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        "event_title":"Gilbert S. Omenn Department of Computational Medicine and Bioinformatics",
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        "combined_title":"Gilbert S. Omenn Department of Computational Medicine and Bioinformatics: Morgan E. Levine, PhD (VP of Computation, Altos Labs in San Diego, CA) presents, \"Origins of Life & Death: Aging as an Out of Distribution Problem\"",
        "event_subtitle":"Morgan E. Levine, PhD (VP of Computation, Altos Labs in San Diego, CA) presents, \"Origins of Life & Death: Aging as an Out of Distribution Problem\"",
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        "description":"Abstract:\r\nEvolution was able to produce living systems with unfettered complexity, solely by optimizing a simple emergent feature\u2014reproductive fitness. In many ways, this task shares features with learning in machine systems allowing us to draw parallels between evolution and deep neural networks. One of the keys to successful learning in both artificial and living systems is training in the context of variable conditions, and it is this limitation that I propose as a theoretical underpinning of the phenomenon of biology aging. While Darwinian Evolution elegantly hints at how the highly ordered complex structures that define living matter evolved, we are still left wondering why such systems inevitably perish. Many theories have been proposed over the years that can generally be grouped into three categories: programmed, damage-based, or quasi-programmed. I propose a novel theory of aging that falls in the category of quasi-programmed, yet at the same time, frames quasi-programmed theories in the context of optimization constraints in living systems. In essence, I propose the following: that the programs employed by living systems have been highly optimized for fitness via selection. However, as with AI models, successful performance in these systems is predicated on the context to which they were trained. As described by proponents of evolutionary theories, the forces of natural selection decline with age and from this perspective, one can also frame this as a dearth of exposure to the context of old age during \u201cevolutionary training\u201d. Thus, the systems will still employ the policies it had learned under the training contexts (e.g. the young organismal state with high fitness potential), however these policies can be inappropriate or even detrimental under the never-before-seen context (e.g. the old organism with low fitness potential). Finally, I will discuss the application of multi-scale AI\/ML models for capturing the complex phenomena of aging and learning how to optimize health.",
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        "event_title":"Intern Abroad Info Sessions - CGIS Internship Programs",
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        "event_title":"Leveraging Your Engineering Degree at MathWorks",
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        "event_type":"Careers \/ Jobs",
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        "description":"Are you an engineering student curious about a career at a software company? Wonder where your skills fit in?Join MathWorks for an insightful session on \"How to Leverage Your Engineering Degree at a Software Company.\" Hear directly from our Engineering Development Group (EDG) members and alumni who have successfully used their engineering expertise into thriving careers at a software company.What to Expect:\u2022 Real Stories: Learn how our EDG members and alumni navigated using their engineering skills in school to putting then into practice at a software company.\u2022 Interactive Session: Engage with current MathWorkers in a dynamic discussion about career growth and opportunities.\u2022Supportive Environment: Experience our culture that promotes innovation,collaboration, continuous learning, and fun.\u2022 Live Q&amp;A: Have your questions addressed directly by professionals who've been in yourshoes.\u2022 Networking Opportunities: Connect with MathWorks employees and learn about potential career paths and opportunities within the company.Ready to Explore Your Potential?Don't miss this unique opportunity to gain insights and advice from those who've successfully leveraged their engineering degrees at MathWorks.",
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        "event_title":"Lunar New Year",
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        "combined_title":"Lunar New Year",
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        "event_type_id":"22",
        "description":"Celebrate the Lunar New Year at the dining halls! The Michigan Dining team is honoring the Lunar New Year with decorations and innovative recipes.\r\n\r\nThis event is included with your residential meal plan. Those with block plans can use a meal swipe to enter. All other guests will pay the door rate to dine in the dining halls.",
        "occurrence_notes":"Dining Halls Across Campus",
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        "event_title":"Probability and Analysis Seminar: A quasi-invariant group action on SLE loops",
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        "combined_title":"Probability and Analysis Seminar: A quasi-invariant group action on SLE loops: Jinwoo Sung (University of Chicago)",
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        "description":"Conformal welding is an operation that encodes a large class of Jordan curves on the Riemann sphere, including the loop version of Schramm\u2013Loewner evolution (SLE), in terms of circle homeomorphisms. In this talk, I will discuss a Cameron\u2013Martin type quasi-invariance result for the SLE loop measure under the right group action by Weil\u2013Petersson circle homeomorphisms on the welding homeomorphism. While this result was hinted at by Carfagnini and Wang's identification of the Onsager\u2013Machlup action functional of the SLE loop measure with the K\u00e4hler potential of the unique right-invariant K\u00e4hler metric on the group of Weil\u2013Petersson circle homeomorphisms (Loewner energy), the group structure of SLE welding has been little understood previously. Our proof is based on the characterization of the composition operator associated with Weil\u2013Petersson circle homeomorphisms using Hilbert\u2013Schmidt operators and the description of the SLE loop measure in terms of the welding of two independent quantum disks by Ang, Holden, and Sun. This is joint work with Shuo Fan (Tsinghua University and IHES).",
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