André Gustavo Carlon is a Postdoctoral Fellow at Stochastic Numerics Research Group under the supervision of Professor Raul F. Tempone at King Abdullah University of Science and Technology (KAUST).

Research Interests

André's research interests include the analysis of stochastic optimization methods, ​the application of stochastic gradient methods to engineering problems, and Bayesian optimal experimental design with non-linear models.

Selected Publications​

• A. G. Carlon, L. Espath, R. Tempone. Approximating Hessian matrices using Bayesian inference: a new approach for quasi-Newton methods in stochastic optimization. Optimization Methods and Software, 2024.
• A. G. Carlon, H. M. Kroetz, A. J. Torii, R. H. Lopez, L. F. F. Miguel. Risk optimization using the Chernoff bound and stochastic gradient descent. Reliability Engineering & System Safety, 2022.
• ​A. G. Carlon, B. M. Dia, L. F. R. Espath, R. H. Lopez, R. Tempone. Nesterov-aided stochastic gradient methods using Laplace approximation for Bayesian design optimization. Computer Methods in Applied Mechanics and Engineering, 2020.
• A. G. Carlon, R. H. Lopez, L. F. R. Espath, L. F. F. Miguel, A. T. Beck. A stochastic gradient approach for the reliability maximization of passively controlled structures. Engineering Structures, 2019.

Professional Memberships

• Member of the STOCHNUM group at KAUST.
• ​Member of CORE/UFSC - Center for quantification and reliability in engineering.

Education Profile

• ​Dr. Eng. in Civil Engineering, Department of Civil Engineering, Federal University of Santa Catarina
• M.Sc. in Civil Engineering, Department of Civil Engineering, Federal University of Santa Catarina

Presentations

• Bayesian quasi-Newton method for stochastic optimization at the Stochastic Numerics and Statistical Learning 2023
• Bayesian quasi-Newton method for stochastic optimization at the UQ Hybrid Seminar