Teaching

• Universidad Adolfo Ibáñez
  • ING200 Optimization.
  • ING480 Process and Service Design.
• University of South Florida
  • ENG3443 Probability and Statistics.
  • EGN4450 Introduction to Linear Systems.
• Universidad de La Frontera
  • GIC305 Data Analysis.

Universidad Adolfo Ibáñez

ING-200 Optimization

Optimization involves making the best selection from a set of elements. The goal is to achieve the best possible outcome, given limited resources. In mathematical terms, this refers to finding the optimal values that maximize or minimize a function, depending on the situation. Optimization is used in various problems, such as operations management, logistics, communications, and strategic planning, among many other areas. This course aims to develop skills that allow students to take an abstract decision-making problem, appropriately model it as an optimization problem, solve it, and interpret its solution. The general topics covered in the course are modeling, linear programming, sensitivity analysis, integer programming, and nonlinear programming.

Learning Outcomes

• Formulate optimization models of different types (continuous or discrete, linear or nonlinear) from various contexts.
• Solve different optimization models using various methods such as graphical method, Simplex, branch and bound, and Karush-Kuhn-Tucker conditions.
• Analyze and solve optimization problems using computational tools.

ING480 Process and Service Design

This course covers concepts and methods for efficiently designing and managing operations to align a good or service’s supply (production) with its demand. The course addresses process identification, productivity, cost analysis, and process management in manufacturing and service companies. In general, the goal of the course is for students to be able to answer questions such as: How should I produce the goods or services required by a company’s customers? How can I improve a company’s processes? How can I improve the productivity of a process? How can I improve quality and consistently produce high-quality outputs?

More specifically, by the end of the course, students will be able to:

• Understand processes in the context of manufacturing and services.
• Identify elements of process management.
• Identify processes, flow units, and capacities in processes.
• Distinguish, calculate, and evaluate process metrics.
• Model process diagrams.
• Calculate costs related to a process.
• Identify value addition in processes.
• Understand concepts and tools of Total Quality Management and Six Sigma.
• Understand components of the Lean method.

University of South Florida

ENG3443 Probability and Statistics

The world is divided into two realms: deterministic and probabilistic. Your math, physics, and chemistry course preparation has focused on “deterministic” models: a given set of inputs or conditions repeatedly produces a fixed, entirely predictable output. This course launches the student modeling skills into a new dimension wherein a given set of inputs or conditions produce random (or “chance” or “probabilistic” or “stochastic”) outcomes. Examples include the characteristics of products leaving manufacturing lines (e.g., a lifetime of a bulb, the concentration of a therapeutic drug), results of laboratory experiments (e.g., growth rates of microorganisms), or processes observed over space or time (e.g., the spatial distribution of soil contaminants or time series of rainfall amounts). The field of statistics deals with the collection, presentation, analysis, and use of data to make decisions, solve problems, and design products and processes.

The first part of the course is devoted to presenting probabilistic concepts that form the building blocks of all statistical procedures, which will be introduced in the course’s second (more applied) part. Information and Data Literacy assignments are embedded throughout the course to help students develop and exercise the skills for critical thinking, problem-solving, critical interpretation of data, comparing opposing claims on the same hypothesis, and professional communication of statistics.

EGN4450 Introduction to Linear Systems

When you take photos with your cell phone, play video games, or do a Google search, you use technologies built upon linear algebra theory. In this class, we study the fundamentals of linear algebra that will help you assess linear systems and manipulate big datasets. Essential topics are the application of matrix algebra, differential equations, and calculus of finite differences. Specific concepts we review in this course are systems of linear equations and matrices, determinants, euclidean vector spaces, general vector spaces, eigenvectors, and eigenvalues.

Universidad de La Frontera

GIC305 Data Analysis

This course focuses on statistical learning for data science and analytics. With the rapid advancement of sensing technology and information systems, massive amounts of data have been generated in various fields, ranging from engineering to applied science. There is an increasing need for data scientists and analysts with the skills and knowledge to analyze and interpret such data to extract patterns and gain insights for problem-solving and decision-making. The objective is to provide students with various data mining and statistical learning techniques, emphasizing concepts and applications. These techniques include regression, classification, clustering, and high-dimensional analysis. Specific concepts we review in this course are linear and logistic regression, decision trees, random forest, dimensionality reduction, clustering, and visualization.