The goal of my teaching is to ensure that students can skillfully research topics on the subject matter, critically think through answering questions, and apply their new-found knowledge to real-life applications. It is my hope that the learning experience from my teaching plants seeds of long-lasting influence in their professional and personal development.
BMED 431/531 Computational Engineering II
This course focuses on utilizing computational methods to solve engineering problems, which often can’t be solved analytically. The goal of this course is to provide students a comprehensive understanding of a variety of computational methods and algorithms. Those methods will be introduced in the context of engineering examples, and implemented in MATLAB. Advanced MATLAB programming techniques will be introduced to solve complex engineering problems. Topics of this course includes: roots and optimization, curve fitting, integration, and differentiation. Advanced topics will also be introduced. Monte Carlo simulation will be discussed in the context of light/tissue interaction and finite difference analysis will be used to assess photothermal damage.
BMED 444/544 Introduction to Biomedical Imaging
This course provides a comprehensive introduction to modern biomedical imaging modalities that are currently employed in both biomedical research and clinical medicine. This course is organized into 5 imaging modules: (1) Optical imaging and microscopy; (2) Radiographic imaging (X-ray and CT); (3) Nuclear medicine imaging (SPECT and PET); (4) Ultrasound imaging; and (5) Magnetic resonance imaging (MRI). The main objective is to offer students a solid overall understanding of each imaging modality and their biomedical applications through lectures, assignments and project. For each imaging modality, we will focus on basic physics, image formation and reconstruction, imaging hardware, and clinical and research applications. Besides imaging modules, this course will also (briefly) cover two additional topics: 1) Research proposal writing; and 2) Image and signal processing. Additional topics prepares students with skills to propose and solve real-world biomedical challenges.
BMED 456/556 Digital Image Processing Using MATLAB
Digital image processing is an indispensable component in biomedical research and imaging. The goal of this course is to provide students a solid understanding of a variety of image processing techniques and their implementations with a focus on biomedical applications. Image processing methods will be introduced primarily using MATLAB. Other image processing software, such as ImageJ and GIMP, will also be briefly introduced. Knowing multiple image processing platforms offers students the freedom to choose the most appropriate one to tackle specific image processing tasks. Topics of this course include: image filtering in spatial- and frequency-domain, image restoration and reconstruction, image transformation and registration, color image processing, and morphological image processing. Advanced image processing techniques will also be introduced
BMED 510 Modern Methods in Biomedical Engineering
This introductory graduate course offers students a broad knowledge of modern methods and engineering tools used in biomedical engineering. Topics include MATLAB programming, 3D modeling/printing using Fusion 360, soft tissue characterization, optical sensing/imaging, FDA guidelines for medical device development/verification. This course features hands-on learning experience. Students will complete a group project after each module. In addition to projects, students will have opportunities to do experiments related to specific topics, such as tissue testing and optical imaging.