Bartosz Krawczyk


Bartosz Krawczyk is an Assistant Professor in the Chester F. Carlson Center for Imaging Science at Rochester Institute of Technology, where he heads Machine Learning and Computer Vision (MLVision) Lab. He received the M.Sc. and Ph.D. degrees from the Wroclaw University of Science and Technology, Wroclaw, Poland, in 2012 and 2015, respectively.

Dr. Krawczyk has authored more than 60 journal articles and more than 100 contributions to conferences. He has coauthored the book Learning from Imbalanced Datasets (Springer, 2018). He is a Program Committee member for high-ranked conferences, such as KDD (Senior PC member), AAAI, IJCAI, ECML-PKDD, IEEE BigData, and IJCNN. He was a recipient of prestigious awards for his scientific achievements such as the IEEE Richard Merwin Scholarship, the IEEE Outstanding Leadership Award, and the Amazon Machine Learning Award, among others. He served as a Guest Editor for four journal special issues and as the Chair for 20 special session and workshops. He is the member of the editorial board for Applied Soft Computing (Elsevier).

Research interests:

  • Machine Learning: class imbalance, ensemble learning, robust algorithms, big data
  • Data Streams: concept drift, adaptive learning, active learning
  • Deep Learning: continual & lifelong learning, adversarial learning, generative models, XAI
  • Computer Vision: representation learning, video & tensor classification
  • Imaging Science: remote sensing, medical image analysis

For more details on my research visit my Google Scholar, ResearchGate, and DBLP pages.


Mar 1, 2024 Two new papers published in Machine Learning and IEEE Internet of Things
Oct 30, 2023 I am included in the Stanford University list of TOP 2% of most cited researchers in AI field
Jun 21, 2023 Multiple fully-funded PhD positions available
Jun 1, 2023 I am included in the World’s Best Computer Science Scientists Ranking by!

selected publications

  1. DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data
    Damien Dablain, Bartosz Krawczyk, and Nitesh V. Chawla
    IEEE Transactions on Neural Networks and Learning Systems, 2022
  2. The class imbalance problem in deep learning
    Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, and 3 more authors
    Machine Learning, 2022
  3. Adversarial concept drift detection under poisoning attacks for robust data stream mining
    Lukasz Korycki, and Bartosz Krawczyk
    Machine Learning, 2022
  4. ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams
    Alberto Cano, and Bartosz Krawczyk
    Machine Learning, 2022