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    • CIS Seminar: “Bridging Informal and Formal AI Reasoning”

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    Wu and Chen Auditorium (Room 101), Levine Hall 3330 Walnut Street, Philadelphia, PA, United States

    Neural language models have opened a fascinating, flexible platform for reasoning in mathematics, programming, and beyond. This talk will explore the intersection of these models and the rigor of formal reasoning. First, I discuss my work on building foundation models for mathematics and using language to guide the search for formally verified proofs. Then, I […]

    PICS Colloquium: Powering decarbonization with modeling and optimization of renewables in the multi-scale atmosphere

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    PICS Conference Room 534 - A Wing , 5th Floor 3401 Walnut Street, Philadelphia, PA, United States

    To meet net-zero carbon emissions targets by mid-century, up to a -fold increase in wind power capacity is required. Acceleration to this rate requires urgent improvements to efficiency and reliability of installed wind farms, as well as cost reductions for future offshore farms. To expand energy production, wind turbines are rapidly increasing in size, wind […]

    MEAM Seminar: “Miniaturized Robots and Probes for Precision Health”

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    Wu and Chen Auditorium (Room 101), Levine Hall 3330 Walnut Street, Philadelphia, PA, United States

    Designing miniaturized robots and bioelectronic devices will enable access throughout the entire human body, leading to novel procedures at the cellular level and offering localized diagnosis and treatment with unprecedented precision and efficiency. However, the soft, complex, and multi-dimensional nature of biological systems poses significant challenges for mechanical design, manufacturing, materials engineering, and functional integration […]

    ESE Spring Seminar – “AI as a Lens: Expanding Vision for Scientific Discovery”

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    Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

    Conventional approaches to scientific discovery often prioritize building larger sensors, gathering more data, and scaling up computational power. In this talk, I will present a complementary perspective: extracting insights hidden in the data we already have. The key lies in using AI not as a black-box predictor, but as a tool for interpreting data through […]

    CIS Seminar: “Efficient Probabilistically Checkable Proofs from High-Dimensional Expanders”

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    Amy Gutmann Hall, Room 414 3333 Chestnut Street, Philadelphia, United States

    The PCP theorem, proved in the 90’s, shows how to encode a proof for any theorem into a format where the theorem's correctness can be verified by making only a constant number of queries to the proof. This result is a significant milestone in computer science and has important implications for approximation algorithms, cryptography, and […]

    MEAM Seminar: “Real-Time Safe and Energy-Efficient UAV Motion Planning in Windy Urban Environments”

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    Towne 319 220 S. 33rd Street, Philadelphia, United States

    Recent advancements in hardware and software are bringing autonomous aerial vehicles closer than ever to finally delivering on futuristic visions of flying cars and package delivery drones. However, the safe deployment of autonomous aircraft at scale in urban environments poses significant challenges, one of which being uncertainties contributed by complex spatial and temporal winds. Clusters […]

    ASSET Seminar: “Demystifying the Inner Workings of Language Models”

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    Amy Gutmann Hall, Room 414 3333 Chestnut Street, Philadelphia, United States

    Abstract: Large language models (LLMs) power a rapidly-growing and increasingly impactful suite of AI technologies. However, due to their scale and complexity, we lack a fundamental scientific understanding of much of LLMs’ behavior, even when they are open source. The “black-box” nature of LMs not only complicates model debugging and evaluation, but also limits trust […]

    Spring 2025 GRASP SFI: Qinghua Liu, Microsoft Research, “When Is Partially Observable Reinforcement Learning Not Scary?”

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    Levine 307 3330 Walnut Street, Philadelphia, PA, United States

    This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Partial observability is ubiquitous in Reinforcement Learning (RL) applications, where agents must make sequential decisions despite lacking complete information about the latent states of the controlled system. Partially observable RL is notoriously challenging in theory—well-known information-theoretic results […]

    CBE & BE Seminar: “Targeting the Brain and Behavior to Probe the Dynamics of Aging” (Claire Bedbrook, Stanford University)

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    Wu & Chen Auditorium

    Bio & Abstract: Claire Bedbrook is an engineer and neuroscientist working to extend lifespan by modulating the brain. Claire was trained in chemical engineering at the University of California, Berkeley. She completed her Ph.D. in Bioengineering at the California Institute of Technology with Professor Frances Arnold and Professor Viviana Gradinaru, where she engineered molecular tools […]

    ESE Spring Seminar – “Quantum Simulation of Electronic Materials with a Superconducting Qubit Array”

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    Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

    Arrays of coupled superconducting qubits are a compelling platform for analog quantum simulations of solid-state matter and many-body physics. These devices natively emulate the Bose-Hubbard model while offering a high degree of control, fast operation rates, and site-resolved readout. We discuss recent experiments using a 4-by-4 array of transmon qubits. By adopting a parametric coupling […]

    IDEAS/STAT Optimization Seminar: “Theoretical foundations for multi-agent learning”

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    Amy Gutmann Hall, Room 414 3333 Chestnut Street, Philadelphia, United States

    As learning algorithms become increasingly capable of acting autonomously, it is important to better understand the behavior that results from their interactions. For example, a pervasive challenge in multi-agent learning settings, which spans both theory and practice and dates back decades, has been the failure of convergence for iterative algorithms such as gradient descent. Accordingly, […]

    CIS Seminar: “Learning Theoretic Foundations for Modern (Data) Science”

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    Levine 307 3330 Walnut Street, Philadelphia, PA, United States

    In this talk, I will explain how fundamental problems in computational learning theory are at the heart of modern problems in machine learning and scientific applications and how algorithmic insights in mathematically tractable models can inspire new solutions in a wide variety of domains. I will explore two directions. First, I will explore algorithmic foundations […]