Research on the use of mathematical models in epidemiology to explain the spread of infectious diseases and hence advise on public health control.
Dynamical Systems and Chaos Theory: The investigation of chaos theory principles, including its applications in very wide fields such as physics, biology, and economics.
Applications of graph theory in network analysis involve studying the potential for using these tools to analyze and optimize different forms of networks, whether they are social, communication, or transportation networks.
Optimization Operations Research Techniques: The course will cover optimization using linear programming, integer programming, metaheuristics, and other techniques; application to real-life problems.
Cryptography and Information Security: Mathematical techniques have been already developed for providing secrecy and authentication of resources in hostile environments and over open networks. This means focusing on cryptographic algorithms and protocols.
The number theory and its applications include the properties of integer and prime numbers, application of such things as cryptography, and coding theories on such properties.
Mathematical finance and risk management: the application of mathematic models in finance to evaluate risk, price derivatives, and optimally invest portfolios.
Combinatorial Mathematics and Its Applications: This study considers combinatorial techniques and their applications to computer science, biology, and optimization problems.
Partial Differential Equations and Their Applications: Theory and solutions of partial differential equations and applications in physics, engineering, and other sciences.
Topology and Applications: An examination of basic concepts in topology with applications to computer science, biology, and robotics.
Algebraic Geometry and Its Applications: The student will study, organizationally, the aesthetic appeal of the science of geometric properties and structure in the meantime. With particular emphasis on applications to cryptography and theoretical physics.
Neural Systems and Brain Functions in Mathematical Neuroscience: The study and examination of neural systems and brain functions is based on mathematical modeling, as derived from the analysis of neural networks and the dynamics of the brain.
Stochastic Processes and Their Applications: Learn the theory of stochastic processes and its different applications in the fields of finance, biology, and queuing theory.
Principles of Mathematical Logic and Foundational Mathematics: Learn the basic principles of mathematical logic, set theory, and foundational mathematics; understand the subject of formal systems and the theory of proof.
Complex Analysis and Its Applications: A representation of the theory of functions of a complex variable including general theory and its applications to problems in engineering, physics, and applied mathematics.
Fractal Geometry and Its Applications: The study of properties and applications of fractals in nature, art, and diverse scientific disciplines.
Machine Learning Mathematics: Investigate the mathematical basis of machine learning algorithms, with an emphasis on optimization, probability theory, and statistical learning.
Homological Algebra and Its Applications: Discuss both the ideas and methods of homological algebra and applications to the fields of algebraic topology and algebraic geometry.
Study how mathematical techniques are employed, for instance, the use of algorithms for image improvement, compression, and recognition.
Mathematical Biology and Population Dynamics: This sub-discipline is concerned with exploring the different mathematical models of biological systems, their inferential dynamical behaviors, and the population dynamics, including those of predator-prey models and their equally related models.
Quantum Mechanics and Mathematical Physics: Mathematical bases of quantum mechanics and the physical theories and applications that arise from them.
Nonlinear Dynamics and Chaos in Engineering Systems: Study the behavior of nonlinear dynamical systems and the development of chaos in engineering applications.
Mathematical Nature of Climate Models: Examine models and mathematics applied in the predictions and forecasts of climate change.
Functional Analysis and Some of Its Applications: This will include the theory of functional analysis and its applications to problems in solving differential equations, optimization problems, and quantum mechanics.
Mathematics Education and Pedagogy: Research the best practices and methodologies that can help to influence improvement in the teaching and learning of mathematics at all levels.
