XavierEstrella | Civil Engineering | Best Researcher Award

Dr. XavierEstrella, Ecole Polytechnique Federale de Lausanne, Ecuador.

Dr.Xavier Estrella is a Doctor of Engineering Sciences specializing in quantitative research and numerical analysis for civil engineering applications . With over 4 years of experience, his expertise spans risk quantification, stochastic simulations, time series , and signal processing. He holds advanced degrees from prestigious institutions , including a Ph.D. in Civil and Environmental Engineering and a Master’s in Financial Engineering . Currently a Postdoctoral Researcher at EPFL , Xavier has a proven track record in developing optimization software and machine learning models for structural design. He is fluent in Spanish, English, and French , and is recognized for his critical thinking and problem-solving skills .

Publication Profile

Google Scholor

Scopus

Education

Doctor of Philosophy, Civil and Environmental Engineering, University of Technology Sydney, Australia (2019 ‒ 2022).
Master of Sciences, Financial Engineering, World Quant University, U.S.A. (2023 ‒ Present).
Bachelor of Engineering, Civil Engineering, Universidad del Azuay, Ecuador (2010 ‒ 2015).
Doctor of Engineering Sciences, Structural Engineering, Pontificia Universidad Católica de Chile, Chile (2016 ‒ 2020).
Master of Sciences, Education Quality Management, Universitat Oberta de Catalunya, Spain (2018 ‒ 2019).

Experience

Postdoctoral Researcher, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (2021 ‒ Present)
- Development of optimization software for flood-resilient housing design in South Sudan, Africa .
- Mathematical modeling of the reuse potential of construction components in western Switzerland .
- Training, testing, and validation of machine learning models for assisted structural design of timber buildings .

Research Assistant, Timber National Center (CENAMAD), Santiago, Chile (2017 ‒ 2020)
- Developed a novel numerical formulation for efficient modeling of timber buildings .
- Created an open-source database of earthquake records for safe housing design in South America .
- Conducted risk analysis, dynamic testing, and performance evaluation of timber buildings in earthquake-prone areas .

Professional Development

Dr.Xavier Estrella has a strong professional development record . As a Postdoctoral Researcher at EPFL , he developed optimization software for flood-resilient housing in South Sudan and modeled the reuse potential of construction components in Switzerland . He also trained machine learning models for timber building design . At CENAMAD in Chile , he created a numerical formulation for timber buildings , developed an earthquake record database for safe housing , and conducted risk analysis and dynamic testing for earthquake-prone areas . Xavier’s work has earned him multiple prestigious awards , showcasing his expertise and dedication to civil engineering advancements.

Research Focus

Dr.Xavier Estrella’s research focuses on quantitative methods and numerical analysis for civil engineering applications . He specializes in risk quantification, stochastic simulations, time series analysis , and signal processing. His projects include developing optimization software for flood-resilient housing in South Sudan and modeling the reuse potential of construction components in Switzerland . At CENAMAD , he created a numerical formulation for timber buildings and an earthquake record database for safe housing . Xavier’s work integrates advanced computational methods with practical engineering solutions, aiming to improve structural safety and resilience in diverse environments .

Publication Top Notes:

Efficient nonlinear modeling of strong wood frame shear walls for mid-rise buildings
X Estrella, P Guindos, JL Almazán, S Malek
Engineering Structures 215, 110670, 32 citations, 2020
Cyclic behavior of wood-frame shear walls with vertical load and bending moment for mid-rise timber buildings
P Orellana, H Santa María, JL Almazán, X Estrella
Engineering Structures 240, 112298, 25 citations, 2021
Experimental study of the effects of continuous rod hold-down anchorages on the cyclic response of wood frame shear walls
X Estrella, S Malek, JL Almazán, P Guindos, H Santa María
Engineering Structures 230, 111641, 23 citations, 2021
Ground motions for FEMA P-695 application in subduction zones
X Estrella, P Guindos, JL Almazán
Latin American Journal of Solids and Structures 16, e237, 20 citations, 2019
Seismic performance factors for timber buildings with woodframe shear walls
X Estrella, P Guindos, JL Almazán, S Malek, H Santa María, J Montaño, …
Engineering Structures 248, 113185, 16 citations, 2021
A simplified approach to assess the technical prefeasibility of multistory wood-frame buildings in high seismic zones
S Berwart, X Estrella, J Montaño, H Santa-María, JL Almazán, P Guindos
Engineering Structures 257, 114035, 13 citations, 2022
Development of an amplified added stiffening and damping system for wood-frame shear walls
J Montaño, R Maury, JL Almazán, X Estrella, P Guindos
Latin American Journal of Solids and Structures 17, e283, 8 citations, 2020

PedroReyes Norambuena | Engineering| Best Researcher Award

Mr. PedroReyes Norambuena, Universidad Católica del Norte ,Chile

Mr.Pedro Jonathan Reyes Norambuena, a Mechanical Civil Engineer with an MBA and a Master’s in Mathematics and Computer Engineering, is currently a PhD candidate in Mathematics and Applications at the University of Vigo, Spain. He is an academic at the Universidad Católica del Norte, Chile, teaching Industrial Engineering courses like Quality, Reliability, Asset Management, and Applied Statistics. His research focuses on sustainable urban planning and the application of machine learning in engineering. He has published numerous papers and holds various certifications, including a Black Belt Six Sigma. Pedro is dedicated to advancing engineering and urban infrastructure through innovative research.

Publication Profile

Education And Experience

Mr.Pedro Jonathan Reyes Norambuena is a highly qualified Mechanical Civil Engineer, holding an MBA and a Master’s in Mathematics and Computer Engineering. Currently pursuing a PhD in Mathematics & Applications, he is deeply involved in academia at the Universidad Católica del Norte, Chile, where he teaches Industrial Engineering courses. Pedro has a strong publication record and has contributed significantly to the field of sustainable urban planning and machine learning. His extensive experience includes roles as a Project Engineer at SIEMENS S.A. and leadership positions within the School of Engineering, Universidad Católica del Norte. Pedro is committed to advancing engineering education and research.

Professional Development

Mr.Pedro Jonathan Reyes Norambuena has pursued continuous professional development throughout his career, showcasing a commitment to enhancing his skills and knowledge. His achievements include a PhD candidacy in Mathematics & Applications, an MBA, and a Master’s in Mathematics and Computer Engineering. Pedro’s diverse educational background is complemented by his extensive teaching experience in Industrial Engineering, where he covers topics such as Quality, Reliability, Asset Management, and Applied Statistics. His active involvement in academia and research, combined with his leadership roles and consulting projects, reflects his dedication to personal and professional growth. Pedro’s enthusiasm for learning is evident in his pursuit of certifications and participation in various training programs.

Research Focus

Mr.Pedro Jonathan Reyes Norambuena’s research focuses on applying advanced mathematical and computational models to solve engineering and urban planning problems. His work includes the development of multi-criteria decision-making models for sustainable urban development and policy-making in educational settings. He also explores the use of machine learning techniques for simulating pedestrian dynamics. This interdisciplinary approach combines engineering, mathematics, and computer science to address real-world challenges, aiming to optimize urban infrastructure and improve decision-making processes in various fields.

Publication Top Notes