introduce a novel fabrication method, Sequential Capillary Rise Infiltration (SCaRI), which sequentially infiltrates individual polymers. We find that strong asymmetry in polymer-nanoparticle interactions can suppress macroscopic phase separation by inducing pore-scale segregation. In blends with symmetric interactions, confinement produces more complex, system-specific effects, leading to either compatibilization or phase separation depending on blend type. We find that confinement enhances solvent resistance in PINFs, but surprisingly, resistance is not governed solely by polymer-solvent interactions: solvent-nanoparticle interactions emerge as a dominant factor in displacing adsorbed chains. Through SCaRI, we demonstrate that the infiltration sequence can significantly alter the final infiltration amount, and that phase morphology resembles fully infiltrated, CaRI-produced structures only when the second polymer has a stronger nanoparticle affinity. Overall, our results reveal several fundamental findings that allow more intelligent design of PINF and blend-PINFs that synergistical combine the aspects of its constituent polymers and nanoparticles, while also unlocking novel properties unachievable without the highly loaded nature of the PINFs.

Summer 2025 GRASP Seminar: "Brain orchestra in resting-state: Identifying communication modules from the functional architecture of area V1"
2025-06-09 12:00 - 13:00 | Amy Gutmann Hall, Room 306, 3317 Chestnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in AGH 306 and virtual attendance via Zoom.
ABSTRACT
How does the brain perform the complicated computations that allow us to learn about and interact with the environment? The rapid advances in optical imaging, machine learning, and the availability of computational resources, provide a unique opportunity to decipher this fundamental question. Although much has been learned about the computational properties of single neurons, we remain far from understanding how networks of cortical cells coordinate and interact with each other to process information. Several pioneering works have proposed theories regarding how the configuration of neuronal ensembles encodes information in the cortex. Ensembles of neurons that fire in synchrony are likely to be more efficient at relaying shared information to downstream targets as well as more likely to belong to networks of neurons subserving similar functions. Spontaneous patterns of activity reflect the intrinsic dynamics of the brain in the absence of external stimulation or task performance.
We imaged essentially simultaneously thousands of pyramidal neurons from granular and supragranular layers in mouse primary visual cortex (area V1) and mapped the functional connectivity within and across layers. We found that under resting-state conditions, 19-34% of neuronal pairs at distances < 300μm exhibited significant functional connections, decreasing to ∼10% by 1mm. Orientation-tuning similarity had a weak influence on correlations measured during resting-state conditions. In contrast, internal brain state, reflected in modulations of aggregate neuronal activity or pupil diameter, played a much stronger role. Overall, V1 laminae display small-world architecture, yet layers show different connectivity structure: Layer 4 exhibits stronger pairwise correlations and flatter degree-of-connectivity distribution compared to supragranular layers, whose degree-of-connectivity distribution decays exponentially.
We argue that neurons, together with their first-order functionally connected partners, define basic multi-neuronal ensembles (modules) that serve as fundamental information processing primitives both within and across cortical laminae. Across cortical layers, the firing probability of Layer 2/3 pyramidal neurons can be predicted by the co-firing of their first-order functionally connected partners in Layer 4, following a ReLU-like activation pattern. Typically, Layer 2/3 neuron firing probability rises sharply, when ≥ 13% of its Layer 4 partners co-fire, a nonlinear behavior that ensures reliable transmission of supra-threshold activity as well as sparse firing. Furthermore, module-to-module information flow from Layer 4 to Layer 2/3 displays increased specificity, sensitivity, accuracy, and precision relative to module-to-neuron information transfer. Interestingly, modules of different sizes exhibit different response properties as well as different strengths of coupling to behavioral brain-state parameters, distributed across a continuum. In general, responses of Layer 2/3 neurons adapt to the dynamic range of the aggregate input they receive from their co-firing Layer 4 partners. These findings on the behavior of first-order functionally connected multi-neuronal ensembles (modules) remain robust even when functional connectivity is assessed under stimulation conditions, where signal correlations predominate.

MSE Ph.D. Thesis: "Metasurfaces For Environmental Refractive Index Sensing: Design, Fabrication And Interrogation"
2025-06-09 15:00 - 17:00 | Towne 327 the Active Learning Classroom
Metasurfaces are artificial materials composed of sub-wavelength building blocks whose size, shape, periodicity and composition are tailored to engineer their optical response and achieve arbitrary control of their interactions with light. Their phase discontinuities or resonances are critically dependent upon the local dielectric or refractive index environment, thus making metasurfaces excellent candidates as refractive index sensors. A unique application of such passive metasurface refractive index sensors is in agricultural and environmental sensing to conduct in-situ measurements of crop health conditions with high spatiotemporal resolution, thus maximizing crop yield. This application necessitates compact, low-cost, biocompatible metasurface sensors that can be distributed en-masse. In this thesis we study low-cost, scalable, combined top-down and bottom-up meatasurface fabrication techniques involving nanoimprint lithography and solution-processible metallic and dielectric colloidal nanocrystals. We then study metasurface sensor monitoring or interrogation techniques utilizing conventional RGB/hyperspectral remote imaging, as well as novel polarimetry techniques, to prove the real-world implementation feasibility of these metasurface refractive index sensors and develop their evaluation metrics.

MEAM Seminar: "SLAM in Hard Places"
2025-06-10 10:15 - 11:15 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Simultaneous Localization and Mapping is a fundamental problem for robots interacting with a novel environment and has been a densely studied area of research for several decades. The modern paradigm of feature extraction and matching coupled with advancements in sensor technology have allowed robots to achieve sub meter localization accuracy over kilometer long trajectories in controlled indoor and urban environments. Despite these advancements, as roboticists endeavour to deploy agents in more unstructured outdoor settings to perform search and rescue or geological survey, the standard assumptions adopted by the majority of the community start to break down. In this talk we will discuss the SLAM paradigm at a high level, how these assumptions break down in the outdoor-unstructured setting, existing strategies for mitigation, and finally present work from the lab for performing SLAM in an underwater ocean setting.

ESE Ph.D. Thesis Defense: "Tunable Dielectric Nanocrystal Metasurfaces for Colorimetric Sensing"
2025-06-11 13:30 | Room 313, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Optical metasurfaces enable strong light–matter interactions, making them ideal platforms for high–figure-of-merit (FOM) sensing. When fabricated from colloidal nanocrystal dispersions, these metasurfaces offer unique advantages in fabrication flexibility, reconfigurability, and cost-effectiveness. However, conventional fabrication approaches often rely on toxic material systems. In this thesis, we enhance the FOM of titanium dioxide (TiO₂)-based dielectric metasurfaces by integrating biocompatible materials and a low-temperature, solution-processable fabrication method. We address three key challenges: (1) scalable fabrication of TiO₂metasurfaces using environmentally friendly materials and low-temperature processes, (2) enhancement of humidity sensitivity for environmental sensing, and (3) realization of dual-band operation through three-dimensional metasurface architectures.
We develop a room-temperature, water-based nanoimprint lithography method using aqueous TiO₂ nanocrystal (NC) inks to fabricate metasurfaces that support quasi-guided mode resonances (QGMs). By tuning geometric parameters, we engineer high quality factor QGM resonances that serve as baselines for sensing. We introduce chitosan biopolymer as a responsive filler into the void spaces between NCs. The moisture uptake properties of chitosan dynamically alter the refractive index of metasurface film, enhancing sensitivity to relative humidity by up to 250%. We model this TiO2 NC – Chitosan composite system using effective medium approximations and experimentally validate the impact of polymer incorporation on device performance and hysteresis behavior. Finally, we demonstrate dual-band optical humidity sensing by fabricating double-sided TiO₂ metasurfaces with independently tunable gratings on opposite sides of a shared waveguide. We imprint gratings of different periodicities and spatial orientations. A decoupling interlayer of PDMS allows one metasurface to remain humidity-insensitive, acting as an in-situ optical standard. This enables differential sensing with improved accuracy.

MEAM Seminar: "Discrete and Continuous Modeling of Fibrous Biological Materials: Compressible Large Deformations, Damage, and Crack Propagation"
2025-06-12 10:15 - 11:15 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Random fiber networks are integral to biological materials such as the extracellular matrix, cytoskeleton, and blood clots. A random fiber network is the main structural component of the extracellular matrix, the cytoskeleton, and our blood clots. The mechanical behavior of these materials is characterized by large deformations, non-linear stress-strain response, and large compressibility. Experimental and computational studies have shown that macroscopic mechanical properties are strongly influenced by changes in network topology and fiber properties. Similarly, the rupture of these networks is dictated by their microstructural organization. However, a complete understanding of the failure mechanisms and their origins remains elusive.
In this talk, we will present computational models of discrete random fiber networks to understand the mechanical response and rupture of random fiber networks. In addition, we will introduce continuum constitutive models that capture the stress-strain relations and damage accumulation for network materials.

MEAM Seminar: "Mechanical Interfaces for Health: From Mechanobiology to Tactile Perception"
2025-06-17 10:15 - 11:15 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Our lab combines adhesion and tribology with modern polymers and surface coatings to understand soft interfaces in biology towards improving human health and accessibility. On the scale of cells, mechanical stiffness of cells and tissue can indicate diseases like fibrosis or osteoarthritis. On the scale of the human body, mechanical forces generated by friction form the tactile stimuli used to perceive touch. Here, we will show how leveraging soft matter phenomena like elastohydrodynamics and soft sliding friction can overcome existing challenges to access mechanical markers in disease modeling, or to develop new methods to control the sense of touch in haptic devices for people who are blind. We will conclude with some future directions where engineering of mechanical interfaces is the basis towards improving healthcare outcomes.

Summer 2025 GRASP Seminar: Antonino Furnari, University of Catania, "Towards an Embodied Understanding of Human Behaviour with Egocentric Vision"
2025-06-17 11:30 - 12:30 | Amy Gutmann Hall, Room 306, 3317 Chestnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in AGH 306 and virtual attendance via Zoom.
ABSTRACT
The last few years are witnessing a major shift in the way we think of computing, with humans relying more and more on AI assistants which speak their language and understand images and videos. While this revolution has largely been possible by wrapping the world with a digital layer allowing artificial systems to natively ingest information and produce content, future AI systems will need to conquer the same physical space in which humans live. Towards this direction, egocentric vision has established itself as a powerful paradigm, placing a camera where humans have eyes, making it possible to perceive the world from their unique point of view. In this talk, I will first discuss the role that the community envisions for egocentric vision in the AI revolution, then highlight the foundational role of large-scale egocentric datasets, such as EPIC-KITCHENS, EGO4D, and Ego-Exo4D in advancing our ability to understand human behavior. I will next present research efforts aimed towards developing deep learning models to perceive, understand, and anticipate human actions and interactions from this unique first-person perspective. Finally, I will discuss how these capabilities can pave the way for assistive technologies on wearable devices designed to provide direct support to users in procedural activities.

ESE Ph.D. Thesis Defense: "Statistical Limits and Efficient Algorithms for Learning-Enabled Control"
2025-06-18 09:00 | Amy Gutmann Hall, Room 414, 3333 Chestnut Street, Philadelphia, 19104, United States
As the adoption of large-scale learning for control continues to grow, developing sample-efficient algorithms has become critical. Yet, even in simple settings, algorithms achieving optimal sample complexity for specific problem instances often remain unknown. Motivated by this limitation, we discuss recent progress toward understanding sample-efficient methods in learning-enabled control. We first examine the statistical limits of offline reinforcement learning with continuous state, action, and observation spaces by deriving lower bounds on the cost of a learned controller that characterize inherently challenging problem instances. We then introduce efficient algorithms and establish tight finite-sample bounds on the cost they incur for controlling a general class of nonlinear dynamical systems. These results underscore the critical role of dataset quality and motivate our subsequent exploration of optimal task-oriented experiment design. Finally, we consider large-scale pre-trained models for control, analyzing how models trained across diverse tasks can be fine-tuned for new control objectives with limited data. We approach this problem through the lens of representation learning in adaptive control and provide upper bounds on the incurred regret.

AI Across the Care Spectrum: From Bench to Bed (Webinar)
2025-06-18 14:00 - 15:00 | PA
Join Penn AI on June 18 @ 2PM for an exciting webinar exploring how artificial intelligence is transforming every corner of healthcare—from dental exams to home care, medical imaging to gerontology, and beyond. Hear directly from leading experts including as they dive into the real-world impact of AI in their fields, the challenges of implementing AI responsibly in clinical settings, and the bold opportunities ahead—such as the possibility of a foundation model for medicine. This dynamic and forward-looking conversation is open to the public—don’t miss the chance to see how AI is reshaping the future of care.
Speakers include:

Marylyn Ritchie, Edward Rose, M.D. and Elizabeth Kirk Rose, M.D. Professor, PSOM/Genetics (co-moderator)
René Vidal, Rachleff University Professor, PSOM/Radiology, SEAS/ Electrical & Systems Engineering (co-moderator)
Markus Blatz, Professor of Restorative Dentistry, Penn Dental Medicine
Patricia Brennan, Provost’s Distinguished Visiting Faculty Fellow 2024-2025
George Demiris, Penn Integrates Knowledge University Professor, Penn Nursing, PSOM/Biostatistics and Epidemiology
Alison Pouch, Assistant Professor of Radiology, PSOM/Radiology, SEAS/Bioengineering
Gary Weissman, Assistant Professor, PSOM/Medicine

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MEAM Ph.D. Thesis Defense: "Elastomeric Strain Limitation for Design of Soft Pneumatic Actuators"
2025-06-20 10:00 - 11:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Modern robots embody power and precision control, yet as robots undertake tasks that apply forces on humans this power brings risk of injury. Soft robotic actuators use deformation to produce smooth, continuous motions and conform to delicate objects while imparting forces capable of safely pushing humans. This thesis presents strategies for the design, modeling, and strain-based control of human-safe elastomeric soft pneumatic actuators (SPA) for force generation, focusing on embodied mechanical response to simple pressure inputs.
We investigate electroadhesive (EA) strain limiters for variable shape generation, rapid force application, and targeted inflation trajectories. We attach EA clutches to a concentrically strain-limited elastomeric membrane to alter the inflation trajectory and rapidly reorient the inflated shape. We expand the capabilities of EA for soft robots by encasing them in elastomeric sheaths and varying their activation in real time, showing applications in variable trajectory inflation under identical pressure sweeps.
We then address the problem of trajectory control in the presence of external forces by modeling the pressure-trajectory relationship for a concentrically strain-limited class of silicone actuators. We validate theoretical models based on material properties and energy minimization using active learning and automated testing. We apply our ensemble of neural networks for inverse membrane design, specifying quasi-static mass lift trajectories from a simple pressure sweep. Finally, we begin analysis of experimentally informed active learning optimization for additional mechanical design tasks, moving towards future works in larger system design.
