Ph.D. student in Biomedical Engineering specializing in computational biomedicine, biomarker discovery, and cancer informatics. Focused on translating multimodal data into actionable clinical insights. Experienced in automated whole slide image analysis, machine/deep learning, and computer vision for computational pathology (Roche), as well as neurophysiological signal processing for chronic pain neural biomarker discovery (Telkes Lab and Medtronic). Proven track record of leading clinical engineering teams and collaborating with the World Health Organization during the COVID-19 pandemic; professional working proficiency in English, Turkish, Azerbaijani, and Persian.
Ph.D., Biomedical Engineering, The University of Arizona, Tucson, AZ, USA | 2024 – Present
M.Sc., Biomedical Engineering, Seraj University, Tabriz, East Azerbaijan, Iran | 2020 – 2022
B.Sc., Biomedical Engineering, Islamic Azad University, Tabriz, East Azerbaijan, Iran | 2010 – 2014
Graduate Research Assistant: Telkes Lab, BME & Neurosurgery Department, University of Arizona, Tucson, USA | 2025 – Present
Computational Pathology Intern: Pathology Lab Research & Early Development, Roche, Tucson, USA | Summer 2026
Project [PL-RED]: HemQ: Automated Cellular Quantification Tool for Dialable LOTUS Hematoxylin
To support the Roche agile team’s development of a customizable Hematoxylin counterstain reagent for the LOTUS platform, I engineered the core computational pipeline for automated tissue segmentation, stain unmixing, and the extraction of nuclear and non-nuclear features to drive pathologist-aligned scoring and reduce diagnostic variability. Building upon this automated quantification tool designed to optimize laboratory efficiency and lower operational costs, I further integrated CPU-bound performance enhancements—including parallel computing, partial patch processing, and coarse-to-fine analysis—to ensure efficient, high-throughput segmentation across standard laboratory workstations without requiring dedicated GPU infrastructure.
Graduate Research Assistant: VSI Lab, ECE Department, University of Arizona, Tucson, USA | 2024 – 2025
My role involved designing and implementing deep learning pipelines for medical object detection and multimodal sensor fusion, incorporating triple adaptive mechanisms and a self-supervised pretraining framework that leverages contrastive learning, adaptive layer weighting, and token-level attention initialized in Python (TensorFlow & Keras) workflows.
Supervisor, Clinical Engineer: Tabriz University of Medical Sciences, East Azerbaijan, Tabriz, Iran | 2014 – 2024
My role involved implementing machine learning frameworks incorporating feature extraction and ensemble methods for multimodal clinical data analysis, while leading clinical engineering teams in overseeing capital and disposable medical device management, operational training, preventive maintenance, statistical analysis, clinical readiness, and collaboration with the WHO on COVID-19 response to ensure safe, efficient, and effective healthcare operations.
Department Assistant: Dean's Office, BME Department, University of Arizona, Tucson, USA | Summer 2025
My role involved managing alumni records, supporting student orientation events, and guiding program resources, research opportunities, and departmental activities.
Project Assistant: Iran COVID-19 Emergency Response Project, World Health Organization | 2020 – 2021
My role involved managing medical equipment across hospitals and analyzing electronic health records to inform data-driven decisions and optimize patient care during the pandemic.
Undergraduate Teaching Assistant: East Azerbaijan, Tabriz, Iran
- [BME 090] Introduction to Clinical Engineering, Tabriz University – Dr. Sebelan Danishvar | 2016 – 2017
- [BME 020] Equipment of Hospitals & Medical Centers, Islamic Azad University of Tabriz – Dr. Hashemiaghdam | 2013 – 2014
- [BME 006-8] Computer Programming & Algorithm Calculus, Islamic Azad University of Tabriz – Dr. Rajabioun | 2012 – 2013
- Sakthivel, S., Saraei, M., Sadek, H., & Telkes, I. (2026). Examining Electrocardiogram Morphology and Heart Rate Variability During Spinal Cord Stimulation for Chronic Pain. Stanford Cardiovascular Institute Research Symposium, California, USA.
- Saraei, M., & Telkes, I. (2026). Preliminary EEG Connectivity Signatures of Long-Term Spinal Cord Stimulation in Chronic Pain. NYC Neuromodulation Conference (Neuromodec), New York, NY, USA. 🔗 Link
- Saraei, M., Pousseu, L., DiMarzio, M., Pilitsis, J. G., & Telkes, I. (2026). Altered Alpha–Theta Network Connectivity During Spinal Cord Stimulation in Chronic Pain. 17th World Congress of the International Neuromodulation Society (INS), Lisbon, Portugal.
- Saraei, M., Lee, E.J., & Lalinia, M. (2025). Deep Learning-Based Medical Object Detection: A Survey. IEEE Access (EMBS), 13, 53019–53038. 🔗 DOI
- Saraei, M., & Liu, S. (2023). Attention-Based Deep Learning Approaches in Brain Tumor Image Analysis: A Mini Review. Front. Health Inform., 12, 164. 🔗 DOI
- Saraei, M., Rahmani, S., Rajebi, S., & Danishvar, S. (2023). A Different Traditional Approach for Automatic Comparative Machine Learning in Multimodal COVID-19 Severity Recognition<. Int. J. Innov. Eng., 3(1), 1–12. 🔗 DOI
Peer-Reviewer:
- IEEE Access, New York, NY, USA | 2025 – Present
- CaPTion @ MICCAI, Strasboug, France | 2026
- MIUA, Dublin, Ireland | 2026
[Research Assistantship]: Supported by the Telkes Lab, University of Arizona ($71,158) | 2025 - Present
[Herbold Fellowship]: Awarded by the College of Engineering, University of Arizona ($58,470) | 2024 - 2025
© 2024-2026 Reza · All rights reserved!
📧 mrsaraei@arizona.edu | mrsaraei@yahoo.com