Research Interests My research is in machine learning/data mining and natural language processing with an emphasis on applications in health informatics. I am particularly interested in using machine learning to mine, organize and filter clinical/biomedical texts, especially in the context of evidence-based medicine. There are too few experts to make sense of the torrents of published clinical data. I am interested in mitigating this problem by developing novel learning algorithms to induce models that semi-automate the clinical evidence synthesis process, thereby reducing workload. More broadly, I am interested in core machine learning issues: e.g., structured and unstructured classification techniques; semisupervised learning methods; learning with imbalanced data; and learning from alternative forms of supervision. I am also broadly interested in computational methods for evidence-synthesis.