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        "event_title":"Practice Behavior-Based Interviewing Using Virtual Reality",
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        "combined_title":"Practice Behavior-Based Interviewing Using Virtual Reality: Presenter: Talent Acquisition",
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        "tags":["Human Resources","Professional Development","Communication"],
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        "event_title":"Swap Shop 2nd Birthday Party",
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        "description":"The Lab Swap Shop, launched in June 2024, serves as a physical location where excess lab consumables, glassware, equipment, and more can be rehomed within the U-M research community. Join us on June 4th from 1-3pm in room 5004 of the North University Building to celebrate a successful second year of the shop! Key milestones include more than a million dollars saved for U-M researchers and diversion of over 20,000 pounds of supplies from the landfill. Bring the Swap Shop a birthday present of surplus lab supplies, engage in creative reuse crafts, take home a free air plant while supplies last, and enjoy a slice of birthday cake! Check out our inventory to get an idea of available items!",
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        "tags":["Sustainability","Waste Reduction","Research"],
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        "combined_title":"Combinatorial Optimization Problems Arising from Graph-Based Models: Samuel Boardman",
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        "description":"Abstract:\n\nWe propose and analyze several graph-defined combinatorial optimization problems inspired by multiple application areas.  \n\nFirst, we consider an influence maximization model that uses the independent cascade approach, but allows two types for packets of information, +1 and -1. These represent the change in a receiver's sentiments on a product or belief on an empirical question (regarded as their \"bias\"), which can be justified via Bayes' rule. The algorithmic problems we study may be viewed as taking a more fine-grained approach to traditional influence maximization problems, and correspondingly exhibit non-trivial behavior even in the unbudgeted version where packets are unlimited\u2014including tractability that depends on the probability parameters of the independent cascade dynamics. On the other hand, we obtain NP-hardness results for the budgeted version more analogous to previous work. Several natural heuristics are shown to induce substantial reductions of bias in simulations with well-known social network datasets.  \n\nNext, given an undirected graph representing similarities between a set of items and an additive measure evaluating them, we treat the position of a special subset of items in an ordinal ranking through a collection of problems in which items may be combined if they are similar. The objective for these problems is to either maximize or minimize the absolute or relative rank of the special subset, with a meta-goal of assessing the robustness of the rank, even in the presence of a well-defined criterion. We classify the computational complexity of all four problems, mostly finding worst-case hardness, then find exact and approximate solutions to special cases and variants of the problems. These structured cases are inspired by numerous real-world examples and may be used to assess commonly cited facts across disparate domains, as we demonstrate for sources of greenhouse gas emissions that contribute to climate change. We then adapt our framework to require subsets of comparable measure, converting the above ranking problems into redistricting problems, with analogues to the former's grid variants. Emphasis is placed on worst-case deviations from proportional representation and an urban-rural model in which gerrymandering ability is curtailed.",
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        "tags":["Mathematics","Graduate Students","Graduate","Dissertation"],
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    {
        "datetime_modified":"20260603T212019",
        "datetime_start":"20260604T140000",
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        "has_end_time":1,
        "date_start":"2026-06-04",
        "date_end":"2026-06-04",
        "time_start":"14:00:00",
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        "time_zone":"America\/Detroit",
        "event_title":"Summer 2026 Workshop Series",
        "occurrence_title":"Crafting Clarity: Engineering Effective Prompts in U-M GPT",
        "combined_title":"Summer 2026 Workshop Series: Crafting Clarity: Engineering Effective Prompts in U-M GPT",
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        "event_type":"Workshop \/ Seminar",
        "event_type_id":"21",
        "description":"Join CAEN for a series of workshops designed to transform how you research, teach, and work using the University of Michigan\u2019s secure GenAI services. Whether you are a beginner or looking to master \"Context Engineering,\" these sessions provide the frameworks and hands-on experience needed to lead in the age of AI. These workshops are open to the campus community.\u00a0\u00a0Secure & Private: All workshops utilize U-M\u2019s GenAI services, ensuring your prompts and data are never used to train external models.",
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        "event_title":"UC3M Group Advising Session",
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        "event_type":"Workshop \/ Seminar",
        "event_type_id":"21",
        "description":"This UC3M Group Advising session is for students applying to study abroad in Winter 2027. We recommend attending sessions earlier in the summer if possible.\u00a0\u00a0If you are still comparing or exploring options, you may benefit\u00a0 from meeting with an\u00a0IPE peer advisor\u00a0or scheduling a1:1 advising appointment\u00a0with the UC3M Advisor.",
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        "event_title":"Virtual Pre-Health Information Sessions",
        "occurrence_title":"",
        "combined_title":"Virtual Pre-Health Information Sessions: For students who have been admitted",
        "event_subtitle":"For students who have been admitted",
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        "description":"As you embark on your journey toward a healthcare career, this Pre-Health Information Session is designed to provide you with the foundational tools and resources to help you start your time at the University of Michigan.\n\nAt the end of this session, you will be able to define how pre-health advising is utilized at the LSA Newnan Academic Advising Center, familiarize yourself with course recommendations, navigate our pre-health website, and apply resources to your pre-health journey.",
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