{ "142332-21890534": { "datetime_modified":"20260206T105512", "datetime_start":"20260212T124500", "datetime_end":"20260212T134500", "has_end_time":1, "date_start":"2026-02-12", "date_end":"2026-02-12", "time_start":"12:45:00", "time_end":"13:45:00", "time_zone":"America\/Detroit", "event_title":"Singing Down the Barriers: A Model to Re-engage Silenced Voices", "occurrence_title":"", "combined_title":"Singing Down the Barriers: A Model to Re-engage Silenced Voices: Louise Toppin University Diversity and Social Transformation Professor, and Professor of Music (Voice) School of Music, Theater & Dance", "event_subtitle":"Louise Toppin University Diversity and Social Transformation Professor, and Professor of Music (Voice) School of Music, Theater & Dance", "event_type":"Lecture \/ Discussion", "event_type_id":"13", "description":"This noted coloratura soprano and authority on classical song and opera by African American composers, will introduce UMRA members to Singing Down the Barriers (SDtB). SDtB explores the repertoire of African American, African, and African Diaspora concert composers, providing a historical perspective along with discussions to examine contemporary attitudes toward performing\/understanding African American songs. Toppin\u2019s presentation will demonstrate the SDtB program, which draws students, teachers, choral directors and musicians from across the country. A U-M faculty member since 2017, Toppin previously served as the University Distinguished Professor and Chair of the Department of Music at the University of North Carolina at Chapel Hill. Among other honors, she received the National Opera Association Lift Every Voice Legacy Award in 2014 and U-M\u2019s Distinguished Faculty Achievement Award in 2021.", "occurrence_notes":null, "guid":"142332-21890534@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/142332", "building_id":"null", "building_name":"Off Campus Location", "campus_maps_id":"1", "room":"", "location_name":"Washtenaw Community College Morris J. Lawrence Building 700 East Huron River Drive 48105", "has_livestream":0, "cost":"", "tags":["Discussion","Retirees"], "website":"https:\/\/www.youtube.com\/@umichretirees\/live", "sponsors":[ { "group_name":"University of Michigan Retirees Association (UMRA)", "group_id":"2816", "website":"http:\/\/www.hr.umich.edu\/umra\/" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2025\/12\/event_142332_original-1.png", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_thumb\/media\/attachments\/2025\/12\/event_142332_original-1.png", "event_large":"https:\/\/events.umich.edu\/media\/cache\/event_large\/media\/attachments\/2025\/12\/event_142332_original-1.png", "event_large_2x":"https:\/\/events.umich.edu\/media\/cache\/event_large_2x\/media\/attachments\/2025\/12\/event_142332_original-1.png", "event_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/event_large_lightbox\/media\/attachments\/2025\/12\/event_142332_original-1.png", "group_thumb":"https:\/\/events.umich.edu\/media\/cache\/group_thumb\/media\/attachments\/2025\/12\/event_142332_original-1.png", "group_thumb_square":"https:\/\/events.umich.edu\/media\/cache\/group_thumb_square\/media\/attachments\/2025\/12\/event_142332_original-1.png", "group_large":"https:\/\/events.umich.edu\/media\/cache\/group_large\/media\/attachments\/2025\/12\/event_142332_original-1.png", "group_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/group_large_lightbox\/media\/attachments\/2025\/12\/event_142332_original-1.png", "event_large_crop":"https:\/\/events.umich.edu\/media\/cache\/event_large_crop\/media\/attachments\/2025\/12\/event_142332_original-1.png", "event_list":"https:\/\/events.umich.edu\/media\/cache\/event_list\/media\/attachments\/2025\/12\/event_142332_original-1.png", "event_list_2x":"https:\/\/events.umich.edu\/media\/cache\/event_list_2x\/media\/attachments\/2025\/12\/event_142332_original-1.png", "event_grid":"https:\/\/events.umich.edu\/media\/cache\/event_grid\/media\/attachments\/2025\/12\/event_142332_original-1.png", "event_grid_2x":"https:\/\/events.umich.edu\/media\/cache\/event_grid_2x\/media\/attachments\/2025\/12\/event_142332_original-1.png", "event_feature_large":"https:\/\/events.umich.edu\/media\/cache\/event_feature_large\/media\/attachments\/2025\/12\/event_142332_original-1.png", "event_feature_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_feature_thumb\/media\/attachments\/2025\/12\/event_142332_original-1.png" }, "occurrence_count":1, "first_occurrence":21890534 } , "144411-21895317": { "datetime_modified":"20260123T170751", "datetime_start":"20260212T130000", "datetime_end":"20260212T140000", "has_end_time":1, "date_start":"2026-02-12", "date_end":"2026-02-12", "time_start":"13:00:00", "time_end":"14:00:00", "time_zone":"America\/Detroit", "event_title":"Lay All Your Love on Metadata: A New API for Discovery", "occurrence_title":"", "combined_title":"Lay All Your Love on Metadata: A New API for Discovery: ICPSR's Data Fair @ Love Data Week", "event_subtitle":"ICPSR's Data Fair @ Love Data Week", "event_type":"Livestream \/ Virtual", "event_type_id":"24", "description":"ICPSR maintains a collection of 60+ years of curated, richly described research data available for reuse by social science researchers at all levels of experience. A key challenge to disseminating this data is making it findable \u2013 helping users discover our data resources and making them aware of the ways in which ICPSR data can support their research needs. \n\nTo address this challenge, ICPSR created a metadata export API (Application Programming Interface) that enables individuals and institutions to programmatically retrieve study-level metadata about ICPSR studies in multiple standards-based formats. The API supports reuse of ICPSR metadata in local catalogs, discovery systems, research workflows, and downstream applications. It extends and enriches ICPSR\u2019s reach while increasing the FAIRness (findability, accessibility, interoperability, and reusability) of its data collections. \n\nIn this presentation, members of ICPSR\u2019s metadata team will demonstrate the new metadata export API and its benefits, including how to query it to find studies that meet specific research needs, what information is returned in the results, and how these exports improve upon ICPSR\u2019s previous metadata distribution offerings. If you're interested in incorporating ICPSR data into another discovery platform, this session will show you how to get started.\n\nPresenters:\n * Mike Shallcross, Senior Associate Archivist, Metadata & Preservation, ICPSR\n * Megan Chenoweth, Metadata Manager, Metadata & Preservation, ICPSR\n * Jared Lyle, Archivist and Director, Metadata & Preservation, ICPSR", "occurrence_notes":null, "guid":"144411-21895317@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/144411", "building_id":"null", "building_name":"Off Campus Location", "campus_maps_id":"1", "room":"", "location_name":"Virtual", "has_livestream":0, "cost":"", "tags":["Data Management","Love Data Week","Metadata","Data","Data Analysis","Data Collection","Data Curation","Icpsr Data Fair"], "website":"https:\/\/myumi.ch\/9pREX", "sponsors":[ { "group_name":"ICPSR at the University of Michigan Institute for Social Research", "group_id":"4533", "website":"https:\/\/www.icpsr.umich.edu\/" }, { "group_name":"Institute for Social Research", "group_id":"3285", "website":"http:\/\/isr.umich.edu" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2026\/01\/event_144411_original-1.png", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_thumb\/media\/attachments\/2026\/01\/event_144411_original-1.png", "event_large":"https:\/\/events.umich.edu\/media\/cache\/event_large\/media\/attachments\/2026\/01\/event_144411_original-1.png", "event_large_2x":"https:\/\/events.umich.edu\/media\/cache\/event_large_2x\/media\/attachments\/2026\/01\/event_144411_original-1.png", "event_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/event_large_lightbox\/media\/attachments\/2026\/01\/event_144411_original-1.png", "group_thumb":"https:\/\/events.umich.edu\/media\/cache\/group_thumb\/media\/attachments\/2026\/01\/event_144411_original-1.png", "group_thumb_square":"https:\/\/events.umich.edu\/media\/cache\/group_thumb_square\/media\/attachments\/2026\/01\/event_144411_original-1.png", "group_large":"https:\/\/events.umich.edu\/media\/cache\/group_large\/media\/attachments\/2026\/01\/event_144411_original-1.png", "group_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/group_large_lightbox\/media\/attachments\/2026\/01\/event_144411_original-1.png", "event_large_crop":"https:\/\/events.umich.edu\/media\/cache\/event_large_crop\/media\/attachments\/2026\/01\/event_144411_original-1.png", "event_list":"https:\/\/events.umich.edu\/media\/cache\/event_list\/media\/attachments\/2026\/01\/event_144411_original-1.png", "event_list_2x":"https:\/\/events.umich.edu\/media\/cache\/event_list_2x\/media\/attachments\/2026\/01\/event_144411_original-1.png", "event_grid":"https:\/\/events.umich.edu\/media\/cache\/event_grid\/media\/attachments\/2026\/01\/event_144411_original-1.png", "event_grid_2x":"https:\/\/events.umich.edu\/media\/cache\/event_grid_2x\/media\/attachments\/2026\/01\/event_144411_original-1.png", "event_feature_large":"https:\/\/events.umich.edu\/media\/cache\/event_feature_large\/media\/attachments\/2026\/01\/event_144411_original-1.png", "event_feature_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_feature_thumb\/media\/attachments\/2026\/01\/event_144411_original-1.png" }, "occurrence_count":1, "first_occurrence":21895317 } , "144369-21895239": { "datetime_modified":"20260204T121635", "datetime_start":"20260212T132000", "datetime_end":"20260212T135000", "has_end_time":1, "date_start":"2026-02-12", "date_end":"2026-02-12", "time_start":"13:20:00", "time_end":"13:50:00", "time_zone":"America\/Detroit", "event_title":"Carillon Lesson open to public observation", "occurrence_title":"", "combined_title":"Carillon Lesson open to public observation", "event_subtitle":"", "event_type":"Class \/ Instruction", "event_type_id":"8", "description":"In place of a regular recital, the public is welcome to visit and observe as students take a lesson on the carillon led by Prof. Tiffany Ng.\n\nThe Ann & Robert H. Lurie Carillon is an instrument of 60 bells with the lowest bell (bourdon) weighing 6 tons.\n\nThirty-minute recitals are performed on the Lurie Carillon every weekday that classes are in session. During these recitals, visitors may take the elevator to level 2 to view the largest bells, or to level 3 to see the carillonist performing. (Visitors subject to acrophobia are recommended to visit level 2 only.) An optional spiral stairway between levels 2 and 3 allows for up-close views of some of the largest bells.", "occurrence_notes":null, "guid":"144369-21895239@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/144369", "building_id":"1000394", "building_name":"Lurie Ann & Robert H. Tower", "campus_maps_id":"91", "room":"", "location_name":"Lurie Ann & Robert H. Tower", "has_livestream":0, "cost":"Free - no tickets required", "tags":["North Campus","Music","Free"], "website":"", "sponsors":[ { "group_name":"School of Music, Theatre & Dance (SMTD)", "group_id":"155", "website":"http:\/\/smtd.umich.edu\/events" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2026\/01\/event_144369_original-1.jpg", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_thumb\/media\/attachments\/2026\/01\/event_144369_original-1.jpg", "event_large":"https:\/\/events.umich.edu\/media\/cache\/event_large\/media\/attachments\/2026\/01\/event_144369_original-1.jpg", "event_large_2x":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_large_2x\/media\/attachments\/2026\/01\/event_144369_original-1.jpg", "event_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/event_large_lightbox\/media\/attachments\/2026\/01\/event_144369_original-1.jpg", 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"combined_title":"Introduction to Emotional Intelligence: Presenter: Amanda Ruud, Amy Fredell", "event_subtitle":"Presenter: Amanda Ruud, Amy Fredell", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"Course details and registration are available on the Organizational Learning website.", "occurrence_notes":null, "guid":"136780-21879102@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/136780", "building_id":"null", "building_name":"Off Campus Location", "campus_maps_id":"1", "room":"", "location_name":"Virtual", "has_livestream":1, "livestream_type":"other", "livetream_require_login":0, "livestream_id":"", "livestream_link":"", "cost":"", "tags":["Discussion","Self Development","Communication"], "website":"https:\/\/hr.umich.edu\/working-u-m\/professional-development\/courses\/introduction-emotional-intelligence", "sponsors":[ { "group_name":"Organizational Learning", "group_id":"2606", "website":"https:\/\/hr.umich.edu\/organizational-learning" } ], "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":4, "first_occurrence":21879100 } , "145024-21896559": { "datetime_modified":"20260204T084859", "datetime_start":"20260212T133000", "datetime_end":"20260212T143000", "has_end_time":1, "date_start":"2026-02-12", "date_end":"2026-02-12", "time_start":"13:30:00", "time_end":"14:30:00", "time_zone":"America\/Detroit", "event_title":"Marwah Al Ismail Dissertation Defense", "occurrence_title":"", "combined_title":"Marwah Al Ismail Dissertation Defense: Advances in Methodology for Regional Landslide Analysis using Statistical, Mechanical, and Machine Learning Approaches", "event_subtitle":"Advances in Methodology for Regional Landslide Analysis using Statistical, Mechanical, and Machine Learning Approaches", "event_type":"Lecture \/ Discussion", "event_type_id":"13", "description":"Landslides are catastrophic events that occur on critically unstable slopes in steep, mountainous regions in response to external triggers, such as seismic events or prolonged,\nintense rainfall. The damage resulting from those landslides is mostly determined by their magnitude and size. Consequently, assessing landslide hazards in steep, tectonically active mountains at high altitudes remains a challenging task; however, advances in computational methods and technologies can make it achievable. This dissertation demonstrates the novel joint utility of mechanistic and statistical (chapters 2 and 3) and machine-learning (chapter 4) techniques for landslide analysis to understand the contribution of near-subsurface material strength, topography, and triggering factors to the regional distribution of landslide sizes.\n\nIn Chapters 2 and 3, we use computational methods to assess hillslope stability using geotechnical engineering models, combined with extensive probabilistic topographic\nsegmentation, to generate a synthetic distribution of landslide sizes. Specifically, we use 2D slope stability analysis to assess the probability of failure (P f ) for a given hillslope geometry (i.e., hillslope area and gradient) under subsurface strength conditions (i.e., cohesion and angle of friction). In addition, using hydrological tools to discretize topography in a random, probabilistic approach identifies the distribution of hillslope geometries prone to failure. The combined probabilities from mechanistic modeling and the availability of hillslopes in a given topography result in a synthetic distribution of landslide sizes. This modeled distribution allows us to investigate, in great detail, the impact of the variation in strength\u2013and hence weathering\u2013with depth and slope, as well as the topography on the overall distribution. Using two different landslide inventory datasets: the 1994 Mw6.7 Northridge earthquake in Southern California and the 2015 Mw7.8 Gorkha earthquake in central Nepal, we find that the variability in the weathering gradient with depth and the slope gradient is essential for accurate reproduction of regional landslide size distribution. Moreover, because of the variable topographic gradient and climatic conditions within central Nepal, we apply this framework to back-estimate the strength-depth profile for each sub-region within the study area from south to north. We find that back-estimated strength increases northward, coinciding with increases in the topographic gradient and landslide density. These findings demonstrate the significance of the synthetic\ndistributions for identifying the controls on the regional landslide size distributions as well as providing an insight into the critical zone structure for hazard assessment and landscape evolution studies.\n\nChapter 4 provides an opportunity to explore the use of machine learning models for landslide analysis, specifically for improving rainfall-triggered landslide forecasting. Steep mountain belts at high altitudes experience the orographic effect, which produces intense rainfall and, consequently, triggers landslides. As rainfall-triggered landslide sizes are sensitive to rainfall event characteristics (i.e., storm depth and intensity), using accurate rainfall data with high spatial and temporal coverage is essential. Ground-based rainfall measurements from gauge stations provide an accurate source of data; however, gauge stations are usually sparsely located and limited in steep terrain, where landslides are most common. In recent years, remotely sensed precipitation measurements have provided high spatial and temporal resolution data, but are often inaccurate, especially on hillslopes at high altitudes. To overcome challenges in each dataset source, we use machine learning models to predict calibrated rainfall data at locations where gauge stations are absent, with a focus on the monsoon season, during which rainfall intensifies. The use of machine learning approaches and associated evaluation metrics enables us to validate their utility for predicting the total rainfall during the monsoon season with high certainty, compared with the original remotely sensed rainfall data. In addition, the model\u2019s predicted rainfall captured the annual distribution of storms during the monsoon season. Although the model\u2019s accuracy at predicting the timing of extreme rainfall events (which trigger landslides), this work provides a promising avenue for using machine learning techniques to predict high-resolution, high-temporal-resolution rainfall datasets.\n\nOn a broader scale, this dissertation provides novel methodologies that enable us to improve landslide hazard analysis, assessment, and forecasting.", "occurrence_notes":null, "guid":"145024-21896559@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/145024", "building_id":"1000188", "building_name":"1100 North University Building", "campus_maps_id":"628", "room":"2540", "location_name":"1100 North University Building", "has_livestream":0, "cost":"", "tags":["Earth And Environmental Sciences"], "website":"", "sponsors":[ { "group_name":"Earth and Environmental Sciences", "group_id":"3170", "website":"http:\/\/www.lsa.umich.edu\/earth" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_thumb\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "event_large":"https:\/\/events.umich.edu\/media\/cache\/event_large\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "event_large_2x":"https:\/\/events.umich.edu\/media\/cache\/event_large_2x\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "event_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/event_large_lightbox\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "group_thumb":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_thumb\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "group_thumb_square":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_thumb_square\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "group_large":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_large\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "group_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_large_lightbox\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "event_large_crop":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_large_crop\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "event_list":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_list\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "event_list_2x":"https:\/\/events.umich.edu\/media\/cache\/event_list_2x\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "event_grid":"https:\/\/events.umich.edu\/media\/cache\/event_grid\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "event_grid_2x":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_grid_2x\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "event_feature_large":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_feature_large\/media\/attachments\/2026\/02\/event_145024_original-1.jpg", "event_feature_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_feature_thumb\/media\/attachments\/2026\/02\/event_145024_original-1.jpg" }, "occurrence_count":1, "first_occurrence":21896559 } }