Title

Reza Sameni

Headshot Placeholder
Reza SAMENI
Title/Position
Associate Professor
Areas of Research

Areas of Research

Biomedical Informatics & Systems Modeling
Contact

Contact

Office 4131, 101 Woodruff CircleGeorgia Tech, Emory
Alphanumerics Lab
Biography

Biography

Dr. Reza Sameni earned a B.Sc. in Electronics Engineering from Shiraz University, an M.Sc. in Biomedical Engineering from Sharif University of Technology, and dual Ph.D. degrees in Biomedical Engineering (Sharif University of Technology) and Signal Processing & Telecommunications (Institut National Polytechnique de Grenoble, INPG). He served as a tenured faculty member and Department Chair at Shiraz University (2008–2018) and later as a senior researcher at GIPSA-lab, Grenoble Alpes University (2018–2020). Since 2020, he has been an Associate Professor of Biomedical Informatics at Emory University, an Adjunct Associate Professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory (since 2024), and the Scientific Director of the Medical Informatics and AI (MIAI) Core at Emory School of Medicine.

Education

Education

  • BS, Electronics Engineering
  • MS, Biomedical Engineering
  • PhD, Biomedical Engineering & Signal Processing
Affiliated Centers & Institutes

Affiliated Centers & Institutes

Research Interests

Research Interests

Dr. Sameni leads the Alphanumerics Lab, which develops models and software that turn high-resolution physiological data and electronic health record data into actionable clinical information. Major application areas include cardiology, brain health, maternal–fetal health, digital psychiatry, multimodality, and AI-enabled clinical decision support. The lab also supports reproducible research through open-source tools, including the Open-Source Electrophysiological Toolbox (OSET), and helps organize community benchmarking efforts such as the annual PhysioNet challenges.

Teaching Interests

Teaching Interests

Model-based machine learning, Biomedical Signal Processing, Estimation Theory
Publications

Publications

Google Scholar
(For latest publications refer to Google Scholar)

Li, Q., Barnett, K., Xue, J., Albert, D., Deepanshi, ., Rad, A. B., Sameni, R., & Clifford, G. D. (2026). Fusion-based QT interval estimation for enhanced long QT detection on a South African population using mobile ECG. Physiological Measurement. https://doi.org/10.1088/1361-6579/ae3fe4

Somayyeh Mousavi, S., Karimi, S., Hassannia, M., Koscova, Z., Bahrami Rad, A., Albert, D., Clifford, G. D., & Sameni, R. (2025). Estimating blood pressure from the electrocardiogram: findings of a large-scale negative results study. Physiological Measurement, 46(11), 115005. https://doi.org/10.1088/1361-6579/ae1926

Karimi, S., Shah, A. J., Clifford, G. D., & Sameni, R. (2025). Bidirectional Translation Between ECG and PCG. In 2025 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI) (pp. 1–5). IEEE. 2025 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI). https://doi.org/10.1109/bhi67747.2025.11269464

Koscova, Z., Shah, A., Rad, A. B., Li, Q., Clifford, G. D., & Sameni, R. (2025). A Noise-Robust Model-Based Approach to T-Wave Amplitude Measurement and Alternans Detection. IEEE Transactions on Biomedical Engineering, 1–11. https://doi.org/10.1109/tbme.2025.3616055

Hassannia, M., & Sameni, R. (2025). A Neural Network Architecture for ECG Lead Reconstruction: Separating Shared and Lead-Specific ECG Characteristics. In Computing in Cardiology Conference (CinC) (Vol. 52). Computing in Cardiology. 2025 Computing in Cardiology Conference. https://doi.org/10.22489/cinc.2025.337

Sameni, R. (2025). On the Geometry of Receiver Operating Characteristic and Precision-Recall Curves. arXiv. https://doi.org/10.48550/ARXIV.2504.02169

Shivashankara, K. K., Deepanshi, Mehri Shervedani, A., Clifford, G. D., Reyna, M. A., & Sameni, R. (2024). ECG-Image-Kit: a synthetic image generation toolbox to facilitate deep learning-based electrocardiogram digitization. Physiological Measurement, 45(5), 055019. https://doi.org/10.1088/1361-6579/ad4954