Teaching Statement of Prof. Lafata

Teaching Philosophy

My philosophy and skillset as a science and technology educator has evolved in a dynamic environment full of exciting opportunities. I have worked on a variety of different projects, which has helped me to become a more well-rounded and versatile academic. For me, teaching is a major career aspiration that is intimately connected to academic research. My teaching philosophy is that research should drive educational lesson plans, and that educational experiences should in turn drive research strategy. Remarkably, some of my best scientific brainstorming sessions started in the classroom with my students, and ultimately turned into novel research insights. While a graduate student, I received formal pedagogical training through the Certificate in College Teaching Program at Duke University. I have been able to integrate many of the pedagogical skills acquired in this program into my teaching responsibilities. As I move forward in my academic career, I am continuously striving to develop and refine my pedagogical practice.

Teaching Experience

I currently teach MedPhys 507 Radiation Biology. In addition to these formal classes, I also teach a yearly workshop on concepts in biomedical image analysis. This 2-week workshop provides an introductory overview of practical techniques (e.g., image processing, computer programming, digital image formats, etc.), as well as current trends in biomedical computer vision applications (e.g., radiomics, deep learning, etc.).

Learning Happens in the Laboratory

It is my belief that one cannot fully disassociate teaching from research. The pedagogical methods that I employ in class have served as an interlocutor between my teaching and my research. As such, I believe that active learning in a laboratory environment is essential to prepare, educate, and mentor the future academics that will one day take our place. 

Student Learning and Assessment

My pedagogical practice focuses on a variety of novel teaching paradigms. For example, I frequently use a technique called Visual Thinking Strategies (VTS) when I am teaching computer vision and image processing concepts. VTS - which has traditionally only been applied to liberal arts education - is widely credited with transforming the way students think and learn about complex issues. The technique is based on Abigail Housen's Theory of Aesthetic Development, and challenges students contextually, metaphorically, and philosophically through the interpretation of art. Due to its basis in visual perception and picture interpretation, I have adapted the VTS paradigm as a teaching tool for concepts in biomedical imaging, computer vision, and image processing. 

In my experience, from a VTS perspective, there is a predictable manner with which students perceive and interpret biomedical imaging data. This is highly consistent with Housen's theory, and provides a reliable formative assessment of student learning. It is fascinating to see students start with a very basic qualitative description of an image, and quickly progress towards complex conversation regarding its mathematical basis. For example, VTS helps students appreciate subtle differences in image texture, anticipate the impulse response of various imaging filters, and speculate the semantic meaning of unsupervised feature extraction. Frequently, students arrive at fundamental questions, including: (a) Do we agree that we're looking at the same phenomena in this image? (b) What is the physical and biological basis responsible for such phenomena? (c) What computer vision techniques could be used to detect and characterize such phenomena?

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