Siyuan Chen
- Ph.D. Student, Computer Science
Biography
Siyuan Chen is a Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), supervised by Prof. Xin Gao and Prof. Yu Li. His research lies at the intersection of artificial intelligence, computational biology, and healthcare, with a focus on developing deep learning methods for genomics, biomedical imaging analysis, and omics-based disease detection and diagnostics. His work has been published in journals including Science Advances, Genome Research, Nature Communications, Bioinformatics, Briefings in Bioinformatics, and IEEE Journal of Biomedical and Health Informatics. His academic service includes reviewing for Bioinformatics, Briefings in Bioinformatics, BMC Bioinformatics, and MICCAI.
Expertise and Interests
Siyuan’s research interests center on developing AI methods to address challenges in biology and healthcare. His expertise spans genomic data analysis, biomedical applications of large language models, biomedical image analysis, and omics-based disease detection. His work emphasizes enhancing model reasoning, evaluating AI safety, automating multi-omics analysis, and enabling multimodal interactions to support personalized healthcare.
Education
- Bachelor of Engineering (B.Eng.)
- Electrical and Computer Engineering, University of Electronic Science and Technology of China, China, 2020
- Master of Science (M.S.)
- Computer Science, King Abdullah University of Science and Technology, Saudi Arabia, 2021
