Biography
Dr. Amir Aghabiglou received his PhD in Mechatronic Engineering from Istanbul Technical University (ITU), Turkey, where his research focused on deep learning methods for inverse problems. He previously obtained his MSc and BSc degrees in Mechanical Engineering from the University of Tabriz and Tabriz Azad University, Iran, respectively.
From 2019 to 2022, he was a Research Assistant at ITU, conducting research on deep learning-based MRI reconstruction and machine learning applications in medical imaging.
In 2022, he joined the Biomedical and Astronomical Signal Processing Laboratory (BASPLab) at Heriot-Watt University as a Research Associate. He conceived and led the development of R2D2 (Residual-to-Residual DNN series for high-Dynamic-range imaging), a deep learning framework for fast, high-precision radio interferometric imaging, in collaboration with colleagues at BASPLab. His current research focuses on advancing R2D2 through improved neural network architectures, including Transformer-based models, and developing scalable reconstruction and training pipelines for large-scale scientific imaging.