Knowledge & Skills

Bayesian Statistics:

Markov Chain Monte Carlo, Gibbs Sampling, Mixture Models, Expectation Maximization, Multivariate Distributions, Hierarchical Models and Latent Variables, Decision Theory, Risk Assessment and Utility functions, Hypothesis Testing, Optimal Design by Simulation, Model Checking, Modeling Sensored and Missing Data, Bayesian Regression Models.

Stochastic Processes Concepts:

Markov Chains, Gaussian Processes, Poisson Processes, Continuous-Time Markov Chains, Random Processes and Linear Systems, Dynamic Programming, Information Theory concepts, Con- strained Optimization, Bayesian Networks, Graphical Models,

Topic Modeling in Text Mining:

Latent Semantics Indexing, Probabilistic Latent Semantics, Latent Dirichlet Allocation, Social Networks, Blog Mining.

Machine Learning:

Classification and Prediction Techniques, Linear and Logistic Regression, Decision Trees, Nayve Bayes, Linear Discriminant Analysis, Support Vector Machines, Boosting, Clustering and Co-clustering using Information Theory, Smart Alerts.

Image Analysis and Computer Vision:

Autoregressive Models, Signal Processing and Acquisition,Binary Images, Filtering, Color Representation, Noise Estimation and Removal from a Single Image. Domain in the analysis of Coronary Tissue Classification from Intravascular Ultrasound (IVUS) Images, and their acquisition and reconstruction from RF signals.

Skills

R, Matlab and different toolboxes, Perl, ANSI C, C++, XLMiner, Weka, Lucene, Lemur, OpenCV, PHP, SQL, HTML, XML