Abdullah Saydemir

Merhaba!

I am a master’s student at Technical University of Munich interested in machine learning and its applications in natural sciences. Currently, I am writing my master’s thesis on state-space models. Lately, I developed generative neural networks for turbulent flow simulations. Before, I studied FNOs for Lattice-Boltzmann simulations, Laplacians for graph neural networks, graph neural PDEs for protein essentiality prediction, and drug scoring for cancer treatment. I am the first author/co-author of three papers on a completely different topic, yield of research during my bachelor’s years.

I would like to pursue a PhD degree to eventually become a professor. I am excited to collaborate with leading experts in the field.

Interests
  • Machine Learning
  • Applied ML
  • Natural Sciences
Education
  • MSc in Computer Science

    Technical University of Munich, DE

  • BSc in Computer Science, 2022

    Özyeğin University, Türkiye

  • Non-Degree Exchange Student, 2021

    Oregon State University, USA

Publications

(2024). Unfolding Time: Generative Modeling for Turbulent Flows in 4D. AI for Science Workshop @ ICML 2024.

DOI

(2023). Genetic Algorithms and Heuristics Hybridized for Software Architecture Recovery. Automated Software Engineering Journal.

Project DOI

(2022). HYGAR: A Hybrid Genetic Algorithm for Software Architecture Recovery. In Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing (SAC ‘22).

Project DOI

(2021). On the Use of Evolutionary Coupling for Software Architecture Recovery. 15th National Software Engineering Symposium of Türkiye (UYMS 2021).

Project DOI

Research Experience

 
 
 
 
 
Research Assistant
Apr 2023 – Oct 2024 Munich
  • Worked on generative diffusion models for turbulent flow simulation with Navier‑Stokes equations in 4D. (10/2023 - 10/2024)
  • Integrated non-conventional Laplacians to spectral GNNs and measured their performance in different heterophily levels. (04/2023 - 10/2023)
  • Surveyed the origins of and sota graph neural PDEs. (04/2023 - 10/2023)
 
 
 
 
 
Research Assistant
Sep 2023 – Aug 2024 Munich
  • Modeled collision operators in Lattice‑Boltzmann equations with physics inspired geometric deep learning models as part of interdisciplinary project.
 
 
 
 
 
Research Assistant
Mar 2021 – Jan 2023 Istanbul
  • Built automated systems for investigating the effects of evolutionary coupling in software architecture recovery.
  • Implemented encoder & decoder functions facilitating arithmetic crossover in genetic algorithms for a continuous optimizer.
 
 
 
 
 
Intern
Feb 2022 – Mar 2022 Istanbul
  • Worked on drug repurposing for personal prescription for lung adenocarcinoma, breast cancer, and kidney cancer.
  • Coded a drug scoring function using tissue specific GTEx, essentiality, and topological data.
 
 
 
 
 
Teaching Assistant
Mar 2019 – Aug 2021 Istanbul

Assisted with preparing course material, conducting tutorials, delivering office hours.

  • Discrete Mathematics for Computer Science (09/2020 – 09/2021)
  • Differential Equations (03/2020 – 06/2020)
  • Calculus II (03/2019 – 06/2020)
  • Calculus I (03/2019 – 06/2020)

Work Experience

 
 
 
 
 
Software Engineer
Mar 2022 – Mar 2023 Remote
  • Developed the fuel estimation algorithm for haul trucks for Komatsu & Modular Mining.
  • Coded an estimator that produces possible missions and refuel windows in the future using the prior missions of a truck.
 
 
 
 
 
Embedded Software Engineer
Mar 2021 – Jan 2022 Istanbul
  • Coded an audio analyzer in Python using PESQ 862 to find how good an audio file is.
  • Contributed to WiFi analyzer that scans the network and extracts relevant information.
  • Implemented a testbed with prplMesh, MiniNet and other hardware simulators on MIPS architecture.
 
 
 
 
 
Intern, Treasury and Investment Operations
Jul 2019 – Sep 2019 Istanbul
  • Examined and compiled financial information obtained from ledger accounts and bank statements.