Sebastian Buschjäger

Sometimes I do stuff.

I am a postdoctoral researcher and the Coordinator for Resource-Aware Machine Learning at the Lamarr Institute. Before that, I was a Ph.D. student in the artificial intelligence group at TU Dortmund University in Germany. There, I participated in the Collaborative Research Center SFB 876, project A1 in which I studied novel machine learning methods for embedded systems and small devices. I received my Ph.D. in 2022 with distinction (summa cum laude) titled “Ensemble learning with discrete classifiers on small devices.” Apart from research, I play badminton, run, and watch too many movies.

My formal CV is available in German or English.

research topics

  • Machine Learning Ensemble learning, model application, submodular functions
  • Computer Architecture Architecture-dependent optimizations and code generation, custom architectures/FPGAs, embedded devices

selected publications

  1. PhD Thesis
    Ensemble learning with discrete classifiers on small devices
    Buschjäger, Sebastian
  2. Shrub Ensembles for Online Classification (to appear, accepted)
    Buschjäger, Sebastian, Hess, Sibylle, and Morik, Katharina
    In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22) 2022
  3. TECS
    Efficient Realization of Decision Trees for Real-Time Inference (to appear, accepted)
    Chen, Kuan-Hsun, Hsu, Chia-Hui, Hakert, Christian, Buschjäger, Sebastian, Lee, Chao-Lin, Lee, Jenq-Kuen, Morik, Katharina, and Chen, Jian-Jia
    ACM Transactions on Embedded Computing Systems 2022
  4. There is no Double-Descent in Random Forests
    Buschjäger, Sebastian, and Morik, Katharina
  5. Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement
    Buschjäger, Sebastian, and Morik, Katharina
  6. ECML
    Very Fast Streaming Submodular Function Maximization
    Buschjäger, Sebastian, Honysz, Philipp-Jan, Pfahler, Lukas, and Morik, Katharina
    In Joint European Conference on Machine Learning and Knowledge Discovery in Databases 2021