Andreas Grigorjew

About me

Welcome! I am a postdoctoral researcher at LAMSADE, Université Paris Dauphine-PSL with Michail Lampis. I finished my PhD in 2025 at the University of Helsinki supervised by Alexandru I. Tomescu.

My research interests broadly lie in theoretical computer science and include graph theory, algorithms and combinatorics.
In spring 2024, I visited the Applied Algorithms Group at the Montana State University.

In my free time, I enjoy climbing/bouldering and spending time in nature.

You are welcome to contact me via email: contact [at] andreasgrigorjew [dot] de (PGP key).

Research

Publications and preprints

• Manuel Cáceres, Andreas Grigorjew, Wanchote Po Jiamjitrak, Alexandru I. Tomescu
  Maximum Coverage k-Antichains and Chains: A Greedy Approach
  arXiv, 2025 (view preprint)
• Andreas Grigorjew, Wanchote Po Jiamjitrak, Brendan Mumey, Alexandru I. Tomescu
  Parameterised Approximation and Complexity of Minimum Flow Decompositions
  arXiv, 2024 (view preprint)
• Andreas Grigorjew, Fernando H. C. Dias, Andrea Cracco, Romeo Rizzi, Alexandru I. Tomescu
  Accelerating ILP solvers for Minimum Flow Decompositions through search space and dimensionality reductions
  SEA 2024 - International Symposium on Experimental Algorithms, 14:1-14:19, 2024 (view)
  Best paper award runner-up
• Manuel Cáceres, Massimo Cairo, Andreas Grigorjew, Shahbaz Khan, Brendan Mumey, Romeo Rizzi, Alexandru I. Tomescu, Lucia Williams
  Width Helps and Hinders Splitting Flows
  ACM Transactions on Algorithms, 20(2), 1--20, 2024 (view extended version)
  ESA 2022 - European Symposium on Algorithms (Track A), 31:1--31:14, 2022 (view)
• Andreas Grigorjew, Artur Gynter, Fernando Dias, Benjamin Buchfink, Hajk-Georg Drost, Alexandru I. Tomescu
  Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD
  Genome Biology 24, 168, 2023 (view)

PhD thesis: Algorithms and Graph Structures for Splitting Network Flows, in Theory and Practice

Software

• Optimized FD: An optimized flow decomposition solver using Integer Linear Programming, for exact optimum and heuristic solutions (GitHub).
  Flow decompositions are used e.g. for RNA transcriptict assembly or viral strain reconstruction.
• EMERALD: a protein sequence aligner that finds protein regions preserved in the suboptimal alignment space (GitHub).

Teaching

I was a teaching assistant in the following courses holding exercise classes:

• Models of Computation, spring 2024 (Helsinki)
• Models of Computation, spring 2023 (Helsinki)
• Elements of Bioinformatics, autumn 2022 (Helsinki)
• Design and analysis of algorithms, autumn 2021 (Helsinki)
• Mathematik für Data Science und Physik Studierende I, winter 2021 (Erlangen)
• Analysis III, winter 2019 (Erlangen)
• Theorie der Programmierung, summer 2019 (Erlangen)
• Theorie der Programmierung, summer 2018 (Erlangen)