Ming Zhang
Prof. Ming Zhang Excites Students About Potential for Computer Vision
Ming Zhang
Assistant Professor, Computer Science
PhD, Utah State University; BS, Shandong University, China
What is your area of expertise?
I focus on computer vision, machine learning, and artificial intelligence.
Please tell us about your work. Can you share any current research or recent publications?
I have created an Artificial Intelligence and Computer Vision (AICV) group to enrich students’ research activities and help them succeed in their future careers. Currently, I lead a group of 12 students on multiple computer vision and machine learning projects from Tufts Medical Center that contributes to osteoarthritis research.
I have received grants from the National Science Foundation (NSF), the National Institutes of Health (NIH), the Food and Drug Administration (FDA), and the Rheumatology Research Foundation (RRF) to provide computer vision and machine learning solutions to medical image problems. I have published 80 peer-reviewed articles in various professional journals and conference reports.
How does the subject you work in apply in practice? What is its application?
Images are an important data source for understanding the world. Eighty percent of the information we need to assess the world comes through the eye. Computer vision is widely used in agriculture, manufacturing, accounting, insurance, homeland security, social media, healthcare, etc. Computer vision is a very popular and rapidly growing area in computer science and engineering. It is also an essential component of artificial intelligence (AI). To date, 49 percent of AI patents are in the computer vision area. Big companies such as Apple, Meta (formerly Facebook), Google, Netflix, Nvidia, and Tesla need people with computer vision skillsets.
What course(s) do you teach at MET?
I teach Analysis of Algorithms (MET CS 566). In the future, I may create a new course about image processing based on my experience. It will provide students with hands-on experience in solving real-world problems such as face recognition, car and sign detection in self-driving, and computer-aided diagnosis of medical images.
Please highlight a particular project within this course(s) that most interests your students. If you previously worked in industry, what “real-life” exercises do you bring to class?
One student project is to count the available spots in university parking lots using surveillance cameras. The program they’ve developed can help faculty and students easily identify a parking space before arriving at the parking lot.