Sepideh Azarianpour

Applied AI researcher with a Ph.D. in Biomedical Engineering and 7+ years of experience developing machine learning models for real-world healthcare data. Expertise in deep learning, multimodal data integration, and large-scale clinical datasets, with a focus on model development, evaluation, and deployment. Experienced in collaborating with clinicians and stakeholders to translate complex healthcare problems into scalable AI solutions that improve patient outcomes and operational efficiency.

Postdoctoral Scholar / Clinical Imaging AI Researcher at Case Western Reserve University (2024-06 – Present)

Department of Biomedical Engineering

• Developed machine learning models for large-scale healthcare imaging datasets, focusing on cardiovascular risk prediction.
• Designed end-to-end pipelines for multimodal data integration, including imaging and clinical variables.
• Built and trained deep learning models (CNNs and transformer-based architectures) for structured and unstructured medical data.
• Evaluated model performance using statistical analysis, survival modeling, and cross-validation techniques.
• Collaborated with clinicians to translate real-world clinical problems into data-driven AI solutions.
• Investigated model robustness across heterogeneous datasets and identified sources of performance variability.
• Presented results through publications, reports, and cross-functional discussions with clinical and technical teams.
• Explored applications of deep learning and emerging foundation models for complex healthcare data analysis.

Algorithm Development Intern at MIM Software Inc. (2022-08 – 2022-11)

• Developed deep learning models for medical image segmentation and refinement within clinical imaging workflows.
• Evaluated model outputs against clinical annotations and analyzed performance improvements.
• Collaborated with engineering teams to improve model usability within software systems.

Graduate Researcher at Case Western Reserve University (2018-09 – 2024-02)

Department of Biomedical Engineering

• Developed machine learning models for high-dimensional biomedical datasets, including imaging and spatial data.
• Designed feature extraction and representation learning approaches for complex biological structures.
• Built predictive models using supervised and unsupervised learning techniques.
• Evaluated model performance through statistical validation and outcome-based analysis.
• Integrated multimodal data sources to improve predictive performance and model interpretability.
• Collaborated with interdisciplinary teams to translate research into clinically relevant insights.

PhD in Biomedical Engineering – Case Western Reserve University (2018-09 – 2024-02)