{"id":2055,"date":"2026-03-03T14:55:08","date_gmt":"2026-03-03T13:55:08","guid":{"rendered":"https:\/\/www.hsu-hh.de\/mathematik\/?page_id=2055"},"modified":"2026-06-10T11:28:12","modified_gmt":"2026-06-10T09:28:12","slug":"workshop-women-in-analysis-and-optimization-on-manifolds","status":"publish","type":"page","link":"https:\/\/www.hsu-hh.de\/mathematik\/en\/workshop-women-in-analysis-and-optimization-on-manifolds\/","title":{"rendered":"Workshop: Women in Analysis and Optimization on Manifolds"},"content":{"rendered":"\n
Tuesday, June 30, 2026 – Thursday, July 2, 2026<\/h5>\n\n\n\n
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Analysis and optimization on Riemannian manifolds is a rapidly growing field with deep connections to PDEs, differential geometry, and computational mathematics. Its scope encompasses highly relevant applications such as shape analysis and optimization, matrix completion, and many others. This workshop aims to bring together researchers working at the intersection of analysis and optimization on manifolds and showcase their contributions on this challenging and vibrant area. It will also offer a supportive environment for early-career researchers to present their work, exchange ideas and build lasting professional networks.<\/p>\n\n\n\n

Participants:<\/h2>\n\n\n\n

We welcome female, male and non-binary researchers at various stages in their careers (from graduate student to senior researcher) from all over the world to foster research collaboration and mentorship. <\/p>\n\n\n\n

Dates:<\/h2>\n\n\n\n

Tuesday, June 30, 2026 – Thursday, July 2, 2026<\/p>\n\n\n\n

Workshop language:<\/h2>\n\n\n\n

English<\/p>\n\n\n\n

Program:<\/h2>\n\n\n\n

Please note that oral presentations are invitation-only. Without invitation you will not be allowed to give an oral presentation. However, non-invited participants are very welcome to present a poster and take part in the poster blitz. <\/p>\n\n\n\n

Detailed program:<\/h2>\n\n\n\n
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Time<\/h3>\n<\/div>\n\n\n\n
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Tuesday (30.06.26)<\/h3>\n<\/div>\n\n\n\n
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Wednesday (01.07.26)<\/h3>\n<\/div>\n\n\n\n
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Thursday (02.07.26)<\/h3>\n<\/div>\n<\/div>\n\n\n\n
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10:00 – 11:00<\/h3>\n<\/div>\n\n\n\n
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Cornelia Vizman<\/h3>\n\n\n\n
Shape spaces of decorated\/augmented submanifolds<\/summary>\n
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We focus on shape spaces of submanifolds having the diffeomorphism type of a given closed manifold. By allowing each submanifold to have an additional structure of an intrinsic type, we get decorated shape spaces. The decoration types can be weights, closed 1-forms, submanifolds, foliations, etc.<\/abbr> More general than decorations are augmentations, which are extrinsic structures along the submanifold. Examples include 1-form densities along submanifolds, which help describe the cotangent bundle of a shape space. The Fr\u00e9chet manifolds of decorated\/augmented shape spaces have shown to be useful in describing coadjoint orbits of diffeomorphism groups, including volume preserving, Hamiltonian, and contact diffeomorphisms.<\/p>\n<\/details>\n<\/div>\n\n\n\n

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Caroline Geiersbach<\/h3>\n\n\n\n
Stochastic optimization with perspectives for problems over manifolds<\/summary>\n
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Uncertainty appears in optimization problems whenever data are unknown or incomplete. Optimal solutions may exhibit a significant dependence on those data and mathematical formulations of the optimization problem should take into account these uncertainties. In this talk, we will give an introduction to optimization under uncertainty. We compare models frequently used in the stochastic optimization literature, which incorporate information on parameters or inputs that may not be known exactly. We highlight key theoretical and numerical challenges. Finally, we discuss open questions in optimization over manifolds and illustrate them through case studies in shape optimization, pointing to a promising direction for future research.<\/p>\n<\/details>\n<\/div>\n\n\n\n

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Lidiya Pryymak<\/h3>\n\n\n\n
The diffeomorphism group in PDE-constrained shape optimization using Sobolev-type metrics<\/summary>\n
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Optimal designs for engineering and biomedical structures can be obtained through shape optimization techniques. Hereby, the cost functional is evaluated on a shape space which contains shapes of interest for the optimization problem. Often, the shape space is chosen to be a Riemannian manifold, as it provides the space with a differential structure and moreover, the Riemannian gradient can be computed using a Riemannian metric and the associated pushforward. In this talk, we consider the diffeomorphism group on \u211d<\/mi>2<\/mn><\/msup>\\mathbb{R}^2<\/annotation><\/semantics><\/math>equipped with Sobolev-type metrics of order s<\/mi>\u2208<\/mo>\u2115<\/mi><\/mrow>s \\in \\mathbb{N}<\/annotation><\/semantics><\/math>. This space is an infinite-dimensional smooth manifold and its tangent space is given by smooth vector fields with compact support. Within this setting, concepts from classical shape calculus, such as the shape derivative, coincide with the Riemannian framework. We propose a Riemannian steepest descent algorithm for a shape optimization problem on the diffeomorphism group and demonstrate its performance through numerical examples.<\/p>\n<\/details>\n<\/div>\n<\/div>\n\n\n\n
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11:00 – 11:30<\/h3>\n<\/div>\n\n\n\n
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Discussion\/Networking<\/h3>\n<\/div>\n\n\n\n
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Discussion\/Networking<\/h3>\n<\/div>\n\n\n\n
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Discussion\/Networking<\/h3>\n<\/div>\n<\/div>\n\n\n\n
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11:30 – 12:30<\/h3>\n<\/div>\n\n\n\n
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Alice Barbara Tumpach<\/h3>\n\n\n\n
Optimization over infinite-dimensional manifolds in the presence of symmetries<\/summary>\n
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In this talk, we present different ways to take symmetries into account in an optimization process over an infinite-dimensional manifold. We will start with a general overview of infinite-dimensional manifolds with symmetries, introducing the notions of principal bundles, quotient spaces and sections of principal bundles. Using the example of the minimization of energy over the space of curves on an infinite-dimensional manifold, we will explain various optimization procedures leading to geodesics on quotient spaces. The different procedures will be compared from a theoretical and practical perspective and illustrated with examples from shape analysis. This talk is based on a work with Stephen Preston.<\/p>\n<\/details>\n<\/div>\n\n\n\n

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Elli Hayes<\/h3>\n\n\n\n
Machine construction and exploration of twisted connected sum G2 manifolds<\/summary>\n
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We construct a new dataset of 7-dimensional twisted connected sum G2 manifolds using the tops construction and investigate their geography. In addition, we demonstrate that machine-learning methods can identify matching pairs beyond those satisfying the standard trivial gluing conditions, enabling the discovery and generation of new G2 geometries.<\/p>\n<\/details>\n<\/div>\n\n\n\n

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Project Discussion<\/h3>\n<\/div>\n<\/div>\n\n\n\n
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12:30 – 13:30<\/h3>\n<\/div>\n\n\n\n
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Lunch<\/h3>\n<\/div>\n\n\n\n
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Lunch<\/h3>\n<\/div>\n\n\n\n
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Lunch<\/h3>\n<\/div>\n<\/div>\n\n\n\n
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13:30 – 15:00<\/h3>\n<\/div>\n\n\n\n
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Project Presentation<\/h3>\n<\/div>\n\n\n\n
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Project Discussion<\/h3>\n<\/div>\n\n\n\n
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Project Discussion<\/h3>\n<\/div>\n<\/div>\n\n\n\n
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15:15 – 15:45<\/h3>\n<\/div>\n\n\n\n
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Poster Blitz<\/h3>\n<\/div>\n\n\n\n
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Social Event<\/h3>\n<\/div>\n\n\n\n
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15:45 – 18:00<\/h3>\n<\/div>\n\n\n\n
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Poster Session<\/h3>\n<\/div>\n\n\n\n
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Social Event<\/h3>\n<\/div>\n\n\n\n
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Organizers:<\/h2>\n\n\n\n