Specializing In:
- Artificial Intelligence in Healthcare
- Machine Learning in Healthcare
- Surgical Skill Assessment
- Pain Management
- Cognitive Assessment
- Brain and Behavior
Research Interests:
- Developing evaluation models for surgical skills using physiological signals
Biography
I am an Assistant Professor in the Department of Urology at Roswell Park Comprehensive Cancer Center in Buffalo, NY. My background spans engineering and computer science, and I specialize in the application of machine learning and deep learning to healthcare challenges. My research is dedicated to enhancing oncology care and includes three main focuses: developing evaluation models for surgical training and patient safety using surgeons’ physiological signals, designing algorithms to monitor the mental health of cancer patients through physiological data, and advancing the objective assessment of pain severity using functional near-infrared spectroscopy (fNIRS) in oncology patients. I have co-authored over 30 peer-reviewed journal articles and conference papers, and my work has been recognized and supported by the National Institutes of Health (NIH).
Positions
Roswell Park Comprehensive Cancer Center
- Assistant Professor of Oncology
- Department of Urology
Background
Education and Training
- 2018 - PhD - Mechanical Engineering, State University of New York at Buffalo, Buffalo, NY
- 2008 - MSc - Aerospace Engineering, Sharif University of Technology, Tehran, Iran
Honors & Awards
- 2020-2025 - Recipient of NIH Grant: R01EB029398, National Institute of Biomedical Imaging and Bioengineering, Role: Principal Investigator
- 2022-2025 - Recipient of Grant: 3R01EB029398-03S1, National Institute On Aging, Role: Principal Investigator
Publications
1) Shafiei, S.B., Shadpour, S., Sasangohar, F., Mohler, J.L., Attwood, K. and Jing, Z., 2024. Development of performance and learning rate evaluation models in robot-assisted surgery using electroencephalography and eye-tracking. npj Science of Learning, 9(1), p.3.
2) Shadpour, S., Shafqat, A., Toy, S., Jing, Z., Attwood, K., Moussavi, Z. and Shafiei, S.B., 2023. Developing cognitive workload and performance evaluation models using functional brain network analysis. npj Aging, 9(1), p.22.
3) Shafiei, S.B., Shadpour, S. and Shafqat, A., 2024. Mental Workload evaluation using weighted phase lag index and coherence features extracted from EEG data. Brain research bulletin, p.110992.
4) Shafiei, S.B., Shadpour, S., Intes, X., Rahul, R., Toussi, M.S. and Shafqat, A., 2023. Performance and learning rate prediction models development in FLS and RAS surgical tasks using electroencephalogram and eye gaze data and machine learning. Surgical Endoscopy, 37(11), pp.8447-8463.
5) Shafiei, S.B., Shadpour, S., Mohler, J.L., Sasangohar, F., Gutierrez, C., Seilanian Toussi, M. and Shafqat, A., 2023. Surgical skill level classification model development using EEG and eye-gaze data and machine learning algorithms. Journal of robotic surgery, 17(6), pp.2963-2971.
6) Shafiei, S.B., Shadpour, S., Mohler, J.L., Attwood, K., Liu, Q., Gutierrez, C. and Toussi, M.S., 2023. Developing surgical skill level classification model using visual metrics and a gradient boosting algorithm. Annals of Surgery Open, 4(2), p.e292.