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Mikael Vejdemo-Johansson started out in computational homological algebra, studying algorithms for computing invariants of Tor modules and A?-algebra structures on the modular group cohomology rings of p-groups. After finishing his PhD, he has worked during postdoctoral studies at Stanford University (2008-2011), University of St Andrews (2011-2012), KTH Royal Institute of Technology (2012-2013, 2014-2015) and the Institute of Mathematics and its Applications, University of Minnesota (2013-2014) on Topological Data Analysis: using persistent homology and cohomology to compute descriptors for abstract point clouds, and the Mapper algorithm generalizing Reeb graphs and nerve simplicial complex constructions to produce intrinsic topological model spaces for arbitrary data. He seeks out application realms anywhere he can find them, and has published work on applications to parliamentary voting records, to the statistics of color naming systems in linguistics, to motion capture data.

In addition to these primary research interests, he has worked on enumerating tie knots, finding 262862 possible tie knots using formal languages and algebraic systems of equations.