معرفی
Xiaodong Cai is a Professor in the Department of Electrical & Computer Engineering at the University of Miami College of Engineering. His research bridges machine learning, bioinformatics, and computational biology to address complex problems in cancer prognosis and medical imaging.
- University: University of Miami
- School: College of Engineering
- Department: Electrical & Computer Engineering
- Email: x.cai@miami.edu
Research Interests:
Dr. Cai focuses on applying advanced machine learning techniques to biomedical data. His work includes developing contrastive learning models for cancer prognosis, inferring differential gene regulatory networks, and analyzing optical coherence tomography (OCTA) images to detect diseases like diabetic retinopathy and multiple sclerosis. His methodologies leverage high-dimensional data analysis and optimization algorithms to improve diagnostic accuracy and network inference.
Scientific Awards:
- IEEE Access Outstanding Paper Award (2021)
- Miller School of Medicine Research Excellence Award (2020)
Publication Trends:
Dr. Cai’s recent publications emphasize machine learning applications in healthcare. His work on contrastive learning for cancer prognosis demonstrates improved classification accuracy using TCGA data, while his gene network inference algorithms reveal condition-specific regulatory changes in cancer and normal tissues. Medical imaging studies highlight wavelet-based feature extraction for early disease detection, particularly in diabetes and multiple sclerosis.
