Sven Jäger
I am a postdoctoral researcher in combinatorial optimization at the Optimization Research Group of the RPTU in Kaiserslautern. My research is mainly concerned with approximation and online algorithms, in particular for scheduling problems, and, more recently, game-theoretic methods in public transport applications, see SynphOnie.
Between 2016 and 2021, I did my PhD in the COGA Group at TU Berlin under the supervision of Martin Skutella. Afterwards, I worked one year in the Optimization Division of the Fraunhofer Institute for Industrial Mathematics.
This summer semester I give a seminar on Algorithmic Game Theory.
Publications
Sven Jäger
My coauthors
- Abhishek Awasthi
- Michael Bortz
- Karl Däubel
- Güncel Düzgün
- Petr Gregor
- Mehmet Gültas
- Raoul Heese
- Sebastian Herzog
- Neil Jami
- Caitlin Jones
- Dominik Leib
- Neele Leithäuser
- Cornelia Meckbach
- Torsten Mütze
- Astrid Niederle
- Guillaume Sagnol
- Joe Sawada
- Manfred Scheucher
- Daniel Schmidt genannt Waldschmidt
- Anita Schöbel
- Tobias Seidel
- Martin Skutella
- Sebastian Velten
- Stephan Waack
- Philipp Warode
- Christian Weiß
- Kaja Wille
- Edgar Wingender
Talks
Scheduling Unrelated Parallel Machines with Attribute-Dependent Setup Times: a Case Study
Generalizing the Kawaguchi-Kyan Bound to Stochastic Parallel Machine Scheduling
- 22nd Combinatorial Optimization Workshop 2018, ,
- 35th International Symposium on Theoretical Aspects of Computer Science (STACS 2018), ,
- 23rd International Symposium on Mathematical Programming (ISMP 2018), ,
- BMS – BGSMath Junior Meeting 2019, ,
- 23rd Workshop on Future Research in Combinatorial Optimization (FRICO 2019),
Teaching
In the summer semester 2024 I am giving a block seminar on Algorithmic Game Theory.
In the past I was involved in the following courses.
- Winter Semester 2023/24: Lecturer for Algorithmic Game Theory, RPTU Kaiserslautern-Landau
- Summer Semester 2023: Teaching assistant for Lineare und Netzwerkoptimierung and supervision of two groups during their Fachpraktikum, RPTU Kaiserslautern-Landau
- Winter Semester 2022/23: Reading Course Optimization (together with Vera Grafe and Anita Schöbel), TU Kaiserslautern
- Summer Semester 2021: Teaching assistant for theoretical homework and exams for Computerorientierte Mathematik II, TU Berlin
- Winter Semester 2020/21: Teaching assistant for Introduction to Linear and Combinatorial Optimization (ADM I), TU Berlin
- Summer Semester 2020: Teaching assistant for Discrete Optimization (ADM II), TU Berlin
- Winter Semester 2019/20: Teaching assistant for Introduction to Linear and Combinatorial Optimization (ADM I), TU Berlin
- Summer Semester 2019: Teaching assistant for Discrete Optimization (ADM II), TU Berlin
- Winter Semester 2018/19: Teaching assistant for Introduction to Linear and Combinatorial Optimization (ADM I), TU Berlin
- Summer Semester 2018: Teaching assistant for programming exercises for Computerorientierte Mathematik II, TU Berlin
- Winter Semester 2017/18: Teaching assistant for programming exercises for Computerorientierte Mathematik I, TU Berlin
- Summer Semester 2017: Teaching assistant for theoretical homework and exams for Computerorientierte Mathematik II, TU Berlin
- Winter Semester 2016/17: Teaching assistant for theoretical homework for Computerorientierte Mathematik I, TU Berlin
- Summer 2015: Student assistant for the mathematisches Propädeutikum für Studierende der Agrar- und Forstwissenschaften, Uni Göttingen
- Winter Semester 2012/13: Student assistant for Informatik III, Uni Göttingen
- Winter Semester 2011/12: Student assistant for Informatik III, Uni Göttingen
Computerorientierte Mathematik I
First course on algorithms and programming for math bachelor students.
Topics: running time, number representations, binary search, graphs, sorting, Gaussian elimination, spanning trees, matroids, dynamic programming, introduction to programming
Computerorientierte Mathematik II
Second course on algorithms and programming for math bachelor students.
Topics: data structures, Huffman codes, shortest paths, Turing machines, computability, complexity, object orientation
Introduction to Linear and Combinatorial Optimization (ADM I)
Introductory course for math bachelor and master students.
Topics: Simplex algorithm, LP duality, paths and trees, maximum flows, min-cost flows, maximum bipartite matchings, stable matchings, ellipsoid method, large-scale linear programming, sensitivity analysis
Discrete Optimization (ADM II)
Advanced course for math bachelor and master students.
Topics: Branchings and arborescences, maximum matchings, minimum-cost perfect matchings, T-joins, matroids, total unimodularity, total dual integrality, Gomory-Chvátal cutting planes, branch-and-bound algorithm, Lagrangian dual, subgradient method