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Qualified Full Professor in Applied Mathematics (CNU 26)

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International Academic Lecture at CERN (Geneva) - 13/12/2016:

Data Mining and Real Systems Modeling 

Here is the video of the lecture !


1. 2023On a new Taylor-like theorem: Application for error estimates of numerical approximations, 15th International Conference on Pure and Applied Mathematics, (Rhodes, Greece).

2. 2022A new probabilistic approach applied to error estimates of numerical approximations, 8th International Conference on Mathematics and Computers in Sciences and Industry, (Athens, Greece).

3. 2022Revisited finite element error estimate by a new probabilistic approach, 8th Ariel University Conference on Functional Differential Equations and Applications, (Ariel, Israel).

4. 2019, From a geometrical interpretation of Bramble Hilbert lemma to a probabilistic distribution for relative finite elements accuracy, International Academic Conference at CERN, (Geneva, Switzerland).

5. 2018From a geometrical interpretation of Bramble Hilbert lemma to a probabilistic distribution for finite elements accuracy, 7th International Conference of Finite Difference Methods. Theory and Applications(Lozenetz, Bulgaria).

6. 2016, Data Mining and Real Systems Modeling, International Academic Conference at CERN, (Geneva, Switzerland).

Research topics:

1. Probabilistic approach for a priori and error estimate of solution and approximation to determinist partial differential equations

  • Mixed geometrical-probabilisitic interpretation of error estimate derived form Bramble-Hilbert lemma: Application to the relative accuracy between two Lagrange finite elements.
  • On generalized binomial laws to evaluate finite element accuracy:On generalized binomial laws to evaluate finite element accuracy:toward applications for adaptive mesh refinement.
  • Relative accuracy for high order finite element by a mixed functional-probabilistic approach.
  • Explicit k−dependency for Pk finite elements in Wm,p error estimates: application to probabilistic laws for accuracy analysis.
  • Continuous probability distribution to compare the approximation error between two Lagrange finite elements.

 2. Mathematical Modeling and Data Mining for Particle Physics

  • Probabilist models and Data Mining methods for error estimate of finite element method.
  • Asymptotic solutions of Vlasov-Maxwell equations applied to relativist paraxial beams.

3. Mathematical modeling and Data Mining applied to Mechanics

  • Bifurcation analysis of Navier Stokes solutions which model atmospheric tornadoes genesis.
  • Data Mining methods applied to aerodynamic optimization strategies for unmanned flight.
  • The complexity, randomness and chaos in elastic vibration systems.

4. Mathematical Modeling andData Mining for Medicine

  • Treatment of Sleep Apnea: Model predictive and characterization protocols "success" and "failure." Exploratory analysis of the relationship between insomnia and Disease Sleep Apnea by data mining methods.
  • Statistical and Data Mining techniques applied to the relationship between the excitability of the supplementary motor area with repetitive transcranial magnetic stimulation and the breathing pattern response caused by an experimental inspiratory load possibly respiratory discomfort.

  • Evolution of health-related quality of life two to seven years after retropubic radical prostatectomy: evaluation by UCLA prostate cancer index.
  • Mathematical methods applied to model the human immune system for the treatment of bladder cancer by injecting the bacteria BCG and interleukin-2.
  • Explicative factors of intrauterine insemination success based on exploratory analysis of 2089 cycles done with statistical and Data Mining tools.

5. Probabilistic modeling for media and marketing

  • Volterra integro differential equation model applied to marketing and media behavior.
  • Unsteady Markov process applied to media exposure.
  • General relativity models applied to geomarking.