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    "148256-21903602":
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        "date_end":"2026-06-03",
        "time_start":"10:00:00",
        "time_end":"13:00:00",
        "time_zone":"America\/Detroit",
        "event_title":"June 1-10, 2026  MWF Course - Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences",
        "occurrence_title":"",
        "combined_title":"June 1-10, 2026  MWF Course - Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences: Heidi Guyer - RTI International",
        "event_subtitle":"Heidi Guyer - RTI International",
        "event_type":"Class \/ Instruction",
        "event_type_id":"8",
        "description":"June 1-10, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application \u2014 entirely online.\n\nData Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals, in real time, and may also reduce participant burden. In this course, we will provide examples of the utility of and integration of wearables, sensors, and apps in research settings. Examples will include the use of wearable health devices to measure activity, apps for ecological momentary assessment, and smartphone sensors to measure sound and movement, among others. Additionally, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage, participation, and measurement error when integrating wearables, sensors, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection, cross-sectional and longitudinal health surveys, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors, such as sleep and diet quality, and the development of chronic health conditions.",
        "occurrence_notes":"Registration and payment are required a minimum of two weeks prior to the start of the course.",
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        "event_title":"June 1-5, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop",
        "occurrence_title":"",
        "combined_title":"June 1-5, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop: Amanda Sonnega -  Institute for Social Research, University of Michigan",
        "event_subtitle":"Amanda Sonnega -  Institute for Social Research, University of Michigan",
        "event_type":"Class \/ Instruction",
        "event_type_id":"8",
        "description":"June 1-5, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content, sample design, weighting, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega, PhD, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM), where she is responsible for integrating communication, outreach, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health, Behavior, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health; institutional and personal factors associated with vulnerability and resilience in aging individuals; and work transitions and their broad effects on health and well-being.",
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        "tags":["Data","Data Analysis","Data Collection","Data Curation","Data Linkage","Data Management","Data Science","Health","Health And Retirement Study","Professional Development","Research","Science","Survey Methodology","Survey Methods","Survey Research"],
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        "event_title":"Privacy for Structured Data Release: Time-Discounted Continual Release and Randomized Quantization",
        "occurrence_title":"",
        "combined_title":"Privacy for Structured Data Release: Time-Discounted Continual Release and Randomized Quantization: Yutong Li",
        "event_subtitle":"Yutong Li",
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        "description":"Abstract:\n\nDifferential privacy provides a formal framework for limiting disclosure risk in computations on sensitive data. This dissertation studies differential privacy in structured data-release settings, focusing on two forms of structure: temporal structure in continual release and quantization structure in finite-level release.\n\nFirst, we propose time-discounted differential privacy (TDDP) for continual release. Standard continual-release privacy definitions do not distinguish events by temporal distance, whereas the time-discounted formulation allows privacy requirements to decay as events become older. We develop mechanisms for this setting and analyze their privacy and utility guarantees.\n\nSecond, we analyze the Random Quantization Mechanism (RQM) of Youn et al., a mechanism that provides privacy-preserving randomized quantization through subsampling. The mechanism itself is not a contribution of this thesis; rather, we derive, under specified hyperparameter calibration requirements, a formal privacy characterization of RQM, including R\u00e9nyi DP guarantees, a max-divergence\/pure-DP refinement, and reconstruction-error bounds. These results make precise privacy claims that were not explicitly established in the original presentation of the mechanism. We then study RQM as a randomized quantization procedure, focusing on how preprocessing choices affect its behavior on unbounded and heavy-tailed data.\n\nFinally, we complement the theoretical analysis with an empirical study of RQM in several new settings, beginning with private mean estimation and then considering distributional approximation, clustering, and image obfuscation. The results show that RQM is most natural when quantization is already compatible with the intended data representation, while also highlighting its sensitivity to parameter choices and application context.",
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    {
        "datetime_modified":"20260601T170313",
        "datetime_start":"20260603T100000",
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        "event_title":"Topics in Modern Machine Learning: Sequential Decision Making, High-Dimensional Statistics and Differential Privacy",
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        "combined_title":"Topics in Modern Machine Learning: Sequential Decision Making, High-Dimensional Statistics and Differential Privacy: Gang Qiao",
        "event_subtitle":"Gang Qiao",
        "event_type":"Lecture \/ Discussion",
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        "description":"Modern machine learning is increasingly applied to make reliable decisions from limited, noisy, high-dimensional, or privacy-constrained data. This dissertation studies several mathematical problems that arise from this demand, with an emphasis on sequential decision making, sparse high-dimensional inference, differential privacy, and global testing. \n\nThe first part of the dissertation concerns stochastic convex hull membership, a pure-exploration problem in which one sequentially samples from a finite collection of distributions in order to decide whether a target point belongs to the convex hull of their unknown means. We first give a complete solution in one dimension, deriving the information-theoretic characteristic time and developing Thompson-CHM, an asymptotically optimal sampling algorithm whose allocation matches the lower bound. We then further extend the whole theory to the higher-dimensional Gaussian setting, where Euclidean geometry makes the least favorable alternatives explicit. \n\nThe second part develops differentially private procedures for the Dantzig selector in high-dimensional linear regression. We start by proposing a private sparse-regression method based on a noisy iterative hard-thresholding oracle tailored to the Dantzig selector's score geometry. The algorithm preserves sparsity by construction and satisfies privacy, parameter-error, and population excess-risk guarantees, with the main error rate matching the known differentially private minimax benchmark up to logarithmic factors.  We then introduce a complementary active-set method that privatizes the Dantzig score more directly: it privately identifies violated score coordinates, refits on a restricted support, and prunes to exact sparsity.  This second approach is closer to the defining feasibility constraint of the Dantzig selector and provides an alternative route to private sparse estimation under stronger sparse-design conditions.\n\nThe final part studies sparse-signal detection in high-dimensional regression by combining two classical ideas: knockoffs and higher criticism. Knockoffs provide dependence-adaptive negative controls, while higher criticism is designed to detect rare and weak alternatives near the sharp sparse-mixture boundary. We introduce a multi-knockoff higher-criticism statistic based on Lasso entry times in an augmented design containing multiple knockoff copies per feature. In the orthogonal-design regime, the proposed statistic attains the classical higher-criticism detection boundary for sparse alternatives against the global null. This result suggests a new way to use knockoff constructions beyond false discovery rate control: as a mechanism for calibrating global tests in high-dimensional models with structured dependence.",
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        "datetime_modified":"20260511T181505",
        "datetime_start":"20260603T110000",
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        "event_title":"Fore-Site (Phase 2): The Stamps Gallery Pillar Project",
        "occurrence_title":"",
        "combined_title":"Fore-Site (Phase 2): The Stamps Gallery Pillar Project",
        "event_subtitle":"",
        "event_type":"Exhibition",
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        "description":"\n\nFrom September 2025 through November 2026, Stamps Gallery is partnering in a curatorial collaboration with two Ypsilanti-based, artist-run project spaces led by Stamps alumni: C.Y.N.K. Studios, directed by Sally Clegg (Lecturer III and Student Exhibition Coordinator, MFA \u201920) and Abhishek Narula (MFA \u201920); and Sometimes Space, directed by Nathan Byrne (Lecturer I, MFA \u201921). Each space hosts dozens of artists annually for exhibitions, performances, and events, fostering experimental work and building community. For this project, Byrne, Clegg, and Narula have been commissioned to reimagine the pillars on Division Street that flank the gallery. In response, they\u2019ve curated six artists to create new work for the pillars over three cycles:\n\nPhase 1 (September 12 - December 12) artists: Amelia Burns (Cranbrook MFA \u201923) and Erin McKenna (MFA \u201920)\nPhase 2 (January 12 - August 12) artists: Sally Clegg (MFA \u201920) and Kim Karlsrud (MFA \u201920)\nPhase 3 (September 12 - November 12) artists: Abhishek Narula (MFA \u201920) and Nathan Byrne (MFA \u201921)\nPhase 2 Curatorial Statement\n\nCurated by Sometimes Space: Sally Clegg (entry pillar)\nCurated by CYNK Studios: Kim Karlsrud (courtyard pillar)\n\nArtists Sally Clegg and Kim Karlsrud wrap the Division Street pillars in highly site-specific ornament unearthed from the overlooked margins of Ann Arbor. On the Courtyard pillar, Karlsrud scales up photographs of objects found in liminal spaces surrounding campus buildings on Green Road, which the artist has encrusted in road salt. On the entryway pillar, Clegg zooms in on tiny fragments of found material from UMich\u2019s famous \u201crock\u201d to celebrate nearly seven decades of student art and activism. Both artists uplift aggregate of local human activity to reveal tiny worlds of found form. \n\nSally Clegg: Sentimentary Rock\nSentimentary Rock is a composition of paint slag collected from the UMich rock monument at the corner of Washtenaw Avenue and Hill Street. This colorful composite material has been accumulating at the base of the iconic limestone boulder since the mid 1950\u2019s, when students began a tradition of painting it in acts of protest, creativity, and ritual, sometimes multiple times per week. Akin to byproducts of industry such as \u201cFordite\u201d (collectable chunks of automotive overspray sometimes called \u2018Detroit agate\u2019), Sentimentary Rock includes thousands of layers, each dripped from a palimpsestic public proclamation. When processed, sculpted, sealed, assembled, and macro-photographed, the result is this enlarged array of tiny gems, intended to celebrate the indissoluble student voice. \n\nKim Karlsrud: What Amasses\nWhat Amasses is an assemblage of everyday found objects collected within the Miller Creek watershed, an urbanized drainage system that encompasses much of the city of Ann Arbor and the University of Michigan campus. Selected objects were immersed in a road salt solution, allowing delicate crystalline formations to emerge. Road salt is a common material input into these hydrological networks during the winter months and exists in multiple states of refinement, expression, coherence, and fragmentation. Each object was then arranged, photographed, and enlarged to recontextualize these materials in ways that invite deeper reflections on how infrastructure and human agency blur notions of the natural and the artificial. \nArtist Statements\/Bios\n\nSally Clegg \nSally Clegg is an artist and educator from Pelham, Massachusetts. Her studio practice is rooted in sculpture and expanded printmaking, stemming from a fascination with human efforts to make meaning from our relationships to objects. Clegg integrates history, popular culture, literature and philosophy as material for artmaking, leveraging personal anecdote and humor to reveal the complexity, absurdity, and theoretical richness at play in our connections to things and to ourselves. \n\nClegg holds an MFA in Art from The University of Michigan Stamps School of Art & Design, and a BA in Art & English from Goucher College. She has exhibited nationally and internationally, and her work can be found in permanent collections at Yale University, The New York Public Library, and elsewhere. Her artwork and writing has appeared in ASAP\/Journal, BOMB Magazine, Sculpture Magazine, and Hyperallergic. She is a lecturer in Art & Design at the University of Michigan. Website \/ Instagram\n\n\nKim Karlsrud \nKim Karlsrud is the co-founder of Commonstudio, a collaborative creative practice that develops socio-ecological and spatial interventions, installations, and initiatives working with and within urban landscapes. Her work explores the space between art and design, and is grounded in the concept of the \u201ccommons,\u201d that which is shared, as well as that which is ordinary, banal, and commonplace.\n\nKarlsrud completed her undergraduate degree in Product Design from Otis College of Art and Design and an MFA in Art from the University of Michigan. She is currently an Assistant Visiting Professor in the College of Design at the University of Oregon, teaching across Art and Landscape Architecture departments. She jointly received the 2014-15 Prince Charitable Trust Rome Prize in Landscape Architecture, was a 2017 resident at the Headlands Center for the Arts, and is the 2025-26 Fuller Fieldscape Fellow. Website \/ Instagram",
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        "datetime_start":"20260603T110000",
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        "date_start":"2026-06-03",
        "date_end":"2026-06-03",
        "time_start":"11:00:00",
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        "event_title":"Fore-Site (Phase 3): The Stamps Gallery Pillar Project",
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        "description":"From September 2025 through August 2026, Stamps Gallery is partnering in a curatorial collaboration with two Ypsilanti-based, artist-run project spaces led by Stamps alumni: C.Y.N.K. Studios, directed by Sally Clegg (Lecturer III and Student Exhibition Coordinator, MFA \u201920) and Abhishek Narula (MFA \u201920); and Sometimes Space, directed by Nathan Byrne (Lecturer I, MFA \u201921). Each space hosts dozens of artists annually for exhibitions, performances, and events, fostering experimental work and building community. For this project, Byrne, Clegg, and Narula have been commissioned to reimagine the pillars on Division Street that flank the gallery. In response, they've curated six artists to create new work for the pillars over three cycles:\nPhase 1 (September 12 - December 12) artists: Amelia Burns (Cranbrook MFA '23) and Erin McKenna (MFA '20)Phase 2 (January 12 - April 12) artists: Sally Clegg (MFA '20) and Kim Karlsrud (MFA '20)Phase 3 (May 12 - August 12) artists: Abhishek Narula (MFA '20) and Nathan Byrne (MFA '21)\nPhase 3 \nCurated by Sometimes Space: Abhishek Narula (entry pillar)Curated by CYNK Studios: Nathan Byrne (courtyard pillar)",
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