Introduction
I am a PhD candidate in the CoRDS Doctoral Network (University of Vienna, in collaboration with University of Bologna and Hapag-Lloyd). My work focuses on combinatorial optimization with a particular interest in logistics and complex planning problems.
I have experience in mathematical programming, metaheuristics, and software engineering, as well as research and teaching in areas such as scheduling, routing, packing, and multi-agent coverage path planning.
I am passionate about developing robust, interpretable, and efficient decision-support methods for challenging real-world optimization problems.
Within the CoRDS Doctoral Network, my research addresses large-scale optimization challenges in container shipping, with a focus on robust decision-making under uncertainty. In particular, I work on problems such as empty container repositioning (ECR), where stochastic effects and solution stability play a critical role in real-world performance.
About
My work lies at the intersection of operations research and algorithm engineering. I develop mathematical and algorithmic methods for complex decision-making problems in logistics and planning, with a particular focus on robustness under uncertainty and the stability of solutions across repeated decision processes. My approach combines mathematical programming, metaheuristics, and low-level engineering techniques.
Technical Profile
My research is strongly shaped by implementation as well as modeling. I primarily work with Python and Rust, and I also have solid experience with C and C++ as well as prior experience with Java and C#. On the optimization side, I work extensively with mixed-integer programming, constraint programming, and metaheuristics, with particular experience using Gurobi and OR-Tools CP-SAT to build exact and hybrid solution methods.Education
I studied Computer Science at Technische Universität Braunschweig, where I built my foundation in optimization, algorithms, and computational problem-solving. Alongside my growing interest in operations research, I also gained a broad computer science background spanning programming, system-level programming, computer networks, relational database design, theoretical computer science, and related areas. During my Erasmus+ program at the University of Maribor, I focused on evolutionary algorithms and received mentorship in using them as metaheuristics for solving complex geometric-combinatorial routing and scheduling problems.
Research & Teaching
I worked as a research assistant at the Institute of Automotive Management and Industrial Production at TU Braunschweig for around two semesters, where I designed and implemented genetic algorithms for real-world job scheduling and disassembly line planning problems in the automotive industry. My work focused on adapting evolutionary and metaheuristic methods to practical, industry-inspired optimization problems with complex combinatorial structure.
My bachelor thesis contributed to the publication How Low Can We Go? Minimizing Interaction Samples for Configurable Systems, for which I implemented a scalable matheuristic based on large neighborhood search and mixed-integer programming to obtain dual bounds for a configuration planning problem in the automotive industry. This work eventually led to my coauthorship on the paper.
I also worked as a teaching assistant for the Algorithm Engineering lecture and as a research assistant in the Algorithms Lab. In both roles, I supported students in learning and applying mathematical programming techniques to assignment, scheduling, routing, and flow problems motivated by logistics and medicine. I also helped design the teaching material and exercises, which gave me valuable experience in explaining algorithmic ideas clearly and guiding students through challenging optimization problems.