Research I've written, reviewed, and published.
Peer-reviewed papers across brain-computer interfaces, machine learning, robotics, and biomechanics, published in international journals and conferences.
- 6Biomedical Signal Processing and Control
NF-EEG: A Generalized CNN Model for Multiclass EEG Motor Imagery Classification Without Signal Preprocessing for Brain-Computer Interfaces
E. Arı, E. Taçgın
A convolutional neural network that classifies multiple motor imagery classes directly from raw EEG, with no preprocessing step, so it can run in real-time systems.
- 5Brain Sciences
Input Shape Effect on Classification Performance of Raw EEG Motor Imagery Signals with Convolutional Neural Networks for Use in Brain-Computer Interfaces
E. Arı E. Taçgın
A study of how the way raw EEG is shaped into network input changes CNN classification accuracy for motor imagery.
Evaluation of Stress Distribution in Mandibular Donor Site After Harvesting Bone Grafts of Different Sizes from the Symphysis
M Yalçın, E. Arı
A finite element study of how the size of a bone graft taken from the chin region affects stress in the donor site.
- 3CoRL 2020
Three-Dimensional Finite Element Analysis of the Effect of Endosteal Implants with Different Macro Designs on Stress Distribution in Different Bone Qualities
M. Yalçın, B. Kaya, N. Laçin, E. Arı
A 3D finite element comparison of how implant macro design and bone quality change stress distribution around dental implants.
- 2
- 12016
Determination of Tool Wear with Vibration Measurements in the Drilling Process of Glass Fiber-Reinforced Composite Material EPGC 201
E. Arı, E. Kılıçkap, M. Hüseyinoğlu
Detects tool wear in composite drilling from vibration measurements, so wear can be monitored without stopping the process.
- 1PH.D. THESIS - MARMARA UNIVERSITY - 2023
Brain-Computer Interface Design and Implementation Using Machine Learning with User Feedback
Emre Arı
A convolutional neural network that classifies multiple motor imagery classes directly from raw EEG, with no preprocessing step, so it can run in real-time systems and a study of how the way raw EEG is shaped into network input changes CNN classification accuracy for motor imagery.
- 1M.SC. THESIS - DICLE UNIVERSITY - 2015
Determination of Tool Wear with Vibration Measurements in the Drilling Process of Glass Fiber-Reinforced Composite Material (EPGC 201)
Emre Arı
Detects tool wear in composite drilling from vibration measurements, so wear can be monitored without stopping the process.
Interested in research collaboration?
I'm always open to research collaborations that push on genuinely hard problems. If your work intersects with mine, let's find out if there's something worth building together.