Former 2-Year Postdoctoral Fellows or former 5-Year Research Fellows with a research grant at the University of Konstanz count as "Fellows".

Sidney Carls-Diamante



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At the Zukunftskolleg since 07/2020 (Postdoctoral Fellow until 06/2023)

Affiliated with the Department of Philosophy

Project: Philosophical Explorations of Bipolar Disorder

Bipolar disorder (BD) is a severe and common lifelong mental illness with extensive existential ramifications alongside its psychological and physical symptoms. These existential issues - which are crucial to bipolar individuals' wellbeing - are traditionally philosophical topics. However, philosophical investigations that could address and resolve these concerns (e.g. whether BD is inseparable from one's personality) and other conceptual difficulties (e.g. whether bipolar depression and major depressive disorder are distinct) that influence how bipolar individuals and clinicians understand and handle the illness are sparse.
As BD has not been subjected to extensive philosophical scrutiny, conceptual issues about its nature, manifestations, and management have been neglected. It is necessary to address and identify these issues, as they scaffold understanding how BD affects individuals, dealing with its symptoms, devising treatment programs, developing new medications, future descriptions in psychiatric manuals such as the DSM and ICD, and even insurance coverage policies.

Violeta Ivanova-Rohling



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Affiliated with the Department of Physics

Project: Strategies for improving the quality of solutions, discovered by machine learning algorithms for problems in quantum state tomography

Due to the rapidly increasing presence of artifical intelligence in daily life, it is demanded that the algorithms for machine learning are dependable and safe. The quality of the solutions (models), which these algorithms find, has to be as high as possible. The project will deal with improving the quality which machine learning algorithms find by using two main approaches. One is Widening, which uses parallel compute resources to improve the exploration of the search space and discover better models. The other approach which we will use to improve the learning algorithms is to incorporate invariants to certain transformations, such as symmetries, in the algorithms with the goal of finding better models. An example of this encoding invariance under symmetry transformations into neural network architectures.

Fellow since 06/2020

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Publications on KOPS