Dr. Marco Andreas Grzegorczyk

**room number:**

449 (Bernoulliborg, building 5161)**Address:**

Nijenborgh 9

9747 AG Groningen

Netherlands**phone numbers:**

domestic: 050 363 3985

international: +31 50 363 3985

fax: 050 363 3800**e-mail:**m.a.grzegorczyk@rug.nl

## Curriculum Vitae

**Since 04/2019**Associate Professor for Computational Statistics, research unit: 'Statistics and Probability', Bernoulli Institute (BI), Groningen University, Netherlands.**12/2013 - 03/2019**Assistant Professor, research unit: 'Statistics and Probability', Bernoulli Institute (BI), Groningen University, Netherlands.**10/2011 - 11/2013**Personal Research Grant, funded by the German Research Foundation (DFG), project title: "Development of new Bayesian network models for systems biology research" (GR3853/1-1), Department of Statistics, TU Dortmund University.**04/2011 - 09/2011**Interim guest lectureship for Applied Statistics, Department of Mathematics, Carl von Ossietzky University Oldenburg.**01/2011 - 03/2011**Post-doctoral research fellow, Department of Statistics, TU Dortmund University.**01/2009 - 12/2010**Post-doctoral research fellow in the Graduate School 'Statistical Modelling', Department of Statistics, TU Dortmund University.**07/2007 - 12/2008**Post-doctoral research fellow at the Centre for Systems Biology at Edinburgh, School of Biological Sciences, Edinburgh University, UK and Associate at Biomathematics and Statistics Scotland (BioSS), Edinburgh, Scotland, UK (7/2007-12/2011).**07/2003 - 06/2007**Research Fellow (PhD student and later post-doctoral fellow) in the research project 'Chemical Biology and Biotechnology' at the Department of Statistics, Dortmund University.

## Research Interests

- Bayesian networks and other graphical models for extracting gene-regulatory networks and protein pathways in systems biology research.

## PhD students:

- Victor Bernal (DSSC project, co-supervised since July 2016)
- Spyros Balafas (co-supervised since April 2017)
- Luca del Core (supervised since September 2018)
- Abdul Salam (supervised since November 2018)
- Azza Ahmed (double PhD candidate Groningen/Khartoum University)

## Former PhD students:

- Dr. Mahdi Shafiee Kamalabad (01/2015-12/2018)

## Visiting PhD students:

- Ahmad Ahmadi Yazdi (Isfahan University of Technology, 06/2018-10/2018)
- Zulfiqar Ali (Quaid-i-Azam University, 10/2018-03/2019)

## Statistical Modelling Society (SMS)

- I am member of the Excecutive Committee and Treasurer of the Statistical Modelling Society (since January 2019) Webpage
- I was chair of the 32nd International Workshop on Statistical Modelling (3-7 July 2017, Groningen, Netherlands) Webpage

## Associate Editorships

- I am Associate Editor of
**Computational Statistics**Webpage - I am Associate Editor of the
**Journal of Applied Statistics**Webpage

## Other involvements:

- I participated in COST Action CA15109 (European Cooperation for Statistics of Network Data Science (COSTNET)) Webpage
- I am member of DSSC (Data Science & System Complexity), Groningen University Webpage
- I was awarded the 'Basis Kwalificatie Onderwijs' (University Teaching Qualification), 2017, Groningen University.
- I was awarded a Fellowship 'Innovation of Teaching' (FIT), 2017, Groningen University.Webpage
- I am member of the Representative Council (Dutch region) of the International Biometrical Society (IBS) Webpage
- I was guest editor of a special issue on Statistical Modelling of Statistica Neerlandica Webpage Editorial

## Former Grants,

Research grant: "Development of new Bayesian network models for systems biology research" funded by German Research Foundation (DFG), 2011-2014 Webpage

## Former Webpage at TU Dortmund University

## Theses

**Habilitation**(Venia Legendi for Statistics), Department of Statistics, TU Dortmund University, Title of thesis: "Bayesian Networks for Reconstructing Gene Regulatory Networks in Systems Biology"**(6/2012)**. Download PDF**Promotion (Dr. rer. nat.)**, Department of Statistics, Dortmund University, Title of doctoral thesis: "Comparative evaluation of different Graphical Models for the Analysis of Gene Expression Data."**(8/2006)**. Download PDF**Diplom in Statistics with special focus on Biometrics**("Studienschwerpunkt: Biometrie"), Department of Statistics, Dortmund University, Title of Diplom thesis: "Auswertung einer Brustkrebsstudie mit logistischen Regressionsmodellen"**(2/2003)**. Download PDF

## Publications

- Bernal, V., Bischoff, R., Horvatovich, P., Guryev, V. and
**Grzegorczyk, M.**(2021): The `Un-Shrunk' Partial Correlation in Gaussian Graphical Models.**BMC Bioinformatics**, 22, article number 424. Available here - Shafiee Kamalabad, M. and
**Grzegorczyk, M.**(2021): A new Bayesian piecewise linear regression model for dynamic network reconstruction.**BMC Bioinformatics**, 22 (Supplement 2), article number 196. Available here - Shafiee Kamalabad, M. and
**Grzegorczyk, M.**(2020): Non-homogeneous dynamic Bayesian networks with edge-wise sequentially coupled parameters.**Bioinformatics**, 36 (4), 1198-1207. Available here - Bernal, V., Bischoff, R., Guryev, V.,
**Grzegorczyk, M.**and Horvatovich, P. (2019): Exact hypothesis testing for shrinkage based Gaussian Graphical Models.**Bioinformatics**, 35 (23), 5011–5017. Available here - Imkamp, K., Bernal, V.,
**Grzegorczyk, M.**, Horvatovich, P., Vermeulen, C.J., Heijink, I.H., Guryev, V., Kerstjens, H.A.M., van den Berge, M. and Faiz, A. (2019): Gene network approach reveals co-expression patterns in nasal and bronchial epithelium.**Scientific Reports**, 9, article number: 15835. Available here - Kaufmann, T., Castela Forte, J., Hiemstra, B., Wiering, M.A.,
**Grzegorczyk, M.**, Epema, A.H. and van den Horst, I.C.C. (2019): A Bayesian network analysis of the diagnostic process and its accuracy to determine how clinicians estimate cardiac function in critically ill patients: Prospective observational cohort study.**JMIR Medical Informatics**, 7(4), online article. Available here - Ahmadi Yazdi, A., Zeinal Hamadani, A., Amiri, A. and
**Grzegorczyk, M.**(2019): A New Bayesian Multivariate Exponentially Weighted Moving Average Control Chart for Phase II Monitoring of Multivariate Multiple Linear Profiles.**Quality and Reliability Engineering International**, 35 (7), 2152-2177. Webpage - Shafiee Kamalabad, M., Heberle, A.M., Thedieck, K. and
**Grzegorczyk, M.**(2019): Partially non-homogeneous dynamic Bayesian networks based on Bayesian regression models with partitioned design matrices.**Bioinformatics**, 35 (12), 2108–2117. Available here **Grzegorczyk, M.**and Husmeier, D. (2019): Chapter 32: Modelling Non-homogeneous Dynamic Bayesian Networks with Piecewise Linear Regression Models. In: Balding, D.J., Moltke, I., Marioni J. (editors),**Handbook of Statistical Genetics**, 4th edition, volume2, pages 899-931, John Wiley & Sons. Webpage**Grzegorczyk, M.**, Aderhold, A. and Husmeier, D. (2019): Overview and Evaluation of Recent Methods for Statistical Inference of Gene Regulatory Networks from Time Series Data. In: Sanguinetti, G. and Huynh-Thu, V. (editors),**Gene Regulatory Networks. Methods in Molecular Biology**, vol. 1883, pages 49-94, Humana Press, New York, NY. Webpage- Shafiee Kamalabad, M. and
**Grzegorczyk, M.**(2020): A new partially segment-wise coupled piece-wise linear regression model for statistical network structure inference. In M. Raposo et al. (eds.)**Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2018), Revised Selected Papers**, Lecture Notes in Bioinformatics, Springer, 139-152. Webpage - Shafiee Kamalabad, M. and
**Grzegorczyk, M.**(2018): Non-homogeneous dynamic Bayesian networks with edge-wise coupled parameters. Proceedings of the**International Workshop on Statistical Modelling (IWSM2018)**, vol. 1, 270-275, Bristol, England. Webpage - Shafiee Kamalabad, M. and
**Grzegorczyk, M.**(2018): Improving nonhomogeneous dynamic Bayesian networks with sequentially coupled parameters.**Statistica Neerlandica**, 72 (3), 281-305. Available here - Shafiee Kamalabad, M. and
**Grzegorczyk, M.**(2017): A sequentially coupled non-homogeneous dynamic Bayesian network model with segment-specific coupling strengths. Proceedings of the**International Workshop on Statistical Modelling (IWSM2017)**, vol. 1, 173-178, Groningen, Netherlands. Webpage **Grzegorczyk, M.**, Aderhold, A., and Husmeier, D. (2017): Targeting Bayes factors with direct-path non-equilibrium thermodynamic integration.**Computational Statistics**, 32 (2), 717-761. Available here- Aderhold, A., Husmeier, D., and
**Grzegorczyk, M.**(2017): Approximate Bayesian inference in semi-mechanistic models.**Statistics and Computing**, 27 (4), 1003-1040. Available here **Grzegorczyk, M.**and Shafiee Kamalabad, M. (2016): Comparative evaluation of various frequentist and Bayesian non-homogeneous Poisson counting models,**Computational Statistics**, 32 (1), 1-33. Available here- Shafiee Kamalabad, M. and
**Grzegorczyk, M.**(2016): A non-homogeneous dynamic Bayesian network model with partially sequentially coupled network parameters. Proceedings of the**International Workshop on Statistical Modelling (IWSM2016)**, vol. 1, 139-144, Rennes, France. Webpage IWSM2016 **Grzegorczyk, M.**(2016): A non-homogeneous dynamic Bayesian network with a hidden Markov model dependency structure among the temporal data points.**Machine Learning**, vol. 102 (2), 155-207. Available here**Grzegorczyk, M.**, Aderhold, A., and Husmeier, D. (2015): Network reconstruction with realistic models. In Friel and Wagner (eds.), Proceedings of the**International Workshop on Statistical Modelling (IWSM2015)**, vol. 1, 204-209, Linz, Austria. Webpage IWSM2015**Grzegorczyk, M.**, Aderhold, A., and Husmeier, D. (2015): Inferring bi-directional interactions between circadian clock genes and metabolism with model ensembles.**Statistical Applications in Genetics and Molecular Biology (SAGMB)**, vol. 14 (2), 143-167. Weblink- Aderhold, A., Husmeier, D., and
**Grzegorczyk, M.**(2014): Statistical inference of circadian regulatory networks.**Statistical Applications in Genetics and Molecular Biology (SAGMB)**, vol. 13 (3), 227-273. Weblink **Grzegorczyk, M.**, Aderhold, A., Smith, V.A., and Husmeier, D. (2014): Inference of circadian regulatory networks.**Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO) 2014**, Granada, Spain, 1001-1014. Download PDF- Aderhold, A., Husmeier, D., Smith, A.V., Millar, A.J., and
**Grzegorczyk, M.**(2013): Assessement of regression methods for inference of regulatory networks involved in circadian regulation.**Proceedings of the Tenth International Workshop on Computational Systems Biology, WCSB 2013**, Tampere, Finland, 29-33. Download Proceedings PDF **Grzegorczyk, M.**and Husmeier, D. (2013): Regularization of Non-Homogeneous Dynamic Bayesian Networks with Global Information-Coupling based on Hierarchical Bayesian models.**Machine Learning**, vol. 91 (1), 105-154. Weblink**Grzegorczyk, M.**and Husmeier, D. (2012): Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters.**Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings (AISTATS2012)**, 22, 467-476. Download PDF**Grzegorczyk, M.**and Husmeier, D. (2012): A non-homogeneous dynamic Bayesian network model with sequentially coupled interaction parameters for applications in systems and synthetic biology.**Statistical Applications in Genetics and Molecular Biology (SAGMB)**, vol. 11 (4), Article 7. Weblink**Grzegorczyk, M.**(2012): Modelling regulatory processes during morphogenesis in Drosophila melanogaster with an improved version of the BGMD dynamic Bayesian network model.**Proceedings of the Nineth International Conference on Computational Systems Biology, WCSB 2012**, Ulm, Germany, 27-30. Download Proceedings PDF- Marbach, D., Costello J.C., Küffner, R., Vega, N.M., Prill, P.J., Camacho, D.M., Allison, K.R.,
**The DREAM5 Consortium**, Kellis, M., Collins, J.J., and Stolovitzky, G. (2012): Wisdom of crowds for robust gene network inference.**Nature Methods**, 9, 796-804. Weblink - Dondelinger, F., Aderhold, A., Lèbre, S.,
**Grzegorczyk, M.**, and Husmeier, D. (2011): A Bayesian regression and multiple changepoint model for systems biology. In Conesa, D. et al. (editors)**Proceedings of the 26th International Workshop on Statistical Modelling (IWSM2011)**, Copiformes S.L., Valencia, ISBN 978-84-694-5129-8, 189-194. Proceedings PDF - Husmeier, D., Werhli, A.V., and
**Grzegorczyk, M.**(2011): Chapter 13: Advanced Applications of Bayesian networks in Systems Biology. In D.J. Balding et al. (editors):**Handbook of Statistical Systems Biology**, 270-289, Wiley, Chichester, UK. Weblink **Grzegorczyk, M.**and Husmeier, D. (2011): Improvements in the reconstruction of time-varying gene regulatory networks: dynamic programming and regularization by information sharing among genes.**Bioinformatics**, 27 (5), 693-699. Weblink**Grzegorczyk, M.**and Husmeier, D. (2011): Non-homogeneous dynamic Bayesian networks for continuous data.**Machine Learning**, 83 (3), 355-419. Weblink**Grzegorczyk, M.**, Husmeier, D., and Rahnenführer, J. (2011): Modelling non-stationary dynamic gene regulatory processes with the BGM model.**Computational Statistics**, 26 (2), 199-218. Weblink**Grzegorczyk, M.**(2010): An Introduction to Gaussian Bayesian Networks. In: Yan Qing (Ed.):**Systems Biology in Drug Discovery and Development**(Springer Series: Methods and Protocols: Methods in Molecular Biology, Vol. 662). Humana Press. ISBN 978-1-60761-799-0. Weblink- Ickstadt, K., Bornkamp, B.,
**Grzegorczyk, M.**, Wieczorek, J., Sheriff, M.R., Grecco, H.E. and Zamir, E. (2010): Nonparametric Bayesian Networks. In: Bernardo, Bayarri, Berger, Dawid, Heckerman, Smith and West (eds.):**Bayesian Statistics 9**, Oxford University Press, 283-316. Download PDF - Lohr, M., Godoy, P., Hengstler, J.G., Rahnenführer, J. and
**Grzegorczyk, M.**(2010): In: Nykter, Ruusuvuori, Carlberg and Yli-Harja (eds.) Extracting differential regulatory sub-networks from genome-wide microarray expression data.**Proceedings of the Seventh International Workshop on Computational Systems Biology, WCSB 2010**, Luxembourg, 63-66. Download Proceedings PDF **Grzegorczyk, M.**, Husmeier, D. and Rahnenführer, J. (2010): Modelling Non-Stationary Gene Regulatory Processes.**Advances in Bioinformatics**, Volume 2010, Article ID 749848. Weblink**Grzegorczyk, M.**and Husmeier, D. (2009): Non-stationary continuous dynamic Bayesian networks. In Bengio, Schuurmans, Lafferty, Williams and Culotta (editors)**Proceedings of the Twenty-Third Annual Conference on Neural Information Processing Systems, NIPS 2009**, Curran Associates, ISBN 9781605603520, 682-690. Weblink**Grzegorczyk, M.**and Husmeier, D. (2009): Avoiding Spurious Feedback Loops in the Reconstruction of Gene Regulatory Networks with Dynamic Bayesian Networks. In: V. Kadirkamanathan et al. (eds.):**Pattern Recognition in Bioinformatics, Lecture Notes in Bioinformatics**, Springer-Verlag, Berlin Heidelberg, 113-124. Weblink**Grzegorczyk, M.**and Husmeier, D. (2009): Modelling non-stationary gene regulatory processes with a non-homogeneous dynamic Bayesian network and the change point process. In: Manninen et al. (eds.)**Proceedings of the Sixth International Workshop on Computational Systems Biology, WCSB 2009**, Aarhus, Denmark, 51-54. Download Proceedings PDF**Grzegorczyk, M.**, Husmeier, D., Edwards, D.E., Ghazal, P. and Millar, A.J. (2008): Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler.**Bioinformatics**, 24 (18), 2071-2078. Weblink**Grzegorczyk, M.**and Husmeier, D. (2008): Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move.**Machine Learning**, 71 (2-3), 265-305. Weblink**Grzegorczyk, M.**(2008): Comparison of two different stochastic models for extracting protein regulatory pathways with Bayesian networks.**Journal of Toxicology and Environmental Health, Part A**, 71, 780–787. Weblink**Grzegorczyk, M.**, Husmeier, D. and Werhli, A.V. (2008) Reverse Engineering Gene Regulatory Networks with various Machine Learning Methods. In Emmert-Streib and Dehmer (eds.)**Analysis of Microarray Data. A Network-Based Approach**, Wiley-WCH. Weblink**Grzegorczyk, M.**(2007): Extracting protein regulatory networks with graphical models.**Proteomics**, 7, 51-59. Weblink- Urfer, W.,
**Grzegorczyk, M.**and Jung, K. (2006): Statistics for Proteomics: A review of tools for analyzing experimental data.**Proteomics**, 6, 48-55. Weblink - Werhli, A.V.,
**Grzegorczyk, M.**and Husmeier, D. (2006): Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical Gaussian models and Bayesian networks.**Bioinformatics**, 22 (20), 2523-2531. Weblink - Sievers, S., Fritsch, C.,
**Grzegorczyk, M.**, Kuhnen, C. and Müller, O. (2006): Absolute ß-catenin concentrations in Wnt pathway stimulated and non-stimulated cells.**Biomarkers**, 11 (3), 270-278. Weblink - Werhli, A.V.,
**Grzegorczyk, M.**, Chiang, M.T. and Husmeier, D. (2006): Improved Gibbs sampling for detecting mosaic structures in DNA sequence alignments In: Urfer and Turkman (eds.)**Statistics in Genomics and Proteomics**, Centro Internacional de Matematica, Coimbra. [no link] - Kutzner, N., Hoffmann, I., Linke, C., Thienel, T. and
**Grzegorczyk, M.**, Urfer, W., Martin, D., Winde, G., Traska, T., Hohlbach, G., Müller, K.-M., Kuhnen, C. and Müller, O. (2005): Non-invasive detection of colorectal tumours by the combined application of molecular diagnosis and the faecal occult blood test.**Cancer Letters**, 1, 33-41. Weblink

## More papers

- Flores-Guerrero, J.L.,
**Grzegorczyk, M.A.**, Connelly, M.A., Garcia, E., Navis, G., Dullaart, R.P.F. and Bakker, S.J.L. (2021): Mahalanobis distance, a novel statistical proxy of homeostasis loss is longitudinally associated with risk of type 2 diabetes,**EBioMedicine**, 71, article ID 103550 Available here - Qamar, S., Khalique, A. and
**Grzegorczyk, M.**(2021): On the Bayesian network based data mining framework for the choice of appropriate time scale for regional analysis of drought Hazard,**Theoretical and Applied Climatology**, 143, 1677-1695. weblink - Ali, Z., Hussain, I.,
**Grzegorczyk, M.**, Ni, G., Faisal, M., Qamar, S., Shoukry, A.M., Wahab Sharkawy, M. , Gani, S., and Al-Deek, F. (2020): Bayesian network based procedure for regional drought monitoring: The Seasonally Combinative Regional Drought Indicator.**Journal of Environmental Management**, 276, article: 111296. weblink - Ali, Z., Hussain, I., Faisal, M.,
**Grzegorczyk, M.**, Qamar, S., Shoukry, A.M., Warhab Sharkawy, M., and Gani, S. (2020): On the more generalized non‐parametric framework for the propagation of uncertainty in drought monitoring.**Meteorological Applications**, 27 (3), DOI: 10.1002/met.1914 Available here - Ali, Z., Hussain, I., Faisal, M.,
**Grzegorczyk, M.**, Almanjahie, I.M., Nazeer, A. and Ahmad, I. (2020): Characterization of regional hydrological drought using improved precipitation records under multi-auxiliary information.**Theoretical and Applied Climatology**, 140, 25-36. Weblink - Ali, Z., Hussain, I., Faisal, M., Almanjahie, I.M., Ahmad, I., Kahn, D.M.,
**Grzegorczyk, M.**, and Quamar, S. (2019): A Probabilistic Weighted Joint Aggregative Drought Index (PWJADI) criterion for drought monitoring systems.**Tellus A: Dynamic Meteorology and Oceanography**, 71 (1), DOI: 10.1080/16000870.2019.1588584 Weblink

## Non-peer-reviewed paper contributions (since December 2013)

- Bernal, V., Horvatovich, P., Guryev, V. and
**Grzegorczyk, M.**(2019): COPD, Statistics, and Network Inference.**Periodiek**, no. 2019-3, 9-11. Weblink **Grzegorczyk, M.**, Shafiee Kamalabad, M., Bernal, V., Barafas, S. and Del Core, L. (2018): Supporting the Life Sciences with Statistics.**Periodiek**, no. 2018-3, 8-10. Weblink- short contribution in the section: `New at the Institute' of the
**Bernoulli Gazet**, 2016 Weblink

## Teaching at Groningen University (since December 2013)

- Statistical Reasoning, BSc [2021/2022]
**scheduled** - Statistics, BSc [2021/2022]
**running** - Honours College (on Practiacal Statistical Hypothesis Testing), BSc [2020/2021]
- Contemporary Statistics with Applications, MSc [2020/2021]
- Statistical Reasoning, BSc [2020/2021]
- Statistics, BSc [2020/2021]
- Honours College (on Bayesian networks), BSc [2019/2020]
- Statistical Reasoning, BSc [2019/2020]
- Statistical Genomics, MSc [2019/2020]
- Statistics, BSc [2019/2020]
- Honours College (on Bayesian networks), BSc [2018/2019]
- Contemporary Statistics with Applications, MSc [2018/2019]
- Statistical Reasoning, BSc [2018/2019]
- Statistics, BSc [2018/2019]
- Statistical Consulting, MSc (co-teacher) [2017/2018]
- Honours College (on Bayesian networks), BSc [2017/2018]
- Statistical Genomics, MSc [2017/2018]
- Linear Algebra and Multivariable Calculus for IEM, BSc [2017/2018]
- Statistical Reasoning, BSc [2017/2018]
- Honours College (on Bayesian networks), BSc [2016/2017]
- Contemporary Statistics with Applications, MSc [2016/2017]
- Linear Algebra and Multivariable Calculus for IEM, BSc [2016/2017]
- Statistical Reasoning, BSc [2016/2017]
- Honours College (on Bayesian networks), BSc [2015/2016]
- Linear Algebra and Multivariable Calculus for IEM, BSc [2015/2016]
- Statistical Genomics, MSc [2015/2016]
- Statistical Reasoning, BSc [2015/2016]
- Contemporary Statistics with Applications, MSc [2014/2015]
- Statistical Reasoning, BSc [2014/2015]
- Honours College (on Graphical Models), BSc [2013/2014]

## Supervised Master projects at Groningen University

- Boris Luttikhuizen (2021): Information Coupling in Bayesian Networks,
**MSc thesis**, Mathematics, Groningen University. - Loes Deuling (2021): Prior Information Integration for Bayesian Networks,
**MSc thesis**, Mathematics, Groningen University. - Moschanthi Korre (2021): A new Bayesian network model for learning static and dynamic interactions from temporal data,
**MSc thesis**, Mathematics, Groningen University. - Yulan van Oppen (2020): A Bayesian bivariate response mixed-effects model for zero-inflated count data containing large outliers,
**MSc thesis**: Mathematics, Groningen University. - ChengLong Deng (2020): Elastic Net prediction on high dimensional macroeconomic data,
**MSc thesis**: Econometrics, Groningen University. - Carlos Rodolfo Huerta Santiago (2020): Advanced Bayesian network models,
**MSc thesis**: Mathematics, Groningen University. - Eline Pasch (2020): Girls Perform Better at School - Statistical Facts, Figures and Fallacies in Media Claims,
**MSc thesis**: Science Education and Communication, Groningen University. - David Langbroek (2019): Homogeneous and non-homogeneous dynamic Bayesian network models,
**MSc thesis**: Mathematics, Groningen University. - Dagmar Heeg (2019): Evaluation of a General Bayesian Method using the Cholesky Decomposition to Model the Transmission of Intelligence,
**MSc thesis**: Science Education and Communication, Groningen University. - Dennis Steenhuis (2017): On the Comparison of Changepoints Models in Network Reconstruction with Themselves and their Bayesian Counterparts.
**MSc thesis**: Mathematics, Groningen University. - Gerard Hekkelman (2017): Comparing Graphical Models with Pseudo-likelihood Methods and their Bayesian Counterparts on Gene Regulatory Networks.
**MSc thesis**: Mathematics, Groningen University. - Martin Eisenmann (2016): Statistical Support of Ageing Research at the UMCG.
**MSc thesis**: Mathematics, Groningen University.

## Supervised Bachelor projects at Groningen University

- Leah Dijkshoorn (2021): A comparative methodology study: using Generalised Additive Models to investigate how indicators impact risk of mortality after heart failure in different sexes,
**BSc thesis**, Mathematics, Groningen University. - Herbert Nieweg (2021): How accurate can we predict match outcome based on match state,
**BSc thesis**, Mathematics, Groningen University. - Oskar D.J. Kolkman (2021): A Comparative analysis of Bayesian and Frequentist approaches to linear regression,
**BSc thesis**, Mathematics, Groningen University. - Hessel Beijaard (2021): Recommender Systems with Naive Bayes and Tree-Augmented Naive Bayes,
**BSc thesis**, Mathematics, Groningen University. - Arend-Jan Tissing (2021): A sample size based comparison of the frequentist and Bayesian logistic regression,
**BSc thesis**, Mathematics, Groningen University. - Sarah Jane Greengrass(2021): An investigation into the impact of temperature on the rise and spread of COVID-19 in the Netherlands,
**BSc thesis**, Mathematics, Groningen University. - Naomi Broersma (2021): Comparison of Random Walk Metropolis and Hamiltonian Monte Carlo,
**BSc thesis**, Mathematics, Groningen University. - Tom Schoemaker (2020): Comparative analysis of Frequentist and Bayesian Statistics using simulated count data,
**BSc thesis**, Mathematics, Groningen University. - Mihail Skurovskii (2020): Generalized Linear Models - Comparing Frequentist and Bayesian Approaches,
**BSc thesis**: Mathematics, Groningen University. - Stephanie R. Ranft (2020): Bayesian networks and analysis with incomplete data,
**BSc thesis**: Mathematics, Groningen University. - Simone M.R. Kockelkorn (2020): Bayesian Network of Spotify's audio features,
**BSc thesis**: Mathematics, Groningen University. - Remco Bruinsma (2020): Using Poisson regression to model football scores and exploit inaccuracies in the online betting market,
**BSc thesis**: Mathematics, Groningen University. - Wieger Schipper (2020): A comparative analysis of the graphical lasso and shrinkage based Gaussian graphical models,
**BSc thesis**: Mathematics, Groningen University. - Alexander Hill (2020): Random Walks: The Properties, Applications and Methods of Analysis,
**BSc thesis**: Mathematics, Groningen University. - Laureando Mattia Arsendi (2020): Statistical Modelling of Trajectories with Bezier curves,
**BSc thesis**: Statistics, Padua University (Italy). - Carlo de Vos (2020): Markov Chain Monte Carlo based inference in logistic regression,
**BSc thesis**: Mathematics, Groningen University. - Alexandra Lecka (2019): A Cross-Comparison of Cubic Splines and Gaussian Processes in Function Approximation,
**BSc thesis**: Mathematics, Groningen University. - Li Voon Loke (2019): Performance Comparison of Control Charts,
**BSc thesis**: Mathematics, Groningen University. - Kaisheng Zheng (2019): A Comparison of Bayesian and Classical Statistics in Analyzing Factors Affecting Life Expectancy in OECD Countries,
**BSc thesis**: Econometrics and Operational Research, Groningen University. - Guanqun Ma (2019): Forecasting football match results with the ordered logit model,
**BSc thesis**: Mathematics, Groningen University. - Gerlijn Nolle (2018): Modeling the Transmission of Intelligence within a Bayesian Framework,
**BSc thesis**: Mathematics, Groningen University. - Sijbren Schotanus (2018): Cross-comparison of inference methods for Gaussian Graphical Models,
**BSc thesis**: Mathematics, Groningen University. - Klaas-Daniel Sijtsma (2017): Bayesian Changepoint Models.
**BSc thesis**: Mathematics, Groningen University. - Dagmar Heeg (2017): Optimization of the Bayesian Poisson Changepoint Model.
**BSc thesis**: Mathematics, Groningen University. - Samuel Toby Knight (2015): An Inhomogeneous Bayesian Poisson-Gamma Model for Taxi Calls in New York City.
**BSc thesis**: Econometrics and Operational Research, Groningen University.

## Supervised Internship projects at Groningen University

- Pelle Jonasse (2021): Internship Project: `HLV determination.' at KPM, Amsterdam, Science, Business and Policy (SBP) Master program.
- Mark Redeman (2019): Internship Project: `An Approach in Testing Algorithms.' at KPMG, Groningen, Science, Business and Policy (SBP) Master program.
- Tigran Airapetian (2019): Internship Project: `Bidding for Impact: Partner specific optimization on the Google Ads Platform.' at BelSimpel, Groningen, Applied Mathematics Master program.
- Alida Wiersma (2019): Internship Project: `Statistical Learning Methods for environmental DNA.' at Witteveen+Bos, Deventer, Applied Mathematics Master program,
**2nd supervisor from Statistics**. - Vera Velt (2016): Internship Project: `Gene Driven Drug Discovery' at University Medical Center Groningen (UMCG), Groningen, Science, Business and Policy (SBP) Master program.

## Workshops and conferences with contributions (since December 2013)

- Conference on Statistical Network Science 2019, European Cooperation for Statistics of Network Data Science (COSTNET), Bilbao, Spain, 9-11 October 2019 Weblink
- 34th International Workshop on Statistical Modelling (IWSM), Guimaraes, Portugal, 7-12 July 2019 Weblink
- DuPont symposium on Breeding Data: Statistical Advances in Modern Plant Breeding, Wageningen, Netherlands, 16 October 2018 Weblink
- Conference on Statistical Network Science 2018, European Cooperation for Statistics of Network Data Science (COSTNET), Warsaw, Poland, 26-28 September 2018 Weblink
- 15th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB), Caparica, Portugal, 6-8 September 2018 Weblink
- 33rd International Workshop on Statistical Modelling (IWSM), Bristol, England, 15-20 July 2018 Weblink
- COSTNET Networking Biostatistics meeting, Milano, Italy, 12-13 April 2018 Weblink
- Conference on Statistical Network Science 2017, European Cooperation for Statistics of Network Data Science (COSTNET), Mallorca, Spain, 25-27 October 2017 Weblink
- 32nd International Workshop on Statistical Modelling (IWSM), Groningen, Netherlands, 3-7 July 2017 Weblink
- ICMS workshop: 'Learning graphical models in high dimensional settings', Edinburgh, Scotland, 4-7 April, 2017 Weblink
- Workshop on Computational Models in Biology and Medicine, Hannover, Germany, 2-3 March 2017 Webpage
- Statistics for Structures Seminar Series, Amsterdam, Netherlands, 4 November 2016 Weblink
- Conference on Statistical Network Science 2016, European Cooperation for Statistics of Network Data Science (COSTNET), Ribno (Bled), Slovenia, 21-23 September 2016 Weblink
- 13th Applied Statistics, International Conference, Ribno (Bled), Slovenia, 18-21 September 2016, Short Course on Bayesian networks Weblink
- 31st International Workshop on Statistical Modelling (IWSM), Rennes, France, 4-8 July 2016 Weblink
- 30th International Workshop on Statistical Modelling (IWSM), Linz, Austria, 6-10 July 2015 Weblink
- Satelite meeting: 'Inferring dynamic genetic networks', International Biometric Society (IBS) Channel Network Conference, Nijmegen, Netherlands, 20-22 April 2015 Weblink
- Van Dantzig Seminar Lecture Series, Amsterdam, Netherlands, 9 October 2014 Weblink
- International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO), Granada, Spain, 7-9 April 2014 Weblink