{ "153381-21915734": { "datetime_modified":"20261006T181240", "datetime_start":"20261021T160000", "datetime_end":"20261021T170000", "has_end_time":1, "date_start":"2026-10-21", "date_end":"2026-10-21", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"Stochastic Models and Optimization for Dynamic Portfolio Management: A Compartment Framework for Financial Growth and Decision Support", "occurrence_title":"", "combined_title":"Stochastic Models and Optimization for Dynamic Portfolio Management: A Compartment Framework for Financial Growth and Decision Support: Tirupathi Rao Padi (Pondicherry University)", "event_subtitle":"Tirupathi Rao Padi (Pondicherry University)", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"Portfolio management is a dynamic decision-making problem characterized by uncertainty, evolving asset states, competing risk\u2013return objectives, and changing market conditions. This research develops an integrated stochastic and optimization framework for modelling financial growth and formulating investment policies by representing a portfolio as a dynamic compartmental system in which risky and non-risky assets undergo stochastic growth, loss, transformation, and migration. Univariate and bivariate birth\u2013death and migration processes, together with Markov and hidden-state modelling perspectives, are employed to characterize the probabilistic evolution and interactions of portfolio components.\n\nThe proposed framework systematically connects stochastic process modelling, probability analysis, statistical inference, nonlinear optimization, computational analysis, and decision support. Difference and differential equations are developed to describe portfolio dynamics, while probability-generating functions and moment-based methods are used to derive expectations, variances, covariances, and related measures under transient and steady-state conditions. These statistical characteristics subsequently serve as inputs to stochastic optimization models that address alternative investment objectives, including risk control, volatility management, portfolio diversification, and the determination of appropriate investment policy parameters.\n\nComputational experimentation and sensitivity analysis are incorporated to examine the effects of growth, loss, and transformation parameters on portfolio behavior, using real-world financial data to ground empirical exploration and model validation. The resulting framework provides a pathway from uncertainty modelling to quantitative risk assessment, prescriptive optimization, and intelligent decision support. The research is intended to stimulate interdisciplinary collaboration across Statistics, Stochastic Processes, Mathematical Finance, Operations Research, Optimization, Data Science, and Computational Modelling, with potential applications in real-data validation, software development, joint publications, and future research on scalable stochastic decision-support systems for contemporary financial management.", "occurrence_notes":null, "guid":"153381-21915734@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/153381", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21915734 } , "148617-21904532": { "datetime_modified":"20260903T140455", "datetime_start":"20261028T160000", "datetime_end":"20261028T170000", "has_end_time":1, "date_start":"2026-10-28", "date_end":"2026-10-28", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"Policy Gradient Flow for Stochastic Control", "occurrence_title":"", "combined_title":"Policy Gradient Flow for Stochastic Control: Zhenjie Ren, University of Evry", "event_subtitle":"Zhenjie Ren, University of Evry", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"Reinforcement learning has achieved remarkable success in landmark applications such as AlphaGo and AlphaFold, and is increasingly expected to play a central role in emerging domains such as autonomous driving. A substantial body of work has established theoretical foundations for classical reinforcement learning algorithms, including temporal-difference learning, policy iteration, and Q-learning. By contrast, policy gradient descent, despite its widespread use, remains less well understood from a theoretical perspective, largely because of its non-convex structure and the complexity of the underlying functional space. Existing convergence analyses typically require uniform regularity assumptions on the policy, viewed as a feedback control function, along the gradient flow; moreover, the resulting convergence rates depend on these regularity bounds. In this work, we significantly strengthen the existing convergence theory. Our key insight is to relate policy gradient descent to a mirror flow on the space of probability measures over controlled trajectories, where the Bregman divergence is induced by the convex control cost. We rigorously prove a JKO-type convergence result showing that the discrete-time mirror flow converges to its continuous-time counterpart, and we identify the limiting dynamics as a preconditioned policy gradient descent flow on the space of control processes. Leveraging this mirror-flow perspective, we establish an exponential convergence rate that is independent of policy regularity. The convergence holds both in Bregman divergence and in the value of the associated control problem.", "occurrence_notes":null, "guid":"148617-21904532@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/148617", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21904532 } , "150012-21907810": { "datetime_modified":"20260807T155844", "datetime_start":"20261104T160000", "datetime_end":"20261104T170000", "has_end_time":1, "date_start":"2026-11-04", "date_end":"2026-11-04", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"Exploratory Optimal Reinsurance under the Mean-Variance Criterion", "occurrence_title":"", "combined_title":"Exploratory Optimal Reinsurance under the Mean-Variance Criterion: Austin Riis-Due, Waterloo", "event_subtitle":"Austin Riis-Due, Waterloo", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"This paper proposes a Reinforcement Learning (RL) approach to the optimal reinsurance problem\nwhen the insurer faces uncertainty about the insurance claim dynamics. To this end, we first formulate\nan exploratory version of the problem as a relaxed stochastic control problem. Within a broad class of\nparametric retention functions and general risk loading functions, we derive the closed-form equilibrium\npolicy under the continuous-time mean-variance criterion. This is achieved through a formal verification\ntheorem and solving classical solutions of a system of exploratory extended Hamilton-Jacobi-Bellman\n(EEHJB) equations. We then establish a policy iteration theorem, showing that starting from any timeand state-homogeneous policy, policy iteration converges to the derived equilibrium policy. Next, we\ndevelop a martingale orthogonality theorem, which serves as the foundation of our RL algorithm. The\nalgorithm is evaluated through simulation studies and real data from the U.S. National Flood Insurance\nProgram. Results demonstrate that the RL approach effectively learns unknown claim distributions,\ntracks unobserved changes in claim dynamics and produces higher insurer surplus trajectories than the\nmaximum likelihood estimation (MLE) approach while simultaneously exhibiting greater robustness to\nthe choice of training window.", "occurrence_notes":null, "guid":"150012-21907810@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/150012", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21907810 } , "149579-21906721": { "datetime_modified":"20260819T202729", "datetime_start":"20261118T160000", "datetime_end":"20261118T170000", "has_end_time":1, "date_start":"2026-11-18", "date_end":"2026-11-18", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"A New Approach for the Continuous Time Kyle-Back Strategic Insider Equilibrium Problem", "occurrence_title":"", "combined_title":"A New Approach for the Continuous Time Kyle-Back Strategic Insider Equilibrium Problem: Bixing Qiao, UM", "event_subtitle":"Bixing Qiao, UM", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"In this talk, we consider a continuous-time Kyle-Back model which is a game between an insider and a market maker. The existing literature typically focuses on constructing equilibria with a PDE approach, which requires certain Markovian structures. We characterize all equilibria through a coupled system of forward-backward SDEs. In particular, when the time duration is small, we show that the FBSDE is well-posed, and therefore the game has a unique equilibrium. Moreover, this unique equilibrium may be non-Markovian and thus not attainable via the PDE approach. We next study the set value of the game, which roughly speaking is the set of insider's values over all equilibria and thus is by nature unique. Finally, we characterize the set value through a level set of a certain standard HJB equation.\nIn the second part of the talk, we apply the new approach to the Kyle-Back model with dynamic legal risk and large numbers of noise traders. In this setting, the insider chooses a strategy that conceals his identity within a large volume of surrounding trades and concentrates on medium-sized trades. We establish an intensity-based mathematical framework for explaining the interconnections between insider trading and stealth trading. When the number of noise traders becomes large, the price impact of the insider asymptotically vanishes, and consequently the stochastic game becomes deterministic optimizations, which also carry implications for regulatory investigations and sanctions.\n\nThe results above include the joint work with Weixuan Xia and with Jianfeng Zhang.", "occurrence_notes":null, "guid":"149579-21906721@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/149579", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21906721 } , "149576-21906718": { "datetime_modified":"20261011T180615", "datetime_start":"20261202T160000", "datetime_end":"20261202T170000", "has_end_time":1, "date_start":"2026-12-02", "date_end":"2026-12-02", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"Inverse problems over probability measure space", "occurrence_title":"", "combined_title":"Inverse problems over probability measure space: Qin Li, University of Wisconsin-Madison", "event_subtitle":"Qin Li, University of Wisconsin-Madison", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"Inverse problems are ubiquitous. Traditionally, the goal is to infer an unknown vector or function. But what if the unknown is a probability measure? Seeking a measure that generates data consistent with given observations leads to an optimization problem over probability space. However, the complex geometric nature of this space prevents the direct use of standard arguments and solvers. We unravel some of the surprises that emerge in this setting and discuss potential solutions.", "occurrence_notes":null, "guid":"149576-21906718@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/149576", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21906718 } , "149577-21906719": { "datetime_modified":"20260727T104405", "datetime_start":"20261209T160000", "datetime_end":"20261209T170000", "has_end_time":1, "date_start":"2026-12-09", "date_end":"2026-12-09", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"THE HEREDITARY LAWS OF LARGE NUMBERS", "occurrence_title":"", "combined_title":"THE HEREDITARY LAWS OF LARGE NUMBERS: Ioannis Karatzas, Columbia University", "event_subtitle":"Ioannis Karatzas, Columbia University", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"The celebrated theorem of Komlos (1967) establishes L^1-boundedness as a sufficient condition for a sequence of measurable functions on a probability space to contain a subsequence along which, and along whose every further subsequence (\u201chereditarily\u201d), the Cesaro averages converge to a \u201crandomized mean\u201d in the spirit of the Strong law of Large Numbers. We provide conditions not only sufficient, but also necessary, for this result, as well as for the hereditary analogues of the Weak Law of Large Numbers, of the Hsu-Robbins-Erdos Law of Large Numbers, and of the Law of the Iterated Logarithm. \n\nJoint work with I. Berkes (Budapest) and W. Schachermayer (Vienna).", "occurrence_notes":null, "guid":"149577-21906719@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/149577", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics","Statistics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21906719 } , "152618-21914186": { "datetime_modified":"20260922T084512", "datetime_start":"20270113T160000", "datetime_end":"20270113T170000", "has_end_time":1, "date_start":"2027-01-13", "date_end":"2027-01-13", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"TBA", "occurrence_title":"", "combined_title":"TBA: Dohyeon Kim, Caltech", "event_subtitle":"Dohyeon Kim, Caltech", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"TBA", "occurrence_notes":null, "guid":"152618-21914186@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/152618", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21914186 } , "153516-21915950": { "datetime_modified":"20261009T132258", "datetime_start":"20270120T160000", "datetime_end":"20270120T170000", "has_end_time":1, "date_start":"2027-01-20", "date_end":"2027-01-20", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"Regularization by Common Noise for Mean Field Games and Mean Field Control", "occurrence_title":"", "combined_title":"Regularization by Common Noise for Mean Field Games and Mean Field Control: Lukas Wessels, Universit\u00e9 C\u00f4te d\u2019Azur", "event_subtitle":"Lukas Wessels, Universit\u00e9 C\u00f4te d\u2019Azur", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"A fundamental challenge in the theory of mean field games (MFGs) is that equilibria are generally non-unique in the absence of monotonicity assumptions. In this talk, we establish that an infinite-dimensional multiplicative common noise restores uniqueness for generic MFGs in one spatial dimension. Furthermore, by exploiting the connection between mean field control (MFC) and potential MFGs, we show that this common noise regularizes the MFC value function. Based on this regularity, we then construct optimal feedback controls for the MFC problem. This talk is based on joint work with F. Delarue.", "occurrence_notes":null, "guid":"153516-21915950@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/153516", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"https:\/\/lukaswessels.org\/", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21915950 } , "149994-21907791": { "datetime_modified":"20260807T120756", "datetime_start":"20270217T160000", "datetime_end":"20270217T170000", "has_end_time":1, "date_start":"2027-02-17", "date_end":"2027-02-17", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"The optimal rate of convergence in mean field control", "occurrence_title":"", "combined_title":"The optimal rate of convergence in mean field control: Sebatian Munoz, UCLA", "event_subtitle":"Sebatian Munoz, UCLA", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"I will discuss the sharp rate of convergence of the value functions of N-particle stochastic control problems to their mean field limit, for merely Lipschitz mean field costs. For d \u2265 2, the optimal rate is that of the empirical measures of i.i.d. samples in the 1-Wasserstein distance, as conjectured by Daudin, Delarue, and Jackson, and it persists with additive common noise. In dimension one, this benchmark can surprisingly be beaten: cooperating particles outperform independent samples, and the optimal exponent is 4\/7, strictly between the accuracy of independent sampling (N^{-1\/2}) and that of quantization (N^{-1}). The proofs rely on a new control-theoretic technique of recoupled shadow flows and, in dimension one, on a Gibbs law implementing the cooperation and a Schr\u00f6dinger ground-state estimate.", "occurrence_notes":null, "guid":"149994-21907791@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/149994", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21907791 } , "150752-21910069": { "datetime_modified":"20260821T200659", "datetime_start":"20270224T160000", "datetime_end":"20270224T170000", "has_end_time":1, "date_start":"2027-02-24", "date_end":"2027-02-24", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"TBA", "occurrence_title":"", "combined_title":"TBA: Tom Bielecki", "event_subtitle":"Tom Bielecki", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"TBA", "occurrence_notes":null, "guid":"150752-21910069@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/150752", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21910069 } , "151564-21911768": { "datetime_modified":"20260904T104356", "datetime_start":"20270317T160000", "datetime_end":"20270317T170000", "has_end_time":1, "date_start":"2027-03-17", "date_end":"2027-03-17", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"TBA", "occurrence_title":"", "combined_title":"TBA: Jose Blanchet, Stanford", "event_subtitle":"Jose Blanchet, Stanford", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"TBA", "occurrence_notes":null, "guid":"151564-21911768@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/151564", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21911768 } , "153757-21916282": { "datetime_modified":"20261015T211032", "datetime_start":"20270324T160000", "datetime_end":"20270324T170000", "has_end_time":1, "date_start":"2027-03-24", "date_end":"2027-03-24", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"Ph.D. Defense (Title TBA)", "occurrence_title":"", "combined_title":"Ph.D. Defense (Title TBA): Hongyi Zhou, University of Michigan", "event_subtitle":"Hongyi Zhou, University of Michigan", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"Title and abstract to be announced.", "occurrence_notes":null, "guid":"153757-21916282@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/153757", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21916282 } , "151565-21911769": { "datetime_modified":"20260904T104603", "datetime_start":"20270414T100000", "datetime_end":"20270414T110000", "has_end_time":1, "date_start":"2027-04-14", "date_end":"2027-04-14", "time_start":"10:00:00", "time_end":"11:00:00", "time_zone":"America\/Detroit", "event_title":"TBA", "occurrence_title":"", "combined_title":"TBA: Baris Ata, University of Chicago", "event_subtitle":"Baris Ata, University of Chicago", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"TBA", "occurrence_notes":null, "guid":"151565-21911769@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/151565", "building_id":"1000166", "building_name":"East Hall", "campus_maps_id":"53", "room":"1360", "location_name":"East Hall", "has_livestream":0, "cost":"", "tags":["Mathematics"], "website":"", "sponsors":[ { "group_name":"Financial\/Actuarial Mathematics Seminar - Department of Mathematics", "group_id":"4890", "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":21911769 } }