BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//UM//UM*Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/Detroit
TZURL:http://tzurl.org/zoneinfo/America/Detroit
X-LIC-LOCATION:America/Detroit
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20070311T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20071104T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260814T125611
DTSTART;TZID=America/Detroit:20261008T130000
DTEND;TZID=America/Detroit:20261008T143000
SUMMARY:Workshop / Seminar:Data Accessibility
DESCRIPTION:Tutorial Overview\nFocus: Using AI to improve access to\, understanding of\, and readiness for working with data.\n\nThis session would focus on helping researchers navigate the early stages of working with data\, especially when datasets are large\, complex\, poorly documented\, or unfamiliar. AI can assist with interpreting data dictionaries\, summarizing metadata\, identifying missing documentation\, and making datasets more approachable for new users.\n\nPossible hands-on activities:\n\nSummarize a dataset description or codebook into plain language\nGenerate a checklist for evaluating whether a dataset is usable for a project\nIdentify likely data limitations or missing documentation\nDraft questions to ask a data provider or collaborator\nUse AI to map dataset fields to possible research questions\nReminder: All attendees\, please bring a laptop.
UID:150270-21908495@events.umich.edu
URL:https://events.umich.edu/event/150270
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data Management,Academic Technology At Michigan,Ai Literacy,Artificial Intelligence,data,Data Analysis,Data Science,Genai,information,school of information
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20261002T212122
DTSTART;TZID=America/Detroit:20261008T130000
DTEND;TZID=America/Detroit:20261008T143000
SUMMARY:Workshop / Seminar:Data Accessibility
DESCRIPTION:Description:This session focuses on the early stages of working with data\, when a dataset is large\, complex\, poorly documented\, or unfamiliar. Participants will use AI to interpret data dictionaries\, surface undocumented assumptions\, and assess whether a dataset can answer their research question. They will also learn how to determine which AI tools they are permitted to use with a given dataset\, since research data frequently carries terms of use that restrict AI tools. Participant exercises use a public-domain dataset and U-M's own AI services.- ICPSR policy on the use of large language models: https://www.icpsr.umich.edu/sites/icpsr/about/policies/large-language-models-and-ai\n- ICPSR redistribution policy: https://www.icpsr.umich.edu/sites/icpsr/about/policies/redistribution\n- Using AI with MIDUS\, NSHAP\, Add Health and other NACDA-hosted data: https://www.icpsr.umich.edu/sites/icpsr/news/using-ai-with-midus-nshap-add-health-and-other-nacda-hosted-data\n- U-M guidance on AI and U-M data: https://safecomputing.umich.edu/protect-the-u/safely-use-sensitive-data/AI-and-UM-Data\n- U-M generative AI services: https://genai.umich.edu/\n- ACS PUMS documentation: https://www.census.gov/programs-surveys/acs/microdata/documentation.htmlPossible hands-on activities:- Determine which tier of AI tool you may use with a dataset you are currently working with\, and where to check\n- Translate a cryptic codebook into plain language\, with the model flagging what it cannot determine instead of guessing\n- Extract documentation into a structured format that records\, field by field\, what the model could not determine from the documentation alone\n- Generate a fitness-for-purpose checklist against your own research question\, and draft specific questions to send a data provider\nBefore the session:1. All attendees please bring a laptop.2. Sign in at genai.umich.edu to make sure your U-M GPT access is working. We'll use it for all hands-on exercises. 3. Come with a research question you're working on\, and the name of a dataset you're using or considering for it. If the dataset has a data use agreement or terms of use page\, have the link handy. Please don't plan to upload your own data during the session. We'll use a public dataset for the exercises\, and part of the session covers how to check which AI tools you're permitted to use with your own data.\n\n
UID:149474-21906466@events.umich.edu
URL:https://events.umich.edu/event/149474
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Sessions
LOCATION:Michigan Union (530 S. State Street, Ann Arbor, MI 48109) - First Floor - Anderson Room ABC.
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260901T143031
DTSTART;TZID=America/Detroit:20261008T130000
DTEND;TZID=America/Detroit:20261008T143000
SUMMARY:Lecture / Discussion:Environmental Humanities Workshop
DESCRIPTION:We will discuss portions of John Bellamy Foster’s *Marx’s Ecology* to generate discussion among EHW and the more social sciences aspect of environmental studies. Read whatever you can and are interested in and join us for what is sure to be a generative conversation.\n\nRSVP here: https://sessions.studentlife.umich.edu/track/event/session/112291\n\nWhether you consider yourself a seasoned Environmental Humanist or you are simply curious about the field\, we hope to see you there! Feel free to bring friends and circulate our programming to anyone else you think might be interested.
UID:151327-21911379@events.umich.edu
URL:https://events.umich.edu/event/151327
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:English Language And Literature,Social Sciences,Humanities,Environment
LOCATION:Angell Hall - 3241
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260930T163122
DTSTART;TZID=America/Detroit:20261008T130000
DTEND;TZID=America/Detroit:20261008T140000
SUMMARY:Social / Informal Gathering:HFES x INFORMS Coffee Chat
DESCRIPTION:Come join us in the IOE Community Suite for some coffee and networking!
UID:153139-21915139@events.umich.edu
URL:https://events.umich.edu/event/153139
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Undergraduate Students,Undergraduate,Industrial And Operations Engineering,Graduate
LOCATION:Industrial and Operations Engineering Building - Community Suite
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20261002T212103
DTSTART;TZID=America/Detroit:20261008T130000
DTEND;TZID=America/Detroit:20261008T140000
SUMMARY:Workshop / Seminar:Laser Training
DESCRIPTION:You must complete FABLab Safety Training and have watched the Laser cutter training video before attending this session!
UID:152896-21915468@events.umich.edu
URL:https://events.umich.edu/event/152896
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Sessions
LOCATION:Taubman College Laser Cutter Room
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20261002T212122
DTSTART;TZID=America/Detroit:20261008T130000
DTEND;TZID=America/Detroit:20261008T143000
SUMMARY:Workshop / Seminar:Marx's Ecology Reading and Discussion
DESCRIPTION:We will discuss portions of John Bellamy Foster’s Marx’s Ecology to generate discussion among EHW and the more social sciences aspect of environmental studies. Read whatever you can and are interested in and join us for what is sure to be a generative conversation.
UID:150232-21908430@events.umich.edu
URL:https://events.umich.edu/event/150232
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Sessions
LOCATION:Angell Hall 3241
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20261001T003552
DTSTART;TZID=America/Detroit:20261008T130000
DTEND;TZID=America/Detroit:20261008T142000
SUMMARY:Workshop / Seminar:Numerical Analysis of Test Optimality
DESCRIPTION:In nonstandard testing environments\, researchers often derive ad hoc tests with correct (asymptotic) size\, but their optimality properties are typically unknown a pri- ori and difficult to assess. This paper develops a numerical framework for determining whether an ad hoc test is effectively optimal—approximately maximizing a weighted average power criterion for some weights over the alternative and attaining a power en- velope generated by a single weighted average power–maximizing test. Our approach uses nested optimization algorithms to approximate the weight function that makes an ad hoc test’s weighted average power as close as possible to that of a true weighted average power–maximizing test\, and we show the surprising result that the rejection probabilities corresponding to the latter form an approximate power envelope for the former. We provide convergence guarantees\, discuss practical implementation and ap- ply the method to the weak-instrument–robust conditional likelihood ratio test and a recently-proposed test for when a nuisance parameter may be on or near its boundary.
UID:151821-21912227@events.umich.edu
URL:https://events.umich.edu/event/151821
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Economics,seminar,Econometrics
LOCATION:North Quad - 4300
CONTACT:
END:VEVENT
END:VCALENDAR