Prof. Dr. Josif Grabocka

Machine Learning Lab

Department Engineering
Machine Learning Lab

About

Prof. Dr. Josif Grabocka has been a full professor of Machine Learning at UTN since December 2023. Before that, he was an assistant professor (W1) of Representation Learning at the University of Freiburg (2019–2023), after receiving his Ph.D. degree from the University of Hildesheim in 2016. Prof. Grabocka’s research interests focus on the optimization of machine and deep learning pipelines from the perspective of hyperparameter optimization. In addition, he is interested in optimal control and reinforcement learning, learning from tabular data, as well as multi-objective optimization.

Prof. Grabocka is an Area Chair at the International Conference on Learning Representations (ICLR) and a Senior Area Chair at the International Conference on Automated Machine Learning (AutoML). His research has been published in prestigious international venues in the field of machine and deep learning, such as ICLR, NeurIPS, SIGKDD, etc.

At UTN, he has been the Coordinator of the M.Sc. program on AI and Robotics (AIR) since 2024. Prof. Dr. Grabocka teaches courses in the AIR program on Deep Learning and Large Language Models.

 

Current Projects

 

Selected Publications

  • Arlind Kadra, Maciej Janowski, Martin Wistuba, Josif Grabocka
    Quickly Learning Which Pretrained Model to Finetune and How
    International Conference on Automated Machine Learning (AutoML 2024)
    Runner-up Best Paper Award
  • Arlind Kadra, Maciej Janowski, Martin Wistuba, Josif Grabocka
    Quickly Learning Which Pretrained Model to Finetune and How
    International Conference on Learning Representations     (ICLR 2024)
  • Arlind Kadra, Maciej Janowski, Martin Wistuba, Josif Grabocka
    Scaling Laws for Hyperparameter Optimization
    Neural Information Processing Systems (NeurIPS 2023)
  • Sebastian Pineda Arango, Josif Grabocka
    Deep Pipeline Embeddings for AutoML
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)
  • Abdus Khazi, Sebastian Pineda Arango, Josif Grabocka
    Deep Ranking Ensembles for Hyperparameter Optimization
    International Conference on Learning Representations (ICLR 2023)
  • Gresa Shala, Thomas Elsken, Hadi Jomaa, Frank Hutter, Josif Grabocka
    Transfer NAS with Meta-Learned Bayesian Surrogates
    International Conference on Learning Representations (ICLR 2023)
  • Gresa Shala, Andre Biedenkapp, Frank Hutter, Josif Grabocka
    Gray-Box Gaussian Processes for Automated Reinforcement Learning
    International Conference on Learning Representations (ICLR 2023)
  • Martin Wistuba, Arlind Kadra, Josif Grabocka
    Supervising the Multi-Fidelity Race of Hyperparameter Configurations
    Neural Information Processing Systems (NeurIPS 2022)
  • Ekrem Öztürk, Fabio Ferreira, Hadi Jomaa, Josif Grabocka and Frank Hutter
    Zero-shot AutoML with Pretrained Models
    International Conference on Machine Learning (ICML 2022)
  • Samuel Müller, Noah Hollmann, Sebastian Pineda Arango, Josif Grabocka, Frank Hutter
    Transformers Can Do Bayesian Inference
    International Conference on Learning Representations (ICLR 2022)
  • Sebastian Pineda Arango, Hadi Samer Jomaa, Martin Wistuba, Josif Grabocka
    HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML
    Neural Information Processing Systems, Datasets and Benchmarks Track (NeurIPS 2021)
  • Arlind Kadra, Marius Lindauer, Frank Hutter, Josif Grabocka
    Well-tuned Simple Nets Excel on Tabular Datasets
    Neural Information Processing Systems (NeurIPS 2021)
  • Michael Ruchte, Josif Grabocka
    Scalable Pareto Front Approximation for Deep Multi-Objective Learning
    IEEE International Conference on Data Mining (ICDM 2021)
  • Ahmed Rashed, Lars Schmidt-Thieme and Josif Grabocka.
    A Guided Learning Approach for Item Recommendation via Surrogate Loss Learning
    ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021)
  • Martin Wistuba and Josif Grabocka
    Few-Shot Bayesian Optimization with Deep Kernel Surrogates
    International Conference on Learning Representations (ICLR 2021)
  • Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka
    Dataset2vec: Learning dataset meta-features
    Journal of Data Mining and Knowledge Discovery (DAMI 2020)
  • Rafael R. Drumond, Lukas Brinkmeyer, Josif Grabocka, Lars Schmidt-Thieme
    HIDRA: Head Initialization across Dynamic targets for Robust Architectures.
    SIAM International Conference on Data Mining (SDM 2020)
  • Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
    Attribute-aware non-linear co-embeddings of graph features
    ACM Conference on Recommender Systems (RecSys 2019)
  • Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
    Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019)

 

List of publications of Prof. Dr. Josif Grabocka on Google Scholar

List of publications of Prof. Dr. Josif Grabocka on dblp