• Source: Scopus
20172022

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Personal profile

Research profile

In her research, Layla addresses various operational research problems in transportation and logistics. She is particularly interested in shared mobility such as carsharing, bikesharing and ride-hailing. Most of her research focuses on strategic questions such as fleet design, but she always considers the operational implications of the decision. Layla has used various different methods, including mixed integer programming, Markov decision processes, and game theory. She strongly believes in the importance of using the right method for the problem at hand, rather than specializing in a single method. Therefore, she likes collaborating with methodological experts. 

Academic background

Layla obtained her doctorate (Dr. rer. pol.) in 2020 from the Technical University of Munich (TUM) where she worked under the supervision of Prof. Stefan Minner, and collaborated also with Prof. Andreas S. Schulz and Prof. Maximilian Schiffer. During her doctoral studies, she visited Prof. Marco Pavone at Stanford University (Oct. 2019-March 2020). 

Previously, Layla obtained her Master degree in Information systems from TUM (in 2017), and her Bachelor degree from the Cooperative State University Baden-Wurttemberg in Stuttgart (in 2015). During her Bachelor and Master studies, she spent two semesters abroad, one at Reykjavik University (Iceland, in 2016), and one at Staffordshire University (UK, in 2014). 

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 11 - Sustainable Cities and Communities

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  • Dissertation Prize

    Martin, Layla (Recipient), 1 Sep 2021

    Prize: OtherCareer, activity or publication related prizes (lifetime, best paper, poster etc.)Scientific