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However, despite their ecological and economic importance, we still lack fundamental understanding of the consequences of bee functional and life history variation for bee ecology, evolution, and pollination services. As native pollinator abundance and diversity continue to decline worldwide, expanding our understanding of how trait variation among bees shapes their geographic distributions and dietary preferences will enhance our ability to predict how global changes may impact this crucial ecosystem service. In this dissertation, I seek to address these gaps by adopting a macroecological and macroevolutionary approach to bee trait diversity. I will integrate large datasets of traits and phylogenies to identify the environmental factors that govern variation in key functional traits and explore how this variation influences bees' interactions with flowering plants. I will also generate new data on diet preferences for poorly studied tropical bees using novel approaches for honey and pollen metabarcoding and contribute to ongoing efforts in the field to create large, global datasets of bee traits and bee-plant interactions. Ultimately, this research will provide new insights into the ecological processes shaping bee diversity and their interactions with flowering plants.", "occurrence_notes":null, "guid":"135008-21875914@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/135008", "building_id":"1005169", "building_name":"Biological Sciences Building", "campus_maps_id":"631", "room":"1010", "location_name":"Biological Sciences Building", "has_livestream":0, "cost":"", "tags":["department of ecology and evolutionary biology","Museum Of Zoology","Museum - Zoology","Museum - Herbarium","Graduate Students","Graduate School","Graduate","Free","evolutionary biology","Environment","eeb","Ecology And Evolutionary Biology","Ecology & Biology","ecology","Bsbsigns"], "website":"", "sponsors":[ { "group_name":"Ecology and Evolutionary Biology", "group_id":"1190", "website":"" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2025\/04\/event_135008_original-1.jpg", "styled_images":{ 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He was the Editor-in-Chief of the IEEE\/ACM Transactions on Networking from 2013-2017 and is currently the Stochastic Models Area Chair for Mathematics of Operations Research.\r\n\r\nAbstract:\r\n\r\nThe first part of the talk will provide some motivation for the use of central limit theorem to design algorithms for machine learning and graph sampling. Then, we will provide an introduction to Stein\u2019s method which can be used to upper bound the Wasserstein distance between the distribution of a scaled sum of random variables and a Gaussian distribution. Finally, we will present some new results on nonasymptotic CLTs for vector-valued martingales and vector-valued functions of Markov chains, and discuss an application to machine learning. 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