Antoine Tambue

Field of work

Antoine   Tambue  is a Full Professor  in  Mathematics  at Department of Computer science, Electrical engineering and Mathematical sciences,  Western Norway University of Applied Sciences (HVL), Norway.

In 2010, he obtained a PhD in  Mathematics at Heriot-Watt University (UK) via an interdisciplinary collaborative project (Bridging the Gaps Between Engineering and Mathematics) between the department of mathematics and  Institute of Petroleum Engineering (since 2019 Institute of GeoEnergy Engineering).  His PhD study was funded  by  the prestigious ORS Awards Scheme.  He was a postdoctoral associate at the University of Bergen from 2010  to December 2013 and  at  the Norwegian University of Science and Technology (NTNU) in 2014. In July 2014, Antoine was appointed as the first AIMS ARETÉ (African Research, Education and Teaching Excellence) junior research Chair funded by  Robert Bosch Stiftung (Germany) and was based at African Institute for Mathematical Sciences  (AIMS) in South Africa  and  the University of Cape Town. The research chair position allowed him to supervise as main supervisor 5 PhD students and  12 masters  theses at AIMS South Africa, University of Cape Town (South Africa), University of Dschang (Cameroon), Chemnitz university of technology (Germany) and Institut de Mathematiques et des Sciences physiques (Benin).

More earlier,   he completed a Bachelor in  Mathematics at University Dschang in Cameroon,  a Master in Mathematics  at University of Yaounde I, Cameroon, a professional  Master in Mathematics  Education at Ecole Normale Superieure de Yaounde  and  a postgraduate diploma in mathematical Sciences  at  AIMS  South Africa and University of Cape Town in South Africa.

His main research interests are  Stochastic Calculus, Numerical Analysis, scientific computing, operational research (stochastic optimal control), computational finance, computational statistics (Bayesian inference) and AI.

 His research vision is to develop novel numerical algorithms, which are efficient ( fast and accurate), scalable in supercomputers to address realistic problems (example, subsurface energy extraction and exploration, pricing options, data mining, life sciences). This is from rigorous mathematical analysis to ingenious implementation in a range of such important applications.

He has developed and analysed many numerical algorithms   for Real-world Systems in low dimension and currently has huge interest in high dimensional   PDEs,  uncertainty quantification,  parameters estimation  and  Operational research (stochastic optimal control) using tool from stochastic analysis, statistics (Bayesian inference) and AI.

Courses taught

• MAT 110 (Basic mathematics for Engineers)
• MAT202 (Advanced mathematics for Engineers)
• MAT301: Multidimensional analysis (Operational research( optimization), triples integrals, lines integrals, surface integrals)
• PCS911: PhD level (Engineering Computing)

     
Research areas

• Engineering computing and Applied Mathematics
• Partial differential equations
• Stochastic Calculus
• Computational Statistics
• Operational research
• Computational finance
• Stochastic optimal control
• Computational Mathematics