JUAN ESTEBAN DIAZ LEIVA

ESTUDIOS

  • PhD in Business and Management, The University of Manchester
  • MSc in Food and Resource Economics, Rheinische Friedrich-Wilhelms-Universität Bonn

EXPERIENCIA LABORAL

Director Data Science Institute & Professor, Universidad San Francisco de Quito
( 2016 - Hasta el presente )
Teaching, research and projects
Seminar Leader, The University of Manchester
( 2015 - 2016 )
Course: “Decision Modelling for Resource Management”, this course is focussed on the solution of real-world problems through optimization
Quality Management Regional Analyst, Nestlé
( 2010 - 2011 )
High and ultra performance liquid chromatography (HPLC y UPLC) expert, responsible for liposoluble vitamins for Ecuador, Colombia y Venezuela
Research Assistant, Technische Universität München
( 2009 - 2009 )
HPLC, micro y ultra filtration

PUBLICACIONES

2021 Artificial Intelligence: Limits and Challenges
2021 Incorporating Decision-Maker\'s Preferences into the Automatic Configuration of Bi-Objective Optimisation Algorithms
2021 Interactive Parameter Tuning of Bi-objective Optimisation Algorithms Using the Empirical Attainment Function
2020 Software open-source - Incorporating Decision-Maker\'s Preferences into the Automatic Configuration of Bi-Objective Optimisation Algorithms
2018 Integrating meta-heuristics, simulation and exact techniques for production planning of a failure-prone manufacturing system
2017 Evolutionary robust optimization in production planning–interactions between number of objectives, sample size and choice of robustness measure
2016 Multi-Objective Formulations for Robust Optimization
2016 Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems
2015 Implicit and explicit averaging strategies for simulation-based optimization of a real-world production planning problem
2014 Linear Programming Applied to Production Planning of Manufacturing Processes
2014 Simulation-based GA optimization for Production Planning
2010 Eficiencia de las pruebas discriminatorias para reportar diferencias cuando se utilizan consumidores ecuatorianos

INTERESES

Business Analytics, Machine Learning, Multi-Objective Optimization under Uncertainty, Simulation-Based Optimization, Automatic Design and Configuration of Evolutionary Algorithms, Seeding in Evolutionary Algorithms, Robust Optimization and Matheuristics, Modelaje y Optimización de Sistemas Complejos, Gerencia de Producción, e Investigación de Operaciones