Dr. Safaa Eldeeb received her PhD in Electrical and Computer Engineering from the University of Pittsburgh. She is a Research Instructor in the Department of Psychiatry at the University of Pittsburgh School of Medicine. Her research lies at the intersection of machine learning, biomedical signal processing, computational psychiatry, and precision mental health.
Dr. Eldeeb's research focuses on understanding the mechanisms underlying emotion dysregulation and their role in mental health outcomes among autistic and non-autistic individuals. She develops and applies advanced machine learning and statistical methods to characterize heterogeneity in emotional experiences and identify factors associated with non-suicidal self-injury (NSSI), suicidal thoughts and behaviors, and related mental health outcomes.
Her work integrates multimodal data sources, including physiological signals collected through wearable biosensors, electroencephalography (EEG), and ecological momentary assessment (EMA), to identify behavioral and biological markers of risk and resilience. Through computational approaches, she seeks to uncover clinically meaningful subgroups, improve risk identification, and advance personalized approaches to prevention, assessment, and intervention for neurodevelopmental and psychiatric conditions
- PhD, Electrical and Computer Engineering, University of Pittsburgh
- NIH-Funded IMPACT T32 Training Program, University of Pittsburgh