Pantea Tavakolian
- Assistant Professor, Biomedical Engineering
Contact Info
- Email: pantea.tavakolian@UND.edu
- Office: 701.777.4429
Office Address
Columbia Hall Room 2370R
501 N Columbia Road Stop 8155
Grand Forks, ND 58202-8155
Websites
Biography
Pantea Tavakolian, Ph.D. is a biomedical engineering scientist whose work focuses on developing and translating multimodal imaging systems for early disease detection and tissue health assessment. Her expertise spans photoacoustic and thermal imaging, biophotonics, medical device prototyping, and advanced data analysis, including image/signal processing and machine learning.
1. BME 280. Skeletal Muscle: Biomedical Engineering Innovation-Based Learning III. 2 Credits.
The third course in the BME innovation-based learning series. This course is designed to develop the student in; 1) the practice of medical device and process innovation, 2) the engineering perspective of physiological concepts, 3) professionalism, and 4) ethical and regulatory issues. Prerequisite: BME 181 with a C or higher. Prerequisite or Corequisite: MATH 166. F.
2. BME 281 Biomechanics
3. BME 444/644: Advanced Imaging Systems in Biomedicine. 3 Credits.
This course will cover the advanced topics on imaging systems in biomedicine, focusing on both foundational and emerging modalities. It is designed for students majoring in Biomedical Engineering, Electrical Engineering, and other engineering disciplines who are interested in learning about the principles, techniques, and applications of medical imaging. In this course, we will explore the fundamental concepts of medical imaging, including X-ray, MRI, ultrasound, spectroscopy, and optical imaging. Special emphasis will be placed on emerging optical imaging techniques, such as optical coherence tomography and hyperspectral imaging, and their applications in clinical and research settings. We will cover various imaging modalities, discussing the principles behind each, their advantages, and their limitations. Topics will include image quality, resolution, contrast, and the impact of tissue scattering and absorption. By the end of the course, students will have gained a comprehensive understanding of the principles of medical imaging across different modalities. They will also have practical experience with imaging equipment and techniques, as well as an appreciation of the ethical and societal implications of medical imaging. Prerequisite: MATH 266 and BME 180. On demand.
4. BME 690 BioPhotonics 1
Biophotonics, Spectroscopy, thermal imaging, medical imaging, image and signal processing, and Machine Learning (ML)
Ph.D. University of Toronto (2019)
M.Sc. University of Western Ontario (2014)