Mathematical Data Science is an exciting inter-disciplinary field that leverages Mathematics, Statistics and computer programming to solve complex problems in business, medicine, sports management and many other fields. Data Scientists with a strong mathematical foundation are uniquely skilled to lead the development and application of new algorithms to generate data-driven discoveries and insights.
Combining rigorous mathematical foundations with cutting-edge data science techniques, our Mathematical Data Science major empowers students to tackle complex problems and drive innovation forward. Applications close late March.
As we launch our new major in Mathematical Data Science, we're excited to offer students a unique blend of traditional data science skills and mathematical expertise. With a strong foundation in mathematics and statistics, graduates will stand out among their peers as leaders in the field.
By combining rigorous mathematical modeling techniques with cutting-edge statistical processing methods, our program prepares students to take on leadership roles within data science teams. They'll be equipped to tackle complex problems, analyze large datasets, and drive innovation forward.
But that's not all. Our graduates will also develop the ability to think creatively, using their mathematical problem-solving skills to push the boundaries of what's possible in data science. By applying mathematical rigor to data analysis, they'll uncover new insights, identify patterns, and make predictions with unprecedented accuracy.
There are plenty of future careers in data science, but we encourage you to make sure that you verify for yourself. The BS in Mathematical Data Science degree gives you access to many careers, some of which in the list below.
Due to the mathematical background, students should expect to be fully prepared for graduate school in data science, mathematics, or statistics.
Both a computer science major and mathematics major have significant overlap with the Mathematical Data Science major. The addition of a dual major should not add too much to your graduation timeline while making you more competitive for your future careers. However, we strongly suggest talking to an advisor before committing to a dual major.
More information is avalible in the Undergraduate Catalog or by consulting the undergraduate advisor, John Zweibel.
Recent Ph.D graduate Dr. Luis Caicedo Torres’s research is in harnessing the power of scientific machine learning (Sci-ML) tools for modeling physical systems with low amount of data available or in systems with dynamics that are computationally infeasible. By drawing inspiration from classical partial differential equation techniques, he is working on building more robust systems that are able to accurately predict behavior in complex systems. In particular, Caicedo Torres is looking at the application of these ideas to neutron kinetics in subcritical nuclear systems and image recognition for nuclear safety applications. These style of systems are seeing an ever-increasing applicability throughout every area of science.
A student is considered to be "Full-time" if they are enrolled in 15 credits. No semester here fills 15 credit hours. Rather we encourage students to explore the Undergraduate Catalog to find other courses in mathematics, statistics, or computer science, that fit your interests to make this degree unique to you. There are also going to be general requirements which are recommended to be evenly distributed across all four years.
View the flow chart for prerequisites.
It's normal to have questions or concerns when deciding your major. The faculty listed below are interested in helping you succeed in the Mathematical Data Science major at FIU. As the program designers they are fully equipped to address any concerns.
Ciprian G. S. Gal
Professor
305-348-1216
cgal@fiu.edu
DM 436B
Julian Edward
Professor
305-348-3050
edwardj@fiu.edu
DM 431C
John Zweibel
Associate Professor; Mathematics Undergraduate Advisor
305-348-3479
zweibelj@fiu.edu
DM 428
