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I'm interested in the following research areas:
Bayesian Inference and Markov Chain Monte Carlo methods
Semi-supervised Learning
Applications of Machine Learning to: 1) Computational Molecular Biology 2) Computer Vision
And unexplored/latent interests in Computational Neuroscience, Probabilistic Relational models, Information Geometry and Bayesian Inference, and possibly other interesting problems too...
Current research projects:
1. I'm working with Professor Radford Neal on a Bayesian approach to Semi-Supervised Learning for discriminative models using Markov Chain Monte Carlo methods.
2. I'm working with Professor Quaid Morris on fast transductive learning algorithms and heuristics for combining multiple sources of information in molecular biology for gene function prediction.
Past projects:
I worked with Xuming He and Professor Richard Zemel on using a Mixture of Conditional Random Fields model for combining contextual and top-down cues for image labeling and segmentation.
Related paper: "Learning and Incorporating Top-Down Cues in Image Segmentation", Xuming He, Richard Zemel and Debajyoti Ray. To be presented at European Conference in Computer Vision, 2006.