{ "135846-21877321": { "datetime_modified":"20250527T170539", "datetime_start":"20250610T130000", "datetime_end":"20250610T150000", "has_end_time":1, "date_start":"2025-06-10", "date_end":"2025-06-10", "time_start":"13:00:00", "time_end":"15:00:00", "time_zone":"America\/Detroit", "event_title":"Mechanistic Modeling of Complex Health Problems with Deep Learning", "occurrence_title":"", "combined_title":"Mechanistic Modeling of Complex Health Problems with Deep Learning: Prayag Chatha", "event_subtitle":"Prayag Chatha", "event_type":"Lecture \/ Discussion", "event_type_id":"13", "description":"Though they show impressive empirical accuracy, machine learning methodologies have been criticized for not producing interpretable, scientific theories. In both clinical medicine and public health, the researchers aim not just to predict health outcomes, but to improve them. Hence, causal, human-interpretable models of nature hold particular value in these fields. In this dissertation, I investigate how deep learning, when integrated into scientifically-informed models and principled statistical frameworks, can be used to advance mechanistic modeling in the health sciences.\r\n\r\nSince the widespread adoption of electronic health records (EHRs), there has been growing interest in evaluating medical interventions through large-scale observational studies of diverse patient populations. In the first chapter, I examine the opportunities and challenges that arise from applying deep neural networks to EHR data. Despite the vast scale of EHR datasets, black box predictive modeling has limited value for informing clinical care, where human judgment is indispensable. Medical researchers are often interested in estimating counterfactual treatment eff ects on patients\u2019 time-to-event outcomes. In the second chapter, I propose the Dynamic Survival Transformer (DynST), a deep survival model that flexibly estimates hazards from both static and time-varying features typical of EHR data, and demonstrate how DynST supports robust, semiparametric inference for causal survival analysis.\r\n\r\nStochastic infectious disease models capture uncertainty in public health outcomes and off er mechanistic explanations of transmission patterns. However, they are often nonlinear dynamical systems with massive latent state spaces, making likelihood-based inference of model parameters difficult. In the third chapter, I develop a methodology for efficiently calibrating large-scale stochastic epidemic simulation models to observed data using Neural Posterior Estimation. In NPE, a neural network trained on simulated data learns to \u201cinvert\u201d a stochastic simulator and returns a parametric approximation of the posterior distribution. I use NPE to calibrate a stochastic Susceptible-Infected model to a study of a healthcare-associated infection in a long-term acute care hospital and find evidence of spatially heterogeneous patient-to-patient transmission risk.", "occurrence_notes":null, "guid":"135846-21877321@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/135846", "building_id":"1000167", "building_name":"West Hall", "campus_maps_id":"163", "room":"438", "location_name":"West Hall", "has_livestream":0, "cost":"", "tags":["Dissertation"], "website":"", "sponsors":[ { "group_name":"Department of Statistics Dissertation Defenses", "group_id":"4045", "website":"" } ], "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":1, "first_occurrence":21877321 } , "135842-21877318": { "datetime_modified":"20250527T143544", "datetime_start":"20250610T131500", "datetime_end":"20250610T151500", "has_end_time":1, "date_start":"2025-06-10", "date_end":"2025-06-10", "time_start":"13:15:00", "time_end":"15:15:00", "time_zone":"America\/Detroit", "event_title":"Reducibility and Anosov Representations", "occurrence_title":"", "combined_title":"Reducibility and Anosov Representations: Max Lahn", "event_subtitle":"Max Lahn", "event_type":"Presentation", "event_type_id":"16", "description":"Abstract:\r\n\r\nIn this thesis, we explore the framework of Anosov representations for reducible representations of a non-elementary word hyperbolic group. We give characterizations of the Anosov condition for these reducible representations in terms of the eigenvalues of the irreducible block factors of its semisimplification, or more generally, of the block factors of its block diagonalization. In the character variety, these Anosov representations comprise a collection of bounded convex domains in certain finite-dimensional vector spaces, and this perspective allows us to conclude for many non-elementary hyperbolic groups that connected components of the character variety which consist entirely of Anosov representations do not contain reducible representations. Applying these results to reducible suspensions, we obtain explicit examples of non-Anosov limits of reducible Anosov representations.", "occurrence_notes":null, "guid":"135842-21877318@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/135842", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"3096", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Dissertation","Graduate","Graduate Students","Mathematics"], "website":"", "sponsors":[ { "group_name":"Dissertation Defense - Department of Mathematics", "group_id":"4889", "website":"" }, { "group_name":"Department of Mathematics", "group_id":"3791", "website":"" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_thumb\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "event_large":"https:\/\/events.umich.edu\/media\/cache\/event_large\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "event_large_2x":"https:\/\/events.umich.edu\/media\/cache\/event_large_2x\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "event_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/event_large_lightbox\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "group_thumb":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_thumb\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "group_thumb_square":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_thumb_square\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "group_large":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_large\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "group_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/resolve\/group_large_lightbox\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "event_large_crop":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_large_crop\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "event_list":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_list\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "event_list_2x":"https:\/\/events.umich.edu\/media\/cache\/event_list_2x\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "event_grid":"https:\/\/events.umich.edu\/media\/cache\/event_grid\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "event_grid_2x":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_grid_2x\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "event_feature_large":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_feature_large\/media\/attachments\/2025\/05\/event_135842_original-1.jpg", "event_feature_thumb":"https:\/\/events.umich.edu\/media\/cache\/resolve\/event_feature_thumb\/media\/attachments\/2025\/05\/event_135842_original-1.jpg" }, "occurrence_count":1, "first_occurrence":21877318 } , "135660-21877055": { "datetime_modified":"20250610T132018", "datetime_start":"20250610T140000", "datetime_end":"20250610T144500", "has_end_time":1, "date_start":"2025-06-10", "date_end":"2025-06-10", "time_start":"14:00:00", "time_end":"14:45:00", "time_zone":"America\/Detroit", "event_title":"Student Life Spotlight 2025", "occurrence_title":"Adapting for Success: Preparing Students for the Evolving Job Market", "combined_title":"Student Life Spotlight 2025: Multiple conference events and sessions: Adapting for Success: Preparing Students for the Evolving Job Market", "event_subtitle":"Multiple conference events and sessions", "event_type":"Conference \/ Symposium", "event_type_id":"5", "description":"Join us to hear from other colleagues who attended a conference, training, workshop, or institute this past year and want to share what they learned. Whether it is new skills, tools, or research, we hope to unpack all of the information we're bringing back to campus from our various development opportunities. These will be hosted in rounds of 45 minute breakout sessions, with a break from 12pm-1pm for attendees to grab lunch on your own.This program is free for all Student Life Staff, and a $15 charge for non Student Life attendees.This is not a formal conference event, but you can think of it more as a \"Teachback\" opportunity! Afterward for Student Life Staff, spend time mingling with colleagues at the Annual Student Life Celebration, 3pm-5pm in the Michigan Union.", "occurrence_notes":null, "guid":"135660-21877055@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/135660", "building_id":"", "building_name":"", "campus_maps_id":"", "room":"", "location_name":"Michigan Union Wolverine Room", "has_livestream":0, "cost":"", "tags":["Sessions"], "website":"https:\/\/sessions.studentlife.umich.edu\/p\/track\/14359", "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":3, "first_occurrence":21877055 } , "135660-21877056": { "datetime_modified":"20250610T132018", "datetime_start":"20250610T140000", "datetime_end":"20250610T144500", "has_end_time":1, "date_start":"2025-06-10", "date_end":"2025-06-10", "time_start":"14:00:00", "time_end":"14:45:00", "time_zone":"America\/Detroit", "event_title":"Student Life Spotlight 2025", "occurrence_title":"Free Speech 101 for Student Life Professionals", "combined_title":"Student Life Spotlight 2025: Multiple conference events and sessions: Free Speech 101 for Student Life Professionals", "event_subtitle":"Multiple conference events and sessions", "event_type":"Conference \/ Symposium", "event_type_id":"5", "description":"Join us to hear from other colleagues who attended a conference, training, workshop, or institute this past year and want to share what they learned. 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