This is a repost of an article written by Kimberly Xiao on the Stony Brook University Department of Computer Science website

Pictured: Haibin Ling, IEEE Fellow and CS Professor

Haibin Ling was recently named a 2023 Institute of Electrical and Electronics Engineers (IEEE) Fellow for his contributions to computer vision in the areas of visual tracking and matching.

When a patient is diagnosed with cancer, a period of fear and confusion inevitably follows. The patient and their doctor may share similar questions: What are the next steps? Which treatment should be pursued? What does the future hold? 

With the use of deep learning, artificial intelligence can help address these difficult questions for doctors and patients, and may ultimately help determine a course of action and treatment options, according to the recent study, “Survival Analysis of Localized Prostate Cancer with Deep Learning.” 

You are driving a car down a city street, when you see a child playing with a ball by the side of the road. When the ball suddenly shoots across the road, you slam on the brakes—anticipating that the child may run out in the street chasing the ball.

Action anticipation, the task of predicting the next action in a sequence, is an important problem in computer vision. For instance, accurately predicting the actions of other cars in a driving sequence is essential to building safe self-driving vehicles. Typically, video frames are used to train AI systems for action anticipation, but language models are another type of data that can be helpful here. 

Part eight of our AI Researcher Profile Series invites Professor Klaus Mueller of the Department of Computer Science to discuss his extensive work with Artificial Intelligence, and how he uses it to produce a human-machine relationship that enables the machine, but empowers the human. 

AI Institute: What sparked your interest in Artificial Intelligence?