The Machine Learning Group at Tufts University focuses on core issues of machine learning, as well as real-world applications of machine learning.
Please visit our research pages to find out more.
Recent core issues investigated include:
- Class label noise
- Active learning
- Time series anomaly detection
- Information retrieval
- Learning from relational data
- Learning and planning in markov decision proceses
- Kernel methods
- Calibrating classifiers' predictions
Recent applications (and collaborators) include:
- Generating maps of global land cover (Geography Department, Boston University)
- Anomalies and classification of light curves (Center for Astrophysics, Harvard University)
- Liquification prediction (Civil Engineering, Tufts University)
- Diagnosis of disease state via saliva (Chemistry Department, Tufts University, Boston University Dental and Medical Schools and many others)
- Vapor sensing ( Chemistry Department, Tufts University)
- Medical abstract screening (Sackler School of Medicine, Tufts University)
