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| Summer Term 2021, Doctoral School Events | |
| 2021-03-19 | Doctoral School Seminar (10:00–12:00, Video conference, TU) |
| Michael Missethan (TU. Advisor: M. Kang): Maximum degree in random planar graphs [show abstract] | |
| Daniel Windisch (TU. Advisor: S. Frisch): Prime ideals in infinite products of commutative rings [show abstract] | |
| New Students (TU+KFU) | |
| Benjamin Klahn (TU. Advisor: C. Elsholtz): A Divisor Problem for Polynomials [show abstract] | |
| 2021-04-23 | Doctoral School Seminar (14:00–16:30, Video conference, KFU) |
| Christian Lindorfer (TU. Advisor: W. Woess): Word problems for groups [show abstract] | |
| Panagiotis Spanos (TU. Advisor: W. Woess): Random walks and the Dirichlet problem at infinity [show abstract] | |
| New Students (TU+KFU) | |
| Aqsa Bashir (KFU. Advisor: A. Geroldinger): Stable Domains and their Arithmetic [show abstract] | |
| 2021-05-21 | Doctoral School Seminar (10:00–12:00, Video Conference, TU) |
| Julian Zalla (TU. Advisor: M. Kang): Loose cores and cycles in random hypergraphs [show abstract] | |
| Raphael Watschinger (TU. Advisor: G. Of): An integration by parts formula for the hypersingular boundary integral operator of the heat equation [show abstract] | |
| New Students (TU+KFU) | |
| Richard Huber (KFU. Advisor: K. Bredies): Evolution of Critical Trajectories [show abstract] | |
| 2021-06-18 | Doctoral School Seminar (14:00–16:30, Video conference, KFU) |
| Josef Strini (TU. Advisor: S. Thonhauser): A time-inconsistent stochastic optimal control problem from risk theory [show abstract] | |
| Huan Chen (KFU. Advisor: G. Haase): Reinforcement learning based controller for hybrid electric vehicles | |
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Abstract: Hybrid electric vehicles (HEVs) are attractive approach to tackle the urgent energy saving and emission reduction problem. The HEV’s energy management is a non-linear multi-target problem, which determines the vehicle's performance with respect to fuel consumption, emissions, and drivability. Reinforcement learning (RL) is a state-of-the-art machine learning technique. We are investigating its potential in providing real-time optimal, or nearly optimal control strategies that are realizable in hardware.[hide abstract] | |
| Martin Schwinzerl (KFU. Advisor: G. Haase): Optimising The Numerical Performance and Scalability Of Beam Field Elements In Beam Dynamics Simulations [show abstract] | |
| Thomas Hirschler (TU. Advisor: W. Woess): Comparing Entropy Rates on Finite and Infinite Rooted Trees [show abstract] |