Dr Pierre Haas



  • 2017-          : Nevile Research Fellow in Applied Mathematics, Magdalene College, Cambridge
  • 2016-2017 : EPSRC Doctoral Prize Fellow, DAMTP, University of Cambridge
  • 2013-2016 : PhD Student, DAMTP, University of Cambridge
  • 2009-2013 : Mathematical Tripos (BA & MMath), Gonville & Caius College, Cambridge


Pierre is a member of the Biological Physics research group in the Department of Applied Mathematics and Theoretical Physics. His research is on the mathematics of morphogensis: how does shape arise in physical systems, living or otherwise?. In particular, Pierre is interested gaining a mechanical understanding of the inversion process in the green alga Volvox, spherical sheets of cells that turn themselves inside out through a small hole at the top.

Related Publications

  1. S. Höhn, A. R. Honerkamp-Smith, P. A. Haas, P. Khuc Trong, and R. E. Goldstein, "Dynamics of a Volvox Embryo Turning Itself Inside Out", Physical Review Letters 114, 178101 (2015).
  2. P. A. Haas and R. E. Goldstein, "Elasticity and Glocality: Initiation of Embryonic Inversion in Volvox", J R Soc Interface 12, 20150671 (2015).
  3. P. A. Haas, S. S. M. H. Höhn, A. R. Honerkamp-Smith, J. B. Kirkegaard, and R. E. Goldstein, "Mechanics and Variability of Cell Sheet Folding in the Embryonic Inversion of Volvox", sub judice (2017).
  4. P. A. Haas and R. E. Goldstein, "Mechanics of Embryonic Inversion in the Green Alga Volvox carteri", preprint (2017).

Shape generating chemical systems are a very literal instantiation of Turing's quest for the chemical basis of morphogenesis. Pierre has been interested in developing a theory describing a recently discovered exemplar of such a system: oil emulsion droplets that flatten into a variety of polygonal shapes upon slow cooling.

Related Publication

  1. P. A. Haas, R. E. Goldstein, S. K. Smoukov, D. Cholakova, and N. Denkov, "A Theroy of Shape-Shifting Droplets", Physical Review Letters 118, 088001 (2017).

Another research interest centres around probabilistic models for the prediction of RNA secondary structures, in particular extending models based on stochastic context-free grammars to include kinetic transcription effects.

Related Publication

  1. J. W. J. Anderson, P. A. Haas, L.-A. Mathieson, V. Volynkin, R. Lyngsø, P. Tataru, and J. Hein, "Oxfold: kinetic folding of RNA using stochastic context-free grammars and evolutionary information", Bioinformatics 29, 704 (2013).