Dr. A. (Reza) Mohammadi PhD
- Plantage Muidergracht 12
- Room number:M 1.24
- Postbus 15953
1001 NL Amsterdam
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Profile
Research interests
My research interests lie primarily in developing statistical methods to analyse high-dimensional data which routinely arise in econometrics, machine learning, neuroscience, and social science. I began my research career by developing Bayesian statistical methods for mixture distributions with application in queuing systems. My current research is focused on developing Bayesian statistical methods in constructing networks for multivariate statistical analysis to understanding the underlying mechanisms in complex systems. These methods have applications in a wide variety of disciplines, such as capturing causal relationships between brain activities for treatment of psychiatric disorders. My motivation to develop these methods is to encode the relationships between the components in high-dimensional scale.
Short Bio
I am currently Assistant Professor of Statistic at the University of Amsterdam, Operations Management section.
During 2016-2017, I worked as a postdoctoral researcher as a statistician at the Department of Methodology and Statistics at the Tilburg University and Jheronimus Academy of Data Science (JADS).
In 2015, I received my PhD in Probability and Statistics from the University of Groningen, thesis entitled "Bayesian Model Determination in Complex Systems", supervised by Prof. Ernst Wit.
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Software
I am a core developer of the following open source software which are used in my publications:
- R package BDgraph: Bayesian Structure Learning in Graphical Models using Brith-Death MCMC
- R package bmixture: Bayesian Estimation for Finite Mixture of Distributions
- R package ssgraph: Bayesian Graphical Estimation using Spike-and-Slab Priors
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Publications
2019
Mohammadi, R., & Wit, E. C. (2019). BDgraph: An R Package for Bayesian Structure Learning in Graphical Models. Journal of Statistical Software, 89(3). https://doi.org/10.18637/jss.v089.i03 [details]
2018
- Dobra, A., & Mohammadi, A. (2018). Loglinear model selection and human mobility. Annals of Applied Statistics, 12(2), 815-845. https://doi.org/10.1214/18-AOAS1164 [details]
- Dyrba, M., Grothe, M. J., Mohammadi, A., Binder, H., Kirste, T., & Teipel, S. J. (2018). Comparison of Different Hypotheses Regarding the Spread of Alzheimer’s Disease Using Markov Random Fields and Multimodal Imaging. Journal of Alzheimer's Disease, 65(3), 731-746. https://doi.org/10.3233/JAD-161197 [details]
2017
- Mohammadi, A., Abegaz, F., van den Heuvel, E., & Wit, E. C. (2017). Bayesian modelling of Dupuytren disease by using Gaussian copula graphical models. Journal of the Royal Statistical Society. Series C: Applied Statistics, 66(3), 629-645. https://doi.org/10.1111/rssc.12171
2016
- Mohammadi, A., & Kaptein, M. (2016). Contributed discussion on article by Pratola [Comment on "M.T. Pratola, Efficient metropolis-hastings proposal mechanisms for Bayesian regression tree models"]. Bayesian Analysis, 11(3), 938-940. https://doi.org/10.1214/16-BA999H
2015
- Mohammadi, A., & Wit, E. C. (2015). Bayesian structure learning in sparse Gaussian graphical models. Bayesian Analysis, 10(1), 109-138. https://doi.org/10.1214/14-BA889
2014
- Mohammadi, A., & Wit, E. C. (2014). Contributed discussion on article by Finegold and Drton: Comment by Abdolreza Mohammadi and Ernst C. Wit. Bayesian Analysis, 9(3), 577-579. https://doi.org/10.1214/13-BA856D
2013
- Mohammadi, A., Salehi-Rad, M. R., & Wit, E. C. (2013). Using mixture of Gamma distributions for Bayesian analysis in an M/G/1 queue with optional second service. Computational Statistics, 28(2), 683-700. https://doi.org/10.1007/s00180-012-0323-3
2012
- Mohammadi, A., & Salehi-Rad, M. R. (2012). Bayesian inference and prediction in an M/G/1 with optional second service. Communications in Statistics: Simulation and Computation, 41(3), 419-435. https://doi.org/10.1080/03610918.2011.588358
Award
- Mohammadi, R. (2018). Travel Grant for COSTNET Sandpit Meeting at Oxford.
- Mohammadi, R. (2018). Short Term Scientific Misson Grant.
- Mohammadi, R. (2017). Travel Grant for COSTNET17 Conference.
Talk / presentation
- Mohammadi, R. (speaker) (10-2017). Bayesian Structure Learning of High-dimensional Graphical Models with Application to Brain Connectivity, COSTNET17, Mallorca.
- Mohammadi, R. (speaker) (22-8-2016). Bayesian Modelling of Dupuytren Disease Using Gaussian Copula Graphical Models, Network Science and its Applications, Cambridge.
- Mohammadi, R. (speaker) (8-8-2015). Bayesian Structure Learning in Graphical Models, Joint Statistical Meetings, Seattle.
- Mohammadi, R. (speaker) (7-2015). Bayesian Structure Learning in Sparse Graphical Models, European Meeting of Statisticians, amsterdam.
- Mohammadi, R. (speaker) (7-2014). Bayesian Copula Gaussian Graphical Modelling, 29th International Workshop on Statistical Modelling, Gottingen.
- Mohammadi, R. (speaker) (3-2013). Gaussian graphical model determination based on birth-death MCMC inference, STAR meeting day, Leiden.
- Mohammadi, R. (speaker) (3-2013). Gene Network inference for high-dimensional problems, Gene Network Inference Meeting 2013, Paris.
- Mohammadi, R. (speaker) (12-2011). Using mixture of Gammas for Bayesian analysis in an M/G/1 queue with optional second service, 4th International Conference of the ERCIM WG on COMPUTING & STATISTICS, Londen.
- Mohammadi, R. (speaker) (8-2010). On Bayesian estimation for the M/G/1 queue with optional second service, International Conference of Mathematical Sciences, Istanbul.
Others
- Mohammadi, R. (participant) (2-7-2017 - 7-7-2017). International Workshop on Statistical Modelling 2017, Groningen. I was a local organizer of the International Workshop on Statistical Modelling 2017 (organising a conference, workshop, ...).
2015
- Mohammadi, A. (2015). Bayesian Model Determination in Complex Systems.
2017
- Dobra, A., & Mohammadi, A. (2017). Loglinear model selection and human mobility. Ithaca, NY: arXiv.org. [details]
- Mohammadi, A., & Wit, E. C. (2017). BDgraph: An R Package for Bayesian Structure Learning in Graphical Models. Amsterdam: University of Amsterdam. [details]
- Mohammadi, A., Massam, H., & Letac, G. (2017). The ratio of normalizing constants for Bayesian graphical Gaussian model selection. (ArXiv e-prints). https://arxiv.org/abs/1706.04416
This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list. -
Ancillary activities
- No ancillary activities
Mohammadi, R., & Wit, E. C. (2019). BDgraph: An R Package for Bayesian Structure Learning in Graphical Models. Journal of Statistical Software, 89(3).