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        "event_title":"Resume Lab",
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        "description":"*RSVP required to attend. Click \"Join Event\" here: https:\/\/app.joinhandshake.com\/events\/1532024\/share_preview\n\nJust getting started building a resume? Have a draft but not sure how to make it better? Want to learn about resources available to revise your resume? Wherever you\u2019re at Resume Lab is a great next step for you.\n\nGet real-time, personalizedsupport in a small group setting by checking out the Resume Lab. \n\nWe will discuss and educate you on\u2026\n- Design and format\n- Writing a great bullet point\n- Targeting your resume for specific internships\/jobs\n\nIf you're a Graduate Student or Recent Grad, please make a 1:1 appointment instead of attending the Lab because this event is designed for undergraduates.\n\nNote: This event's information is shown in Handshake as well as onthe Happening @ Michigan calendar so that it will be seen by a larger number of U-M Students. If you'd like to indicate that you'll be attending this event then please go to: https:\/\/umich.joinhandshake.com\/edu\/events\/1452770",
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        "event_title":"Safety Benchmarking of Automated Driving Systems: The Challenges of Apples to Apples Comparison",
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        "combined_title":"Safety Benchmarking of Automated Driving Systems: The Challenges of Apples to Apples Comparison: Carol Flannagan, Ph.D.",
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        "description":"Current Automated Driving Systems (ADS) have reached the point of fully driverless deployments and even carrying passengers, so the question being asked is \u201cAre ADS safer than humans?\u201d This question turns out to be hard to answer because: 1) human-driver data systems were built to answer a different set of questions, and 2) ADS are being deployed in specific ODDs such that their crash rates may not be directly comparable to human-driver crash rates developed from national datasets. In this talk, Dr. Carol Flannagan will explore \u201cApples to Apples\u201d safety comparisons between ADS and human drivers. What would the perfect comparison look like? What has been done? What are the challenges to achieving the perfect comparison and what can be done about it? Finally, what reasonable compromises can be made to prevent the perfect from becoming the enemy of the good?\r\n---\r\nAbout the speaker: \r\nDr. Flannagan has over 30 years of experience conducting data analysis and research on injury risk related to motor vehicle crashes. Her recent work on crash-avoidance technologies includes the application of statistical methods to estimate the effectiveness and potential benefits of crash-avoidance technologies as well as the safety assessment of automated driving systems (ADS). Dr. Flannagan\u2019s work often involves the fusion and analysis of large state- and national-level databases, including crash, EMS, and hospital data. These fused databases are useful in analyzing the effect of a wide variety of countermeasures on crash involvement and injury risk. Finally, Dr. Flannagan has worked to develop and apply a wide variety of new and old statistical approaches, such as natural language processing, Bayesian methods, and causal inference methods to address transportation data issues and answer transportation research questions.",
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