Ozan Özdenizci

Ozan Özdenizci

Research Group Leader, Chair of Cyber-Physical-Systems, Montanuniversität Leoben

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Journal Articles

  • O. Özdenizci, D. Erdoğmuş, “Stochastic mutual information gradient estimation for dimensionality reduction networks”, Information Sciences, 2021. PDF
  • M. Han, O. Özdenizci, T. Koike-Akino, Y. Wang, D. Erdoğmuş, “Universal physiological representation learning with soft-disentangled rateless autoencoders”, IEEE Journal of Biomedical and Health Informatics, 2021. PDF
  • O. Özdenizci, S. Eldeeb, A. Demir, D. Erdoğmuş, M. Akçakaya, “EEG-based texture roughness classification in active tactile exploration with invariant representation learning networks”, Biomedical Signal Processing and Control, 2021. PDF
  • M. Han, O. Özdenizci, Y. Wang, T. Koike-Akino, D. Erdoğmuş, “Disentangled adversarial autoencoder for subject-invariant physiological feature extraction”, IEEE Signal Processing Letters, 2020. PDF
  • O. Özdenizci, Y. Wang, T. Koike-Akino, D. Erdoğmuş, “Learning invariant representations from EEG via adversarial inference”, IEEE Access, 2020. PDF / Code
  • O. Özdenizci, D. Erdoğmuş, “Information theoretic feature transformation learning for brain interfaces”, IEEE Transactions on Biomedical Engineering, 2019. PDF / Code
  • O. Özdenizci, Y. Wang, T. Koike-Akino, D. Erdoğmuş, “Adversarial deep learning in EEG biometrics”, IEEE Signal Processing Letters, 2019. PDF
  • O. Özdenizci, M. Yalçın, A. Erdoğan, V. Patoğlu, M. Grosse-Wentrup, M. Çetin, “Electroencephalographic identifiers of motor adaptation learning”, Journal of Neural Engineering, 2017. PDF
  • S. Weichwald, T. Meyer, O. Özdenizci, B. Schölkopf, T. Ball, M. Grosse-Wentrup, “Causal interpretation rules for encoding and decoding models in neuroimaging”, NeuroImage, 2015. PDF

Peer-Reviewed Conference Publications

  • D. Bethge, P. Hallgarten, T. Grosse-Puppendahl, M. Kari, R. Mikut, A. Schmidt, O. Özdenizci, “Domain-invariant representation learning from EEG with private encoders”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore, 2022. PDF
  • O. Özdenizci, R. Legenstein, “Training adversarially robust sparse networks via Bayesian connectivity sampling”, International Conference on Machine Learning (ICML), 2021. PDF / Code
  • O. Özdenizci, D. Erdoğmuş, “On the use of generative deep neural networks to synthesize artificial multichannel EEG signals”, 10th International IEEE/EMBS Conference on Neural Engineering (NER), Virtual, 2021. PDF
  • M. Han, O. Özdenizci, Y. Wang, T. Koike-Akino, D. Erdoğmuş, “Disentangled adversarial transfer learning for physiological biosignals”, IEEE Engineering in Medicine and Biology Conference (EMBC), Virtual, 2020. PDF
  • O. Özdenizci, T. Meyer, F. Wichmann, J. Peters, B. Schölkopf, M. Grosse-Wentrup, “Neural signatures of motor skill in the resting brain”, IEEE International Conference on Systems, Man, and Cybernetics (SMC), Bari, Italy, 2019. PDF
  • O. Özdenizci, B. Oken, T. Memmott, M. Fried-Oken, D. Erdoğmuş, “Adversarial feature learning in brain interfacing: an experimental study on eliminating drowsiness effects”, 8th Graz Brain-Computer Interface Conference, Graz, Austria, 2019. PDF
  • O. Özdenizci, Y. Wang, T. Koike-Akino, D. Erdoğmuş, “Transfer learning in brain-computer interfaces with adversarial variational autoencoders”, 9th International IEEE/EMBS Conference on Neural Engineering (NER), San Francisco, USA, 2019. PDF / Code
  • O. Özdenizci, C. Cumpanasoiu, C. Mazefsky, M. Siegel, D. Erdoğmuş, S. Ioannidis, M. S. Goodwin, “Time-series prediction of proximal aggression onset in minimally-verbal youth with autism spectrum disorder using physiological biosignals”, IEEE Engineering in Medicine and Biology Conference (EMBC), Honolulu, USA, 2018. PDF
  • O. Özdenizci, S. Y. Günay, F. Quivira, D. Erdoğmuş, “Hierarchical graphical models for context-aware hybrid brain-machine interfaces”, IEEE Engineering in Medicine and Biology Conference (EMBC), Honolulu, USA, 2018. PDF
  • M. S. Goodwin, O. Özdenizci, C. Cumpanasoiu, P. Tian, Y. Guo, A. Stedman, C. Peura, C. Mazefsky, M. Siegel, D. Erdoğmuş, S. Ioannidis, “Predicting imminent aggression onset in minimally-verbal youth with autism spectrum disorder using preceding physiological signals”, 12th EAI International Conference on Pervasive Computing Technologies for Healthcare, New York, USA, 2018. PDF
  • O. Özdenizci, F. Quivira, D. Erdoğmuş, “Information theoretic feature projection for single-trial brain-computer interfaces”, IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Tokyo, Japan, 2017. PDF
  • A. A. Mastakouri, S. Weichwald, O. Özdenizci, T. Meyer, B. Schölkopf, M. Grosse-Wentrup, “Personalized brain-computer interface models for motor rehabilitation”, IEEE International Conference on Systems, Man, and Cybernetics (SMC), Banff, Canada, 2017. PDF
  • O. Özdenizci, M. Yalçın, A. Erdoğan, V. Patoğlu, M. Grosse-Wentrup, M. Çetin, “Correlations of motor adaptation learning and modulation of resting-state sensorimotor EEG activity”, 7th Graz Brain-Computer Interface Conference, Graz, Austria, 2017. PDF
  • O. Özdenizci, M. Yalçın, A. Erdoğan, V. Patoğlu, M. Grosse-Wentrup, M. Çetin, “Pre-movement EEG low beta power is modulated with motor adaptation learning”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, USA, 2017. PDF
  • O. Özdenizci, M. Yalçın, A. Erdoğan, V. Patoğlu, M. Grosse-Wentrup, M. Çetin, “Resting-state EEG correlates of motor learning performance in a force-field adaptation task”, IEEE Signal Processing and Communications Applications Conference, International Workshop on Machine Learning for Understanding the Brain, Ankara, Turkey, 2016. PDF
  • O. Özdenizci, T. Meyer, M. Çetin, M. Grosse-Wentrup, “Adaptive alpha neurofeedback on parieto-occipital cortex for motor learning performance” (in Turkish), IEEE Signal Processing and Communications Applications Conference, Malatya, Turkey, 2015. PDF
  • O. Özdenizci, T. Meyer, M. Çetin, M. Grosse-Wentrup, “Towards neurofeedback training of associative brain areas for stroke rehabilitation”, 6th Graz Brain-Computer Interface Conference, Graz, Austria, 2014. PDF

Theses

  • O. Özdenizci, “Statistical Learning and Inference in Neural Signal Processing: Applications to Brain Interfaces”, Ph.D. Dissertation, Northeastern University, April 2020. PDF
  • O. Özdenizci, “Identifying Neural Correlates of Motor Adaptation Learning for BCI-Assisted Stroke Rehabilitation”, MSc. Thesis, Sabancı University, August 2016. PDF
  • O. Özdenizci, “Neurofeedback Training via Brain-Computer Interfaces for Motor Learning Performance”, BSc. Senior Project, Sabancı University, June 2014.