M.Sc. Teemu Kuosmanen defends his PhD thesis "On Stochasticity and Control of Evolving Populations" on Thursday the 4th of June 2026 at 12 in the University of Helsinki Main Building, Auditorium Karolina Eskelin (U3032, Fabianinkatu 33, 3rd floor). His opponent is Professor, Director Arne Traulsen (Max Planck Institute for Evolutionary Biology, Germany) and custos Professor Ville Mustonen (University of Helsinki). The defence will be held in English.
The thesis of Teemu Kuosmanen is a part of research done in the Department of Computer Science and in the Bioinformatics and Evolution group at the University of Helsinki. His supervisor has been Professor Ville Mustonen (University of Helsinki).
On Stochasticity and Control of Evolving Populations
Evolution is the process that has generated the extraordinary diversity of life. Evolutionary theory can also provide explanations as to why we age, get cancer, or why drugs lose their efficacy. Recent advances have shown that evolution might be much more repeatable and predictable than previously thought, which has inspired new research devoted to understanding whether evolutionary theory could be applied to solve some of the most pressing biological, technological, and medical problems. To facilitate progress in these important areas, more detailed theoretical and quantitative understanding of eco-evolutionary processes is also needed.
This thesis develops mathematical and computational models that can be used to better understand, predict, and control evolving cell populations. In particular, it introduces a birth-death framework that provides a way to connect classical population genetic theory with explicit population regulation and ecological feedback. Using this framework, it is shown how key concepts of evolutionary theory can be self-consistently derived starting from the underlying demographic processes of birth and death.
Throughout the thesis, special attention is paid to stochasticity that invariably affects all biological processes, including ecological and evolutionary dynamics. We demonstrate the relevance of stochastic population dynamics by studying the establishment of novel mutations, which we show significantly depends on the turnover rate of the mutant. We characterize a systematic turnover bias which may act on longer timescales. Finally, we investigate the ergodicity of relevant eco-evolutionary processes and discuss the implications of non-ergodicity for the foundations of eco-evolutionary theory.
An important application of the presented theory is the study of cancer and drug resistance evolution. To this end, we apply and develop methods of optimal control theory in the eco-evolutionary context. We provide insights into treatment optimization by formulating the problem in an eco-evolutionarily informed way using evolutionary rescue theory and by considering various ecological and evolutionary costs that the treatment may realize. We then solve the optimal treatment strategy in the case where the drug therapy itself may enhance the evolvability of the target population.
In summary, this thesis contributes to the foundations of a more unified eco-evolutionary theory that is broadly relevant for the study of evolving systems.
Availability of the dissertation
An electronic version of the doctoral dissertation will be available in the University of Helsinki open repository Helda at
Printed copies will be available on request from Teemu Kuosmanen: