Dr. Beniamino Hadj-Amar


I am a Postdoctoral Fellow in  the Department of Statistics at Rice University (Houston, TX), working with Marina Vannucci in a collaborative effort with Read Montague's lab at Virginia Tech.

My research area is at the interface between statistics and science, where I am particularly interested in the development of Bayesian methodologies for the automated analysis of complex dynamical time series. I have obtained my Ph.D. in the Oxford-Warwick Statistics Programme (OxWaSP), working under the supervision of Bärbel Finkenstädt (University of Warwick, UK). 


Research Interests:

To identify latent structures, deal with complex streams of temporal data, as well as properly account for model uncertainty,  I often need to design highly flexible and interpretable models characterized by non-stationary behavior, non-linear features, and sparse structures. From a methodological perspective, I have experience working on switching models (e.g.hidden Markov and semi-Markov models), change-point models,  Gaussian processes, Bayesian nonparametrics,  graphical models, Bayesian variable selection, factor models, mixture models, statistical spectral analysis, and Markov chain Monte Carlo.   Throughout my academic experience, I have been working on addressing scientific problems in several fields, such as neuroscience (neuromodulation alongside electrophysiological and electrochemical data derived from the conscious human brain, as well as fMRI data), respiratory research (airflow trace data), and circadian studies (datasets obtained from wearable devices).

Publications:


* : joint first author 

Software: