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2 events,
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The mammalian cortex is the most effective and efficient electronic device we know of, yet its immense complexity and large spatial extent make interfacing with it extraordinarily difficult, limiting our understanding of its operation. To help address this challenge, we are developing tools that enable interrogation of cortical dynamics both in concert with the natural […]
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Abstract: Colloidal self-assembly remains difficult to predict and control, particularly in systems where experimental observations deviate from predictions based on traditional Brownian dynamics models. In these systems, hydrodynamic interactions (HI), which are often neglected or oversimplified, can play a critical role in governing particle dynamics. This dissertation systematically investigates the role of hydrodynamic interactions in […] |
1 event,
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Performance is the currency of modern computing. Achieving peak throughput on fast‑evolving accelerators demands more control than today's compilers provide. I will present Exo and the Exocompilation paradigm: a user‑schedulable programming language that shifts two responsibilities traditionally hard‑coded in compilers--hardware backends and optimization strategies--into safe, extensible user libraries. In Exo, optimizations are expressed as verified […] |
2 events,
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After pre-training, large language models are aligned with human preferences based on pairwise comparisons. State-of-the-art alignment methods (such as PPO-based RLHF and DPO) are built on the assumption of aligning with a single preference model, despite being deployed in settings where users have diverse preferences. As a result, it is not even clear that these […]
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This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. This week's speaker will be presenting virtually. ABSTRACT Access to timely, high-quality medical care is a global challenge due to workforce shortages. In this talk, I will discuss how we can address this bottleneck through two emerging frontiers: autonomous […] |
3 events,
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The Mei Research Group at Purdue University bridges the gap between fundamental discovery and real-world innovation. Integrating chemistry, materials science, and engineering, our research advances organic semiconductors and conductors—materials with transformative potential for printed electronics, bioelectronics, and related technologies. Our work spans both immediate industrial impact and long-term visionary pursuits. In this seminar, I will […]
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Trustworthy AI requires secure hardware that protects data confidentiality and integrity. Yet security is often an afterthought, while AI hardware is optimized primarily for performance and energy efficiency. My vision is to establish AI hardware as the root of trust, enforcing confidentiality and integrity through hardware mechanisms without sacrificing these critical design goals. This talk […]
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Zoom link: https://upenn.zoom.us/j/98220304722 Learning Gaussian Mixture Models (GMMs) is a fundamental problem in machine learning, and the Expectation-Maximization (EM) algorithm and its variant gradient-EM are the most widely used algorithms in practice. When the ground-truth GMM and the learning model have the same number of components, m, a line of prior work has attempted to […] |
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This event will be in-person ONLY in Wu and Chen Auditorium. ABSTRACT With increasing availability of data in various forms from images, audio, video, 3D models, motion capture, simulation results, to satellite imagery, representative samples of the various phenomena constituting the world around us bring new opportunities and research challenges. Such availability of data has […] |
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Energy systems are becoming increasingly complex, featuring greater variability and uncertainty. While AI tools promise to improve performance for decision-making under uncertainty, establishing robustness and risk guarantees remains challenging. Motivated by real-world energy challenges, we develop sufficient conditions to control tail risks for arbitrary AI decision-making policies. Furthermore, we develop an end-to-end framework to learn […] |
3 events,
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Architected materials (or mechanical metamaterials) across length scales—from nanometers to centimeters—have enabled previously unachievable mechanical properties through a variety of 3D material morphologies. Significant advances in our understanding of these materials have thus pointed to structure-property relations that lead to unique macroscopic mechanical properties. Despite this progress, several hurdles have precluded widespread application of these […]
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The shift to multi-tenant clouds and growing data demands exacerbate contention on shared data infrastructure. In these environments, contention remains a primary bottleneck to performance. While there is extensive research on concurrency control protocols, these approaches share a fundamental limitation: they handle conflicts only after they have materialized, missing opportunities to improve performance by avoiding […] |
4 events,
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Many of the most important optimization problems in practice are massive in scale, mathematically complex, and involve numerous unknown parameters. Machine learning offers a powerful way to address these challenges by uncovering hidden structure and improving decision quality, but integrating predictions into algorithms raises fundamental questions: which architectures align with combinatorial structure, and how can […]
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The Department of BIoengineering at the University of Pennsylvania and Dr. Lewis Chodosh are pleased to announce the Doctoral Dissertation Defense of Hamza T. Title: "JAK-STAT Signaling in Breast Cancer Dormancy and Recurrence" Date: Wednesday, April 8th Time: 12:30 pm ET Location: BRB Gaulton Auditorium The public is welcome to attend.
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This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT As data-driven approaches become the predominant paradigm for robotics, the burden of scaling robot data becomes increasingly transparent. The standard recipe for data-driven robot learning requires teleoperated expert demonstrations on real robots, which are expensive to scale. […] |
3 events,
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From fundraising to competitive strategy, vibe coding to agentic orchestration, Aristotle offers a surprisingly practical operating system for entrepreneurs in the AI era. This isn't an ethics talk. This is a first principles review of the formal logic underpinning entrepreneurial game theory and industrial economics amidst rapid, tectonic shifts in the market landscape. Hosted by […]
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Dielectric components play an integral role in the electronic communication, navigation, and defense systems, all devices which underpin daily life in our modern world. For many of these devices, particularly those which are designed to operate in high-radiation environments like space, space-charging and resulting dielectric breakdown present a persistent and pressing challenge for long term […]
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Zoom link: https://upenn.zoom.us/j/98220304722 The recent empirical success of the Muon optimizer in training large language models has outpaced the theoretical understanding of its matrix-gradient orthogonalization design. To bridge this gap, this talk introduces surrogate-model approaches that analyze and systematically improve deep learning optimization over a single iteration. We first present the isotropic curvature model, a […] |
1 event,
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Abstract: Protein-protein interactions (PPI) are ubiquitous in biological processes. Their study has significant implications for drug discovery as PPIs are important pharmacological targets for small molecules and important in various therapeutic modalities, such as targeted protein degradation and antibodies. Therefore, understanding the stability and dissociation of protein-protein complexes is of great fundamental and practical interest. […] |
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1 event,
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The Department of Bioengineering at the University of Pennsylvania and Dr. Roy Hamilton are pleased to announce the Doctoral Dissertation Defense of Shreya Parchure. Title: "Understanding and Improving Language Performance in Post-Stroke Aphasia with Machine Learning, Brain Networks, and Transcranial Magnetic Stimulation" Advisor: Dr. Roy Hamilton Date: Monday, April 13, 2026 Time: 12:30 PM Location: […] |
5 events,
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The talk will focus on my lab's research program at the interface of crustacean biomechanics and bio-inspired robotics. I will begin by introducing metachronal propulsion within the wider landscape of aquatic locomotion strategies, highlighting its taxonomic breadth and the gap in its translation to engineered systems. I will then present new, unpublished data from a […] Out-of-distribution (OOD) data presents a significant challenge for data-driven runtime monitors of safety-critical cyber-physical systems. In particular, such monitors are rarely resilient to OOD data: both theoretical guarantees and empirical performance are difficult to maintain when the input to the data-driven component lies outside of the training distribution. In this thesis, we aim to develop […]
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Integrated photonics is poised to transform communication, computing, and sensing by shrinking complex optical systems onto scalable chip-scale platforms. Realizing this potential, however, requires next-generation photonic systems that move beyond isolated device-level advances toward integrated platforms that are simultaneously low-power, low-noise, reconfigurable, and scalable. Meeting this challenge demands a full-stack understanding of photonic systems across […] |
7 events,
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A trained Large Language Model (LLM) contains much of human knowledge. Yet, it is difficult to gauge the extent or accuracy of that knowledge, as LLMs do not always "know what they know'' and may even be unintentionally or actively misleading. In this talk I will discuss feature learning introducing Recursive Feature Machines — a […]
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As the only quantum information carrier at atmospheric pressure and temperature, photons play a versatile role in the quantum information ecosystem. Recent progress in fabricating high-quality-factor microresonators has enabled unprecedented control of photons through nonlinear optical interactions. In this talk, I will focus on the precision-metrology aspect of quantum photonics. I will discuss the on-chip […] |
2 events,
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High-entropy ceramics are an emerging class of materials in which configurational entropy competes directly with enthalpy to stabilize complex crystal structures. Beyond their promise for applications ranging from energy storage and catalysis to radiation tolerance and extreme-environment structural materials, their vast compositional space and diverse bonding environments present a rich landscape for simulation and modeling. […] Aluminum nitride (AlN) bulk acoustic wave (BAW) devices dominate acoustic filtering in the mobile market at 3 GHz and below along with surface acoustic wave (SAW) devices. However, the intrinsic electromechanical coupling coefficient of AlN limits the scaling of these BAW devices to higher frequencies to support the increased data processing demands of 5G and […] |
4 events,
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This event will be in-person ONLY in Wu and Chen Auditorium. ABSTRACT This talk surveys recent advances on contraction theory for dynamical systems, as a robust, computationally-friendly and modular stability theory. Starting from basic notions, I will present novel theoretical properties and examples of contracting dynamics, including gradient systems, controlled Lure' systems, constrained optimization solvers, […]
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The Department of Bioengineering at the University of Pennsylvania and Drs. Robert L. Mauck and Carla R. Scanzello proudly announce the Doctoral Dissertation Defense of Sung Yeon Kim. Title: "Biophysical Regulation of Synovial Fibroblasts and Macrophages in Osteoarthritise" Advisors: Drs. Robert L. Mauck and Carla R. Scanzello Date: Friday April 17, 2026 Time: 12:00 EM […]
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ABSTRACT This thesis presents studies of band engineering in structured photonic systems, in which geometry, symmetry, and periodic patterning are used as design principles to access topological phases, flat bands, and nonlinear optical responses that are unavailable in unstructured settings. Both the dispersion and the geometric structure of Bloch states provides the unifying theoretical language […] |
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1 event,
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The Department of Bioengineering at the University of Pennsylvania along with Drs. Christos Davatzikos and Haochang Shou proudly announce the Doctoral Dissertation Defense of Vasiliki Tassopoulou. Title: "Probabilistic and Uncertainty-aware Methods for Biomarker Trajectory Forecasting in Aging and Neurodegeneration" Advisor: Drs. Christos Davatzikos and Haochang Shou Date: Monday, April 20 2026 Time: 1:30 PM Location: […] |
5 events,
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There is a lack of confidence in present in vitro disease models and drug efficacy tests, as they do not properly recapitulate the dynamic physiology and pathophysiology of the human organism. This challenge is particularly acute in oncology: present tools to study drug responses fail to faithfully mimic the patient’s tumor microenvironment (TME) and thus […]
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Since the invention of the integrated circuit in 1958, the integration of exponentially more devices onto a single chip has transformed computing—yet memory remains largely separated from logic, resulting in a “memory wall”. Recent advances in memory research have introduced a variety of new memory technologies. My research focus, Memory Integration and Data Dis-Aggregation (MIDDAS), […]
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Foundation Models and Generative AI for Medical Imaging Segmentation in Ultra-Low Data Regimes |
5 events,Modern AI systems are typically trained by optimizing average losses. Yet, many of the requirements that matter in practice are not, inherently, averages. Safety, robustness, truthfulness, alignment, and invariance often describe conditions that should hold across inputs, outputs, or transformations of both. When such requirements are enforced on average over data, a model may still […]
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Progress in 3D reconstruction and generation has accelerated rapidly, producing increasingly detailed geometry and photorealistic rendering. However, moving beyond photorealism requires models that not only look correct, but are also semantically grounded and physically plausible. This talk focuses on two complementary directions. First, multimodal grounding: 3D representations should align naturally with language and images to […]
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The Department of Bioengineering at the University of Pennsylvania and Dr. Jessica Morgan are pleased to announce the Doctoral Dissertation Defense of Angela Xu. Title: "Cone Photoreceptor Structure and Function in Choroideremia Assessed Using Adaptive Optics Scanning Light Ophthalmoscopy" Advisor:Dr. Jessica Morgan Date: Wednesday, April 22, 2026 Time: 1:00 PM - 3:00 PM Location: Goddard […] |
4 events,
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Nanomaterials have found widespread use in many applications, including those related to photonics, electronics, catalysis, energy conversion, sensing, imaging, and biomedicine. Chemistry plays a central role in all these developments. For almost three decades, my group has been working diligently to develop chemical methods for synthesizing colloidal nanomaterials with well-controlled properties. In this talk, I […]
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Zoom link: https://upenn.zoom.us/j/98220304722 There are two broad strands of literature on the theoretical underpinnings of machine learning. “Computational“ learning theory traces its origins to theoretical computer science, with an influential paper being Valiant’s 1984 paper on probably approximately correct (PAC) learning. “Statistical” learning theory dates back even further, and traces its origins to statistical decision theory, […] |
2 events,
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This event will be in-person ONLY in Wu and Chen Auditorium. ABSTRACT Perception is central to both intelligent machines and human experience, with vision playing a dominant role in how we sense and interpret the world. In this talk, I will explore how invisible wave signals, including radio frequency (RF) and sound, can complement vision […]
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Calibration in the Age of AI: From Prediction to Decision Making to AI-Assisted Research How much should users trust AI predictions, and how should they use their predictions when making important decisions? This talk will discuss calibration and how it mediates the interface between probability, prediction and decision making. We will also touch on how […] |
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4 events,
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AI is transforming the world, but at what cost to our energy systems? As demand for computing power surges, data centers are becoming one of the most consequential frontiers in the energy transition. Dr. Chan's talk will unpack how emerging technologies, smarter design, and bold innovation can redefine data centers as engines of efficiency, sustainability, and progress.
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While many of the tremendous advances seen in robotic dexterity over the past half-decade have been driven by new motor learning methods, I remain convinced that manipulation is a “full stack” problem, benefiting from beautiful synergy between all levels of a robotic system. In this talk, I will present examples from our lab’s attempts to […]
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Cloud droplets grow initially by condensation, and thereafter by colliding and coalescing with each other. We discuss how condensation can make cloud turbulence different from "normal" turbulence. We then ask about caustics: locations where droplet collisions may occur. In toy vortical flows we find surprising ways in which caustics may form, and create lucky drops […] |
3 events,
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The Department of Bioengineering at the University of Pennsylvania and Dr. Li Shen are pleased to announce the Doctoral Dissertation Defense of Jiong Chen. Title: "GRAPH AND VISION BASED LEARNING FOR MEDICAL IMAGE ANALYSIS: APPLICATIONS IN BRAIN NETWORKS AND OMICS PHENOTYPING" Advisor: Dr. Li Shen Date: Wednesday, April 29th Time: 3:00 PM - 5:00 PM […]
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Abstract: Commercialized membrane electrolyzers use acidic proton-exchange membranes (PEMs). These systems offer high performance but require the use of expensive precious-metal catalysts such as IrO2 and Pt that are nominally stable under the locally acidic conditions. Alkaline-exchange-membrane (AEM) electrolyzers in principle offer the performance of PEM electrolyzers with earth-abundant catalysts and inexpensive cell components. Unfortunately, […] |
2 events,
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Click here for all the details Join us at the University of Pennsylvania for the IDEAS on Generative AI Symposium, a forward-looking event exploring the next wave of generative and multimodal artificial intelligence. As generative models rapidly evolve from text and image synthesis toward integrated systems that can reason, perceive, and act, this symposium will […] |
1 event,
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Abstract: Many biological models relevant to clinical and biochemical applications are governed by ordinary and partial differential equations. Traditional numerical methods are well suited for forward simulations of these models; however, patient and system‑specific inference often requires invasive measurements or data that is experimentally inaccessible. As a result, inference tasks involving the reconstruction of state […] |
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