I am working with numerical methods for genetic analysis of complex traits. My main supervisor is Sverker Holmgren (Professor in Scientific Computing) and my co-supervisor are Lars Rönnegård(Professor, Dalarna University, Section of Statistics) and Carl Nettelblad (PhD in Scientific Computing, Uppsala University). For more information please visit our research group web page.
My research interests lie generally in the fields of statistical computing. Statistical computing is the application of scientific computing and computer science to statistics.
- M.S., Engineering Mathematics and Computational Science (with specialization in Mathematical Statistics); Chalmers University of Technology, Goteborg, Sweden; Thesis Topic: Exploring connectivity of random subgraphs of a graph, Adviser: Professor Jeffrey Steif
- M.S., Complex Adaptive Systems, 2008; Chalmers University of Technology, Goteborg, Sweden; First Thesis Topic: Implementing two simplified coalescent algorithms, Adviser: Professor Bernhard Mehlig; Second Thesis Topic: Analyzing two simplified coalescent algorithms, Adviser: Dr. Anders Eriksson
- B.S., Applied Mathematics, 2004; K.N.T University of Technology, Tehran, Iran; Thesis Topic: Java-3D and Computer Graphics, Adviser: Mr. H.MohamadZadeh
- Fitting Linear Mixed Models using Sparse Matrix Methods for Large Matrices. Submit Sep 2015. Behrang Mahjani, Lars Rönnegård, Lars Elden
- A flexible computational framework using R and Map-Reduce for permutation tests of massive genetic analysis of complex traits. Submitted Jan 2015. Behrang Mahjani, Salman Toor, Carl Nettelblad, Sverker Holmgren
- Fast and accurate detection of multiple quantitative trait loci. Carl Nettelblad, Behrang Mahjani, and Sverker Holmgren. In Journal of Computational Biology, volume 20, pp 687-702, 2013.
- Sequential Markov coalescent algorithms for population models with demographic structure. A. Eriksson, Behrang Mahjani and B. Mehlig, Theoretical Population Biology, Volume 76, Issue 2, September 2009, Pages 84-91
- Map-Reduce programming model for QTL applications, Poster presentation, Winter school in Big data challenges to modern statistics, Geilo, Norway, Jan 2014
- USING PEAK SHAPE TO IMPROVE EFFICIENT AND EFFECTIVE DETECTION OF MULTIPLE QTL IN KNOWN CROSSINGS, Carl Nettelblad, Behrang Mahjani, Fourth International Conference of Quantitative Genetics, 17-22 June 2012
- Advanced Statistical Computing, developing a new course for Autumn 2015
- Computer-intensive Statistics and Data Mining, Spring 2012, Spring 2013, Spring-Autumn 2014, Spring-Autumn 2015, Spring-Autumn 2016
- Scientific computing II, Autumn 2015
- Computational Finance, Spring 2012
- Fast and Accurate Detection of Multiple QTL in Know Crossing, Behrang Mahjani, Talk, 4th Swedish Meeting on Mathematics in Biology 11-12 December.
- Detection of Multiple QTL in Known Crossings, Talk, ReiDok1, 3Symposium on Computational PhD Projects, University of Iceland, April 22 201.