{ "147694-21901610": { "datetime_modified":"20260518T092027", "datetime_start":"20260526T100000", "datetime_end":"20260526T110000", "has_end_time":1, "date_start":"2026-05-26", "date_end":"2026-05-26", "time_start":"10:00:00", "time_end":"11:00:00", "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", "event_subtitle":"", "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.", "occurrence_notes":null, "guid":"147694-21901610@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/147694", "building_id":"", "building_name":"", "campus_maps_id":"", "room":"", "location_name":"", "has_livestream":0, "cost":"", "tags":["Sessions"], "website":"https:\/\/sessions.studentlife.umich.edu\/p\/track\/17048", "sponsors":[ { "group_name":"Sessions @ Michigan", "group_id":"4791", "website":"https:\/\/sessions.studentlife.umich.edu\/" } ], "image_url":"", "styled_images":{ "event_thumb":"", "event_large":"", "event_large_2x":"", "event_large_lightbox":"", "group_thumb":"", "group_thumb_square":"", "group_large":"", "group_large_lightbox":"", "event_large_crop":"", "event_list":"", "event_list_2x":"", "event_grid":"", "event_grid_2x":"", "event_feature_large":"", "event_feature_thumb":"" }, "occurrence_count":15, "first_occurrence":21901610 } , "148255-21903515": { "datetime_modified":"20260513T131053", "datetime_start":"20260526T130000", "datetime_end":"20260526T160000", "has_end_time":1, "date_start":"2026-05-26", "date_end":"2026-05-26", "time_start":"13:00:00", "time_end":"16:00:00", "time_zone":"America\/Detroit", "event_title":"June 1-5 Course - Introduction to Qualitative Research Methods", "occurrence_title":"", "combined_title":"June 1-5 Course - Introduction to Qualitative Research Methods: Dr. Monique Hennink - Hubert Department of Global Health, Emory University", "event_subtitle":"Dr. Monique Hennink - Hubert Department of Global Health, Emory University", "event_type":"Class \/ Instruction", "event_type_id":"8", "description":"June 1-5, 2026, M-F\n1:00-4:00pm \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\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research, covering principles of qualitative research, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews, focus groups, and observation \u2013 and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan, Department of Epidemiology, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory\u2019s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1,000 citations - considered high impact scholarship. She received the 2020 Provost\u2019s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years\u2019 experience in the design, conduct, analysis, and publication of qualitative health research. She has authored five textbooks on qualitative research, including: Qualitative Research Methods 2nd edition (2020); Focus Group Discussions (2014), Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https:\/\/sph.emory.edu\/qual-works) training program in 2013 for public health professionals. Her courses, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research, such as using interpreters and translators in qualitative data collection; the effect of using court reporters on data quality; estimating sample size in qualitative studies; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their \u2018Cases in Methodology\u2019 work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP), on \u2018Qualitative Research in Population Studies\u2019 which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums, such as: International Congress of Qualitative Inquiry; International Institute for Qualitative Methods; European Association of Population Studies; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition; Emerson et al (2011) Writing Ethnographic Fieldnotes; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition; Hennink (2014) Focus Group Discussions. Oxford University Press", "occurrence_notes":"Registration and payment are required a minimum of two weeks prior to the start of the course.", "guid":"148255-21903515@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/148255", "building_id":"null", "building_name":"Off Campus Location", "campus_maps_id":"1", "room":"", "location_name":"Virtual", "has_livestream":0, "cost":"$1,200", "tags":["Biomedical","Center For Political Studies","Data","Data Analysis","Data Collection","Data Curation","Data Linkage","Data Management","Data Science","Graduate","Graduate and Professional Students","Health","Health Data","Mathematics","Professional Development","Public Health","Research","Survey Methodology","Survey Methods","Survey Research"], "website":"https:\/\/shorturl.at\/wlr68", "sponsors":[ { "group_name":"Summer Institute in Survey Research Techniques", "group_id":"4327", "website":"" }, { "group_name":"Institute for Social Research", "group_id":"3285", "website":"http:\/\/isr.umich.edu" }, { "group_name":"Survey Research Center", "group_id":"5063", "website":"https:\/\/src.isr.umich.edu\/" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2026\/05\/event_148255_original-1.png", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_thumb\/media\/attachments\/2026\/05\/event_148255_original-1.png", "event_large":"https:\/\/events.umich.edu\/media\/cache\/event_large\/media\/attachments\/2026\/05\/event_148255_original-1.png", "event_large_2x":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_large_2x\/media\/attachments\/2026\/05\/event_148255_original-1.png", "event_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/event_large_lightbox\/media\/attachments\/2026\/05\/event_148255_original-1.png", "group_thumb":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_thumb\/media\/attachments\/2026\/05\/event_148255_original-1.png", "group_thumb_square":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_thumb_square\/media\/attachments\/2026\/05\/event_148255_original-1.png", "group_large":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_large\/media\/attachments\/2026\/05\/event_148255_original-1.png", "group_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_large_lightbox\/media\/attachments\/2026\/05\/event_148255_original-1.png", "event_large_crop":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_large_crop\/media\/attachments\/2026\/05\/event_148255_original-1.png", "event_list":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_list\/media\/attachments\/2026\/05\/event_148255_original-1.png", "event_list_2x":"https:\/\/events.umich.edu\/media\/cache\/event_list_2x\/media\/attachments\/2026\/05\/event_148255_original-1.png", "event_grid":"https:\/\/events.umich.edu\/media\/cache\/event_grid\/media\/attachments\/2026\/05\/event_148255_original-1.png", "event_grid_2x":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_grid_2x\/media\/attachments\/2026\/05\/event_148255_original-1.png", "event_feature_large":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_feature_large\/media\/attachments\/2026\/05\/event_148255_original-1.png", "event_feature_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_feature_thumb\/media\/attachments\/2026\/05\/event_148255_original-1.png" }, "occurrence_count":24, "first_occurrence":21903453 } , "148265-21903535": { "datetime_modified":"20260513T130729", "datetime_start":"20260526T130000", "datetime_end":"20260526T150000", "has_end_time":1, "date_start":"2026-05-26", "date_end":"2026-05-26", "time_start":"13:00:00", "time_end":"15:00:00", "time_zone":"America\/Detroit", "event_title":"June 2 - July 30, 2026 T\/TH Course - Sampling in Practice", "occurrence_title":"", "combined_title":"June 2 - July 30, 2026 T\/TH Course - Sampling in Practice: Yajuan Si - Institute for Social Research, University of Michigan.", "event_subtitle":"Yajuan Si - Institute for Social Research, University of Michigan.", "event_type":"Class \/ Instruction", "event_type_id":"8", "description":"June 2-July 30, 2026, T\/TH\n1:00pm - 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\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\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied, hands-on approach, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods, including simple random sampling, stratification, systematic selection, cluster sampling, probability proportional to size sampling, and multistage sampling. We will also cover sampling cost models, sampling error estimation techniques, non-sampling errors, missing data, and nonprobability samples. The course emphasizes practical implementation, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys, selecting subjects, analyzing sample data, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan\u2019s research focuses on methodology development, from data analysis to study design, in streams of Bayesian statistics, linking design- and model-based approaches for survey inference, data integration, missing data analysis, confidentiality protection, and causal inference, with applications in the social and health sciences. 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Rivera", "event_type":"Lecture \/ Discussion", "event_type_id":"13", "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. 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