FALL SEMESTER: MATHEMATICAL TOOLS FOR MODELING
The Application for the 2019 Fall Semester in Mathematical Tools for Modeling is NOW OPEN!
The last forty years have seen an accelerating trend toward the applicability of mathematics. To such a degree that, today, they flood and permeate our whole life: finance, climate, electronic commerce, communication and new materials, to name but a few. Many of the ground-breaking technologies that have become available in recent years are mathematical in nature. A strong background in the basic aspects of these mathematical tools is fundamental to understanding their effectiveness and for developing new technologies. This success cannot be explained without the equally accelerated power of computation available to us. By combining mathematical techniques and computational power, we can tackle problems that were unthinkable a few years ago.
The complexity of today's challenges requires the participation of multidisciplinary teams in which mathematicians play a central role. Successful participation in this process requires not only a solid foundation in some mathematical disciplines, but also the ability to manage the computer implementations that facilitate their application to specific problems.
During this semester, we focus on six areas of Mathematics which have had a huge impact on applications: Algebra, Linear Algebra, Differential Equations, Differential Geometry, Dynamics Modeling, and Probability. The courses combine an overview of the basic aspects of each area with interesting applications based on state-of-the-art software. The ability to use mathematical techniques to model real-life situations gives participants in this semester a definite advantage in a world with problems that become more challenging and complex every day. In this semester, we provide the basic tools to tackle a variety of dynamic problems.
|SEMESTER GOALS AND OBJECTIVES|
The aim of this semester is to learn and master the mathematical and computational foundations necessary for students majoring in Math to deepen their knowledge and practical skills in areas related to modeling.
The aim is for students to develop the following skills by the end of the semester:
Successful applicants will:
Click on the tiles below to see details of each of the courses in the program*
*Minimum course load = four per semester
Extra: Workshop on Computational Tools for Modeling [2 weeks]
- Introduction to programming in Python: variables, conditionals, loops, functions, introduction to classes.
- Introduction to programming in R.
- Introduction to SageMath.
|FACULTY FALL 2019|
Post-doctoral research: Universität Heidelberg, Germany; Centro de Investigación en Matemáticas (CIMAT), Mexico; University of Wisconsin-Madison, USA
Ph.D. Universidad Complutense de Madrid, Spain (2010)
Research interests: Algebraic Geometry, Singularity Theory.
Ph.D. University of Utah, USA (1989)
Research interests: Differential Geometry, Riemannian Geometry, Game Theory.
Ph.D. Instituto Nacional de Matemática Pura e Aplicada (IMPA), Brasil (1993)
Research interests: Dynamical Systems, Ergodic Theory.
Post-doctoral research: Fields Institute for Research in Mathematical Sciences, Canada; Universitat Autònoma de Barcelona, Spain
Ph.D. Boston University, USA (2002)
Master’s degree: Applied Mathematics, Centro de Investigación en Matemáticas (CIMAT), Mexico (1997)
Research interests: Holomorphic Dynamical Systems, Continuum Theory.
Post-doctoral research: University of Virginia, USA
Ph.D. University of Michigan, Ann Arbor, USA (2013)
Research interests: Commutative and Algebraic Geometry.
Ph.D. University of North Carolina at Chapel Hill, USA (1985)
Master’s degree: Mathematics, Instituto Politécnico Nacional, Mexico (1977-1979)
Research interests: Probability and Statistics, Random Matrices, Mathematics for Data