Dalarna University

https://www.du.se/en/about-du/personal-presentation/?userId=1998840162
https://www.researchgate.net/profile/Alam_Moudud

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Current Position: Associate Professor in Microdata Analysis School of Technology and Business Studies Dalarna University, Sweden. Contact: Moudud Alam School of Technology and Business Studies Högskolan Dalarna SE 791 88 Falun Sweden. Tel. +46-(0)23-778854, e-mail: maa@du.se Professional Experiences: Position Associate Professor in Microdata Analysis Institution School of Technology and Business Studies, Dalarna University. Duration 14th of December 2017 till date. Position Visiting Research Fellow Institution Data Science for Knowledge Creating Research Centre, Seoul National University, South Korea. Duration 1st of March 2018 to April 30, 2018. Position Senior Lecturer in Statistics Institution School of Technology and Business Studies, Dalarna University. Duration 1st of July 2014 till date. Doctoral Degree: Doctoral degree (PhD) obtained in 2011 from the Swedish Business School at Örebro University with the thesis entitled, “Feasible Computation of the Generalized Linear Mixed Models with Application to Credit Risk Modelling” (public defence took place in December, 2010), under the supervision of Prof. Sune Karlsson. Recent Research Grants: 1. Project name: Bättre social miljö för mjölkkor kan öka djurens välfärd och production Role: Participant Funder: FORMAS Period: 2019-2021 2. Project name: Feeding reindeer for future free-range functionality – REINFEED. Role: Participant Funder: FORMAS Period: 2019-2021 3. Project: Reindeer and wind power in the winter grazing area Role: Participant Funder: VINDVAL, Swedish Energy Agency Period: 2018-2020 List of recent publications 1. Saqlain, M., Alam, M., Rönnegård, L., and Westin, J. (2020), Investigating stochastic differential equations modelling for levodopa infusion in patients with Parkinson’s disease, European Journal of Drug Metabolism and Pharmacokinetics, 45(1): 41-49 . 2. Thomas, I., Alam, M., Bergquist, F., and Johansson, D. (2019), Sensor-based algorithmic dosing suggestions for oral administration of levodopa/carbidopa microtablets for Parkinson's disease: a first experience, Journal of Neurology, 266(3): 651-658 3. Svenson, K., McRobbie, S., and Alam, M. (2019): Detecting road pavement deterioration with finite mixture models, International Journal of Pavement Engineering, 20(4): 458-465. 4. Nowak, C., Carlsson, A. C., Östgren, C.J., Nyström, F. H., Alam, M., …, and Ärnlöv, J. (2018), Multiplex proteomics could improve understanding and risk prediction of major adverse cardiovascular events (MACE) in type 2 diabetes. Diabetologia, 61(8): 1748–1757 5. Thomas, I., Westin, J. Alam, M., Bergquist, F., Nyholm, D., Senek, M., and Memedi, M. (2018), A treatment–response index from wearable sensors for quantifying Parkinson's disease motor states, IEEE Journal of Biomedical and Health Informatics, 22(5): 1341 - 1349. 6. Skarin, A., Sandström, P. and Alam, M. (2018), Out of sight of wind turbines—Reindeer response to wind farms in operation. Ecology and Evolution, 8: 9906–9919. 7. Skarin, A., and Alam, M. (2017), Reindeer habitat use in relation to two small wind farms, during preconstruction, construction, and operation. Ecology and Evolution, 7: 3870–3882. 8. Lee, Y., Alam, M., Noh, M., Rönnegård, L., and Skarin, A. (2016), Spatial modelling of data with excessive zeros applied to reindeer pellet-group counts, Ecology and Evolution, 6: 7047-7056. 9. Alam, M., Rönnegård, L., and Shen, X. (2015), Fitting conditional and simultaneous autoregressive spatial models in hglm, The R Journal, 7(2): 5-18. 10. Alam, M. (2014), Likelihood prediction for generalized linear mixed models under covariate uncertainty, Communications in Statistics-Theory and Methods, 43(2): 219-234.