معرفی
Xiaojun Li is a Professor affiliated with the Department of Mechanical Engineering at the University of Maryland, with additional research ties to Texas A&M University and institutions in China. His work spans interdisciplinary fields including machine learning, computer vision, and engineering systems. He has contributed to over 130 publications since 1985, focusing on topics like deep learning applications in healthcare, seismic modeling, and intelligent systems for infrastructure. His research emphasizes practical solutions in domains such as medical diagnostics, tunnel construction optimization, and energy forecasting.
Key contributions include the development of JaunENet for jaundice detection, advanced seismic wave modeling techniques, and intelligent systems for automated tunnel construction. He collaborates extensively with experts in data science, environmental engineering, and computer science. His work bridges theoretical advancements with real-world applications, addressing challenges in healthcare technology, sustainable infrastructure, and energy management.
Recent projects highlight innovation in multimodal hate speech detection, smart evacuation systems using VR, and the application of graph-based methods for EEG emotion recognition. His research often integrates big data analytics and AI-driven approaches to solve complex problems in both technical and societal contexts.
