Applied Mathematics
Computational Mathematics involves numerical analysis and the development of algorithms to solve mathematical problems efficiently using computers.
Financial Mathematics applies mathematical models to analyze and solve problems in finance, including pricing of securities, risk management, and investment strategy.
Operations Research uses mathematical models to make decisions and solve problems in optimization, logistics, and process management for complex systems.
Mathematical Physics focuses on the development and use of mathematical methods to formulate and solve problems in physics, including theories of the fundamental forces of nature.
Mathematical Biology applies mathematical techniques to model natural and biological processes, from population dynamics to the complexities of cellular pathways.
Mathematical Chemistry uses mathematical approaches to solve chemical problems, including reaction dynamics and molecular modeling.
Control Theory deals with the behavior of dynamical systems and the development of controllers that result in desired changes in output.
Optimization involves finding the best available values of some objective function given a defined domain, including linear, non-linear, and dynamic methods.
Statistics focuses on the collection, analysis, interpretation, and presentation of data, applying probability theory to infer information from sample data.
Mathematical Economics uses mathematical techniques to formulate and solve economic problems, encompassing areas like game theory and economic dynamics.
Actuarial Science applies mathematical and statistical methods to assess risk in the insurance and finance industries, primarily working with uncertainty and time.
Cryptology combines various mathematical disciplines to secure communication in the presence of adversarial behavior and includes cryptography and cryptanalysis.
Mathematical Programming involves creating mathematical models to represent complex decision-making problems as optimization problems.
Numerical Analysis focuses on the design and analysis of algorithms for numerically approximating solutions to mathematical problems.
Systems Theory explores the abstract organization of phenomena, independent of their substance, type, or spatial or temporal scale of existence.
Mathematical Statistics develops the theoretical underpinnings of how statistical methods work, including inference, hypothesis testing, and estimation.