My research focuses on the intersection of Human-Computer Interaction (HCI) and Machine Learning (ML). Specifically, I explore how ML can enhance and create innovative interaction techniques for devices like wearables, smartphones, and tablets. Previously, I developed an interaction technique that uses the back and sides of devices to sense and model users’ grip patterns, improving touchscreen accuracy, user identification, and error detection.
Lately, my interest has shifted towards computer vision, particularly image processing. I am currently collaborating with my PhD student to investigate deep learning techniques for estimating tree species from high-resolution UAV canopy imagery. Additionally, I am working on establishing predictive models of river water quality based on their chemical properties, hydrological factors, and subjective evaluations. My research also includes projects with students on detecting cancerous cells in CT scan images and assessing student attentiveness based on brain wave activity.
Beyond ML and deep learning, I am also involved in various classic HCI areas, such as interactive touch gestures and usability testing.
