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Biography
Background and Expertise:
- Ph.D. in Data Science
- Machine learning, deep learning, graph neural networks, mRNA-seq analysis
Research Interests:
- Machine learning and deep learning applications in pharmacology, genomics, multiomics, and metabolomics.
- Developing models to study drug interactions, uncover disease mechanisms, and identify biomarkers for personalized medicine
Dr. Maria Vaida is an Assistant Professor of Data Science whose research focuses on using computational tools to address challenges in biology and medicine. She specializes in graph neural networks, differential gene expression analysis, and applying machine learning to cancer research. Her work includes developing models to study drug interactions, uncover disease mechanisms, and identify biomarkers for personalized medicine.
