Farrukh Saleem is an expert in which study of mathematical models of conflict and cooperation between intelligent rational decision-makers?
Game theory
Game theory
Game theory is "the study of mathematical models of conflict and cooperation between intelligent rational decision-makers".
 Game theory is mainly used in economics, political science, and psychology, as well as logic, computer science and biology.
 Originally, it addressed zero-sum games, in which one person's gains result in losses for the other participants.
 Today, game theory applies to a wide range of behavioral relations, and is now an umbrella term for the science of logical decision making in humans, animals, and computers.
Farrukh Saleem
Farrukh Saleem (Urdu: فاروخ سليم; PhD), is a Pakistani political scientist, game and economic theorist, financial analyst writer, and television personality.
 Currently working on specialising the discipline of finance and education, he has extensively published articles on geopolitics, economic competition, and education reforms in Pakistan, and the world.
 Currently, he is leading the research project on politics and education at the Center for Research and Security Studies (CRSS).
Applied mathematics
Applied mathematics is a branch of mathematics that deals with mathematical methods that find use in science, engineering, business, computer science, and industry.
 Thus, applied mathematics is a combination of mathematical science and specialized knowledge.
 The term "applied mathematics" also describes the professional specialty in which mathematicians work on practical problems by formulating and studying mathematical models.
 In the past, practical applications have motivated the development of mathematical theories, which then became the subject of study in pure mathematics where abstract concepts are studied for their own sake.
 The activity of applied mathematics is thus intimately connected with research in pure mathematics. Moment measure
In probability and statistics, a moment measure is a mathematical quantity, function or, more precisely, measure that is defined in relation to mathematical objects known as point processes, which are types of stochastic processes often used as mathematical models of physical phenomena representable as randomly positioned points in time, space or both.
 Moment measures generalize the idea of (raw) moments of random variables, hence arise often in the study of point processes and related fields. Mathematical and theoretical biology
Mathematical and theoretical biology is an interdisciplinary scientific research field with a range of applications.
 The field is sometimes called mathematical biology or biomathematics to stress the mathematical side, or theoretical biology to stress the biological side.
 Theoretical biology focuses more on the development of theoretical principles for biology while mathematical biology focuses on the use of mathematical tools to study biological systems, even though the two terms are sometimes interchanged.
 Mathematical biology aims at the mathematical representation, treatment and modeling of biological processes, using techniques and tools of applied mathematics.
 It has both theoretical and practical applications in biological, biomedical and biotechnology research.
 Describing systems in a quantitative manner means their behavior can be better simulated, and hence properties can be predicted that might not be evident to the experimenter.
 This requires precise mathematical models. Viral dynamics
Viral dynamics is a field of applied mathematics concerned with describing the progression of viral infections within a host organism.
 It employs a family of mathematical models that describe changes over time in the populations of cells targeted by the virus and the viral load.
 These equations may also track competition between different viral strains and the influence of immune responses.
 The original viral dynamics models were inspired by compartmental epidemic models (e.g. the SI model), with which they continue to share many common mathematical features, such as the concept of the basic reproductive ratio ("R").
 The major distinction between these fields is in the scale at which the models operate: while epidemiological models track the spread of infection between individuals within a population (i.e. "between host"), viral dynamics models track the spread of infection between cells within an individual (i.e. "within host").
 Analyses employing viral dynamic models have been used extensively to study HIV, hepatitis B virus, and hepatitis C virus, among other infections Super-recursive algorithm
In computability theory, super-recursive algorithms are a generalization of ordinary algorithms that are more powerful, that is, compute more than Turing machines.
 The term was introduced by Mark Burgin, whose book "Super-recursive algorithms" develops their theory and presents several mathematical models.
 Turing machines and other mathematical models of conventional algorithms allow researchers to find properties of recursive algorithms and their computations.
 In a similar way, mathematical models of super-recursive algorithms, such as inductive Turing machines, allow researchers to find properties of super-recursive algorithms and their computations. Mathematical model
A mathematical model is a description of a system using mathematical concepts and language.
 The process of developing a mathematical model is termed mathematical modeling.
 Mathematical models are used in the natural sciences (such as physics, biology, Earth science, meteorology) and engineering disciplines (such as computer science, artificial intelligence), as well as in the social sciences (such as economics, psychology, sociology, political science).
 Physicists, engineers, statisticians, operations research analysts, and economists use mathematical models most extensively .
 A model may help to explain a system and to study the effects of different components, and to make predictions about behaviour. Rational expectations
In economics, "rational expectations" are model-consistent expectations, in that agents inside the model are assumed to "know the model" and on average take the model's predictions as valid.
 Rational expectations ensure internal consistency in models involving uncertainty.
 To obtain consistency within a model, the predictions of future values of economically relevant variables from the model are assumed to be the same as that of the decision-makers in the model, given their information set, the nature of the random processes involved, and model structure.
 The rational expectations assumption is used especially in many contemporary macroeconomic models. Point process operation
In probability and statistics, a point process operation or point process transformation is a type of mathematical operation performed on a random object known as a point process, which are often used as mathematical models of phenomena that can be represented as points randomly located in space.
 These operations can be purely random, deterministic or both, and are used to construct new point processes, which can be then also used as mathematical models.
 The operations may include removing or "thinning" points from a point process, combining or "superimposing" multiple point processes into one point process or transforming the underlying space of the point process into another space.
 Point process operations and the resulting point processes are used in the theory of point processes and related fields such as stochastic geometry and spatial statistics.