Graph Signal Processing |
Mathematical Modeling

Nafiseh Ghoroghchian, Dr.

Machine Learning Scientist with extensive experience in developing and deploying large-scale machine learning models and signal processing solutions, particularly within the biomedical domain.

Expertise in end-to-end model development, feature engineering, and high-performance computing, with hands-on skills across Python, PyTorch, and Docker.

Proven track record of implementing scalable ML solutions for clinical applications, optimizing MRI reconstructions, and advancing neuroscience research.

Ph.D. in Electrical and Computer Engineering with a strong research background, complemented by leadership in clinical studies, team mentorship, and community engagement.

My research focuses on developing algorithms to extract biometrics from brain signals, modeling brain network and function, and improving electrophysiological intervention techniques in order to predict and control brain states.

In my recent efforts, I have concentrated on locating regions and timing of stimulations to intervene with the brain in order to treat neurological disorders such as epilepsy. This stimulation exploration has a great potential to increase the efficacy of existing treatment options, including neuromodulation devices, for individuals with neurological disorders using electronic implants in the brain. The goal is to leverage advanced machine learning to identify precise locations that can be stimulated to achieve the best therapeutic results.