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This presenter is one of the winners of the 2025 GRASP vote for internal PhD or postdoc SFI Speakers! This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Building general-purpose robots remains fundamentally constrained by data scarcity and labor-intensive engineering. Unlike vision and language, robotics lacks […] |
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High performance electrochemical energy storage devices are critical technologies to ensure energy security and sustainability. In this presentation, I will introduce a gradient-based optimization framework to design porous electrodes for maximum energy storage under ultra-fast charging conditions, along with experimental validation of the optimized design. Porous electrode materials are characterized by highly tortuous pore networks […]
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As the impact of artificial intelligence (AI) continues to proliferate, computer architects must assess and mitigate its energy demands. This talk will survey strategies for mitigating the energy used by AI computation and datacenter infrastructure, drawing on data and experiences from industrial, hyperscale systems. |
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Modern generative AI is often improved through costly post-training (e.g., RLHF or preference tuning). This talk highlights a complementary alternative called inference-time methods. With the right inference-time objectives, search procedures, and compute allocation, we can meaningfully improve generative AI model behavior without updating model weights. We will begin with a principled formulation of inference-time methods […]
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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 presenter will be virtual. ABSTRACT AI agents — whether embodied robots, conversational systems, or wearable assistants — are increasingly present in our daily lives, yet they remain far from being true partners. Bridging the gap from […] |
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Structure and dynamics of electric double layer (EDL), the sub-nanometer region at the electrode/electrolyte interface, are essential to the function and performance of many energy conversion and storage devices, ranging from electrolyzers, photoelectrochemical cells, fuel cells to batteries. In situ probe of the EDL structure and dynamics at the molecular level requires advanced molecular spectroscopic […]
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Zoom link: https://upenn.zoom.us/j/98220304722 Physics-informed neural networks (PINNs) minimize composite losses that penalize PDE residuals alongside boundary and initial conditions. While this resembles multi-task learning, the optimization landscape is fundamentally different. Differential operators amplify high-frequency error modes by polynomial factors, while the neural tangent kernel's eigenspectrum suppresses precisely those modes -- creating a spectral mismatch absent […]
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Traditional medicine failed because it is designed for the “average patient” as a one-size-fits-all solution. The generative AI revolution promises the moonshot of conditioning each treatment on the right patient at the right time, named as precision medicine. But knowing who the right patient is and when the right time is is far from trivial. […] |
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This event will be in-person ONLY in Wu and Chen Auditorium. ABSTRACT Recent years have seen a transformation in artificial intelligence fueled by the convergence of machine learning models, internet-scale data, and large training infrastructures. Vision-Language Models (VLMs) have enabled unprecedented progress in aligned vision-language processing, while Vision-Language-Action (VLA) models and deep reinforcement learning (RL) […] |
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The next generation of space structures demands unprecedented multifunctionality, incorporating capabilities to morph, adapt, sense, communicate, generate and manage energy, and process information. Realizing ultra-large space infrastructures, such as space solar farms, orbital data centers, and human habitats, requires breakthrough advances in in-space structural assembly and manufacturing (ISAM). This presentation will highlight several projects aimed […] |
2 events,Multi-agent systems are increasingly deployed autonomously in complex, real-world environments. Yet the black-box nature of deep policy learning approaches — despite their universal approximation power enabling coordinated, emergent behaviors — poses significant hurdles for ensuring scalability and safety. How can learned robot policies respect the underlying physics and geometry of the systems they control ? […]
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There are many ways science can go wrong. Our studies are too small. We confuse correlation with causation. We are biased. Our hypotheses are not fairly tested. We overfit. We misunderstand the literature. Our data is not shared. And, arguably, much of this could be avoided with better planning. Which is exactly why our P.I., […] |
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How does living matter acquire its physical form? Living cells and tissues are active materials that generate forces, undergo large deformations, and collectively self-organize into robust structures. Understanding and predicting the mechanics of such active matter, from single cells to multicellular systems, calls for new approaches grounded in mechanics and in close conjunction with biological […]
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AI + SCIENCE SEMINAR: Creativity by Compositionality in Generative Diffusion Models Diffusion models have shown remarkable success in generating high-dimensional data such as images and language – a feat only possible if data has strong underlying structure. Understanding deep generative models thus requires understanding the structure of the data they learn from. In particular, natural […] |
5 events,
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Oversight and auditing of AI systems is becoming increasingly difficult as people use systems in a wide variety of ways, with instructions expressed in natural language prompts. We can no longer use readily quantifiable metrics like accuracy or statistical parity to understand model performance and potential impacts. Instead, we need ways of conducting open-ended analyses […]
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The Department of Bioengineering at the University of Pennsylvania and Dr. Ravinder Reddy are pleased to announce the Doctoral Dissertation Defense of Blake Benyard. Title: "DEVELOPMENT OF LIPID-WEIGHTED NOE AND CEST MRI METHODS FOR ADVANCED NEUROIMAGING" Advisor: Dr. Ravinder Reddy Date: Wednesday, March 18, 2026 Time: 2:00 PM Location: JMB Class of '62 Hall The […]
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This talk will discuss the opportunities and progress for AI models and hardware accelerator co-design towards the goal of efficient general intelligence (EGI). Some successful examples include hierarchical memory transformer (HMT), lookup-table (LUT) based large-language models (LLMs) and customized acceleration of the LLM memory-processing pipeline. The talk will also present the latest research results at […] |
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The Department of Bioengineering at the University of Pennsylvania and Dr. Su Chin Heo are pleased to announce the Doctoral Dissertation Defense of Ellen Zhang. Title: "Single-Nucleus Multi-Omics Approaches to Enhance Cartilage Repair" Advisor: Dr. Su Chin Heo Date: Thursday, March 19, 2026 Time: 9:00 AM Location: Biomedical Research Building (BRB) Room 252 Zoom: https://pennmedicine.zoom.us/my/suchinheo […]
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The Department of Bioengineering at the University of Pennsylvania and Dr. Su Chin Heo proudly announce the Doctoral Dissertation Defense of Ellen Zhang. Title: Single-Nucleus Multi-Omics Approaches to Enhance Cartilage Repair Date and time: 03/19/2026 at 9am Location: Biomedical Research Building (BRB) Room 252 Zoom link for online participants: https://pennmedicine.zoom.us/my/suchinheo. The public is welcome to […]
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Dynamic biomaterials exhibit highly useful properties that are impossible with traditional materials but crucial for a wide variety of emerging applications in biomedicine. These materials typically employ enthalpy-dominated crosslinking interactions that become weaker at elevated temperatures, leading to significant softening. Herein, we will discuss the development of a physical hydrogel platform exploiting dynamic and multivalent […] |
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2 events,
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The Department of Bioengineering at the University of Pennsylvania and Dr. Dani Bassett are pleased to announce the Doctoral Dissertation Defense of Xiaohuan Xia. Title: Computational and Multidisciplinary Perspectives on Modeling Individual and Collective Human Behavior Date: March 23, 2026 Time: 9 AM Location: Room 225 Towne Building Zoom option: https://upenn.zoom.us/j/3010037731 Meeting ID: […]
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Please note important updates on date an location to this seminar: The session will not take place on its usual Thursday, but has been rescheduled to Monday, March 23, at noon. The new location is the Glandt Forum, Singh Center for Nanotechnology. Lunch will be served in Glandt Forum at 1pm. All meetings with speaker will still be in AGH. […] |
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Reservoir computing is an information processing paradigm within which the nonlinear dynamics of a system are exploited to perform information processing. While originally proposed in the context of artificial and biological neural network dynamics, computing via dynamics has been shown to be applicable to a wide range of systems. Of note are physical reservoir computers, […] |
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“Synthesize a realistic electrocardiogram (ECG) from a patient’s medical record to stress-test a disease classifier while preserving privacy.” “Forecast home energy demand given location, EV usage, and an incoming winter freeze.” “Retrieve all instances where a self-driving car executed an unprotected left near a truck and an accident followed within ten minutes.” These tasks require […] |
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Abstract: Whereas human tissues and organs are mostly soft, wet, and bioactive, machines are commonly hard, dry, and abiotic. Merging humans and machines is of critical importance in addressing grand societal challenges in AI, health, environment, security, education, and happiness in life. However, merging humans and machines is extremely challenging due to their fundamentally contradictory […] |
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Abstract: Future aerospace platforms, from aerial systems and spacecraft, need to meet rising demands for acoustic and electromagnetic interference (EMI) mitigation, operation in harsh environments, and payload maximization, all while reducing mass. In this talk, we will discuss our work addressing some of these challenges by uniting biological design principles with machine intelligence to create […]
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The Cora Ingrum Center is thrilled to invite you to the Celebration of Community. This annual event showcases Penn Engineering students, staff, faculty, and alumni in their multi-talented richness. The program will consist of guest speakers, performances, presentations from student and outreach organizations, and mouthwatering dishes from around the globe. Fill out the form linked […] |
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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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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 […] |
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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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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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