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DTSTART:20070311T020000
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DTSTAMP:20260513T084945
DTSTART;TZID=America/Detroit:20260526T130000
DTEND;TZID=America/Detroit:20260526T150000
SUMMARY:Lecture / Discussion:Statistical Foundations for Microplastic Identification: Efficient Sampling and Distribution-Free Uncertainty Quantification
DESCRIPTION:Microplastics are an emerging pollutant of global concern\, with environmental particles documented across the world. Reliable identification of microplastic particles is essential for quantifying their prevalence and assessing environmental exposure\, yet current spectroscopic identification pipelines face several statistical challenges. Measurements can be costly and time-consuming\, commonly used spectral matching procedures often lack formal guarantees\, and environmental samples can vary over time and across locations. This dissertation develops statistical and machine learning methods for adaptive sampling and uncertainty quantification\, with a focus on improving the reliability and efficiency of microplastic spectral identification.\n\nFirst\, we study adaptive sampling through pure exploration problems in logistic bandits. We introduce Logistic Track-and-Stop\, the first track-and-stop algorithm for general pure exploration problems under a logistic bandit model. The method combines adaptive sampling with a stopping rule based on generalized likelihood ratio statistics and asymptotically matches an approximation to the instance-specific lower bound on expected sample complexity.\n\nSecond\, we develop and apply conformal prediction methods for microplastic spectral identification. We first apply conformal prediction to popular database matching pipelines\, highlighting the limitations of practitioner-selected similarity thresholds. We then extend the conformal prediction framework to ensemble and multi-view settings by aggregating nonconformity scores across multiple models or data modalities. In particular\, we apply multiview conformal prediction to photothermal infrared and Raman spectra\, producing more efficient and robust prediction sets than those obtained from single-view methods.\n\nThird\, we study online conformal prediction across multiple coverage levels. We leverage online optimization algorithms to enforce nestedness of prediction sets across the full risk spectrum while controlling quantile estimation error. Beyond improving interpretability\, jointly estimating multiple coverage levels can improve statistical efficiency by enforcing non-crossing constraints and sharing information across quantiles.\n\nTogether\, these contributions provide tools for accelerating microplastic identification and improving the reliability of the resulting scientific conclusions.
UID:148254-21903452@events.umich.edu
URL:https://events.umich.edu/event/148254
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Dissertation
LOCATION:West Hall - 438
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260330T091858
DTSTART;TZID=America/Detroit:20260526T140000
DTEND;TZID=America/Detroit:20260526T150000
SUMMARY:Workshop / Seminar:Accessibility in Action: Building an Inclusive Community at U-M
DESCRIPTION:This workshop will guide us through the ways accessibility shapes equity on campus and beyond. We’ll explore why disability matters\, define key concepts like ableism\, discuss universal design\, language and etiquette\, workplace accommodations\, and the role of the Disability Equity Office. Together\, we’ll learn how accessibility benefits everyone — not just those with disabilities.\n\nAmerican Sign Language (ASL) interpreting services and Communication Access Realtime Translation (CART) captioning services will be provided. If you need additional accommodations to participate in this webinar\, please email the ADA Coordinator at ADAcoordinator@umich.edu.
UID:146705-21899510@events.umich.edu
URL:https://events.umich.edu/event/146705
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Disability,Diversity,Discussion,Digital Accessibility,Communication,Accessibility,Workshop,Virtual,Neurodiversity,Inclusion
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260524T162022
DTSTART;TZID=America/Detroit:20260526T140000
DTEND;TZID=America/Detroit:20260526T150000
SUMMARY:Workshop / Seminar:Summer 2026 Workshop Series
DESCRIPTION:Join CAEN for a series of workshops designed to transform how you research\, teach\, and work using the University of Michigan’s 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.  Secure & Private: All workshops utilize U-M’s GenAI services\, ensuring your prompts and data are never used to train external models.
UID:147694-21901611@events.umich.edu
URL:https://events.umich.edu/event/147694
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Sessions
LOCATION:
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260519T101823
DTSTART;TZID=America/Detroit:20260526T153000
DTEND;TZID=America/Detroit:20260526T170000
SUMMARY:Lecture / Discussion:Structured Statistical Learning and Inference for Complex Scientific Data
DESCRIPTION:This dissertation develops structured statistical learning and inference methods for complex scientific data. Here\, structure refers to problem-specific patterns that can be modeled to improve learning or inference: cluster-specific abundance and presence--absence patterns in microbiome compositions\, modular organization in high-dimensional conditional dependence networks\, and the conditional predictive structure among outcomes\, covariates\, and black-box predictions. Modeling such structure can improve clustering\, network learning\, and inference while preserving interpretability and statistical validity.\n\nThe first part studies model-based clustering of microbiome compositional data. We develop an Ising-Dirichlet mixture model for zero-inflated compositions\, where each cluster has a presence--absence dependence structure and a nonzero abundance profile. The method is designed to improve clustering with limited samples by using information from both taxon occurrence patterns and relative abundance variation. Simulations and a resistant potato starch study show improved clustering accuracy and interpretable microbiome subgroups.\n\nThe second part studies variable clustering in high-dimensional graphical models. We develop a one-step joint estimation framework for a sparse precision matrix and a latent variable partition. This allows graph estimation and partition recovery to reinforce each other\, rather than clustering a separately estimated graph. The method treats the partition as an explicit estimation target and allows nonzero cross-cluster dependence\, relying on a modularity criterion in which within-cluster connectivity is denser than between-cluster connectivity. Simulations and real-data applications show more stable and interpretable graph-and-cluster representations than two-stage alternatives.\n\nThe third part studies statistical inference with limited gold-standard labels and abundant black-box predictions. Because these predictions are not ground truth\, valid use requires bias correction. We develop adaptive prediction-powered inference\, which learns a score-side adjustment from labeled data to approximate the variance-optimal conditional score adjustment through Taylor-based and ensemble-based constructions. Simulations and real-data examples show that the method preserves coverage while producing smaller confidence regions than existing prediction-powered and surrogate-adjustment methods.
UID:148340-21903957@events.umich.edu
URL:https://events.umich.edu/event/148340
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Dissertation
LOCATION:Off Campus Location
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260519T131502
DTSTART;TZID=America/Detroit:20260526T160000
DTEND;TZID=America/Detroit:20260526T171500
SUMMARY:Workshop / Seminar:LSA Transfer Information Session
DESCRIPTION:Join the LSA Transfer Recruitment Team for our virtual sessions where we will discuss LSA requirements\, transfer credit\, pre-transfer academic advising\, LSA opportunities and other transfer tidbits.\n\nRegistration is required. Register using link to the right
UID:141040-21902621@events.umich.edu
URL:https://events.umich.edu/event/141040
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Transfer Students
LOCATION:Off Campus Location
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20250925T095602
DTSTART;TZID=America/Detroit:20260526T170000
DTEND;TZID=America/Detroit:20260526T183000
SUMMARY:Well-being:Virtual Dialectical Behavior Therapy (DBT) Group for Adults
DESCRIPTION:Are you looking to gain better control of your thoughts and emotions? Our Psychological Clinic invites adults 18 and older to participate in our weekly Dialectical Behavior Therapy (DBT) group sessions\, held virtually for your convenience. Learn practical skills for managing anxiety\, depression\, and challenging situations with the support of experienced clinicians and peers.\n\nWhy Choose DBT Group Therapy?\nGroup sessions offer unique benefits\, including opportunities to learn new techniques\, share experiences\, and build supportive connections. You’ll develop practical skills in mindfulness\, emotion regulation\, interpersonal effectiveness\, and distress tolerance—essential tools for managing strong emotions and handling stress. Research shows that connecting with peers in a supportive group environment encourages real-world growth\, accountability\, and lasting change.\n\nProgram Details:\n- Who: Adults 18+ interested in building coping skills\, managing emotions\, and improving relationships.\n- When: Tuesdays from 5:00 – 6:30 p.m. (via Zoom).\n- Structure: The program runs in ongoing 4-month cycles\, each focusing on a different theme.\n- Flexible Start: New participants can join at the first Tuesday session of any month.\n- Cost: $45 per session (insurance may help cover costs).
UID:139870-21886256@events.umich.edu
URL:https://events.umich.edu/event/139870
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Depression,Undergraduate Students,Undergraduate,Staff,mental health,Health & Wellness,Graduate Students,Graduate and Professional Students,Graduate,anxiety
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260524T162022
DTSTART;TZID=America/Detroit:20260526T173000
DTEND;TZID=America/Detroit:20260526T183000
SUMMARY:Conference / Symposium:NORTHWOOD 2025-2026
DESCRIPTION:
UID:135675-21902645@events.umich.edu
URL:https://events.umich.edu/event/135675
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Sessions
LOCATION:Northwood Community Center (1000 McIntyre)
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260524T162021
DTSTART;TZID=America/Detroit:20260526T180000
DTEND;TZID=America/Detroit:20260526T190000
SUMMARY:Conference / Symposium:East Quad (Spring/Summer 2026) (Housing)
DESCRIPTION:
UID:147859-21904158@events.umich.edu
URL:https://events.umich.edu/event/147859
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Sessions
LOCATION:4217 Lounge, Abeng Multicultural  Lounge
CONTACT:
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