Biography

Frank Nielsen was awarded his PhD on adaptive computational geometry (1996) from INRIA/University of Cote d’Azur (France). He is a fellow of Sony Computer Science Laboratories Inc. (Sony CSL, Tokyo) where he currently conducts research on the fundamentals and practice of geometric machine learning and intelligence. He taught at Ecole Polytechnique (France) visual computing (Charles River Media textbook, 2005) and high-performance computing for data science (Springer UTICS textbook, 2016), and currently serves the following journals: Springer Information Geometry, MDPI Entropy, and IEEE Transactions on Information Theory. Frank Nielsen co-organizes with Frederic Barbaresco the biannual conference Geometric Science of Information (GSI LNCS proceedings).

• Five selected publications:
  • Bregman Voronoi diagrams, Discrete and Computational Geometry, 2010.
  • The Burbea-Rao and Bhattacharyya centroids, IEEE Transactions on Information Theory, 2011.
  • An information-geometric characterization of Chernoff information, IEEE Signal Processing Letters, 2013.
  • On the chi square and higher-order chi distances for approximating f-divergences, IEEE Signal Processing Letters, 2013.
  • Generalized Bhattacharyya and Chernoff upper bounds on Bayes error using quasi-arithmetic means, Pattern Recognition Letters, 2014.
   
  
• Five selected collaborative publications tackling various applications:
  • Imaging: Statistical region merging, IEEE Transactions on pattern analysis and machine intelligence, 2014.
  • Music: DeepBach: a Steerable Model for Bach Chorales Generation, ICML 2017.
  • Computer graphics: Volumetric illustration: designing 3D models with internal textures, SIGGRAPH, 2004.
  • Computer vision: Shape retrieval using hierarchical total Bregman soft clustering, IEEE transactions on pattern analysis and machine intelligence, 2012.
  • Telecommunications: Combinatorial optimization algorithms for radio network planning, Theoretical Computer Science 2001.

1. Basic (Vic-20)
2. LOGO (Amstrad PCW)
3. Assembler
4. Turbo Pascal (IBM)
5. FORTRAN
6. LISP
7. PROLOG
8. OCAML
9. C
10. C++
11. C* (CM2)
12. Hypercard (Apple)
13. (OpenGL)
14. Java/Processing
15. Javascript
16. (MPI/OpenCL)
17. Excel (yes, macros when grading my teaching!)
18. Scala
19. R
20. Python
21. Julia