Stochastic Processes and Their Applications: In Honor of Prof. Sally McClean
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Probability and Statistics".
Deadline for manuscript submissions: 15 November 2024 | Viewed by 14254
Special Issue Editors
Interests: probability; stochastic processes; stochastic modeling; applied probability; financial mathematics; stochastic analysis; mathematical finance; Markov chains; Markov processes; option pricing
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Interests: Markovian processes; stochastic modeling; manpower planning; multiple objective optimization; simulation; performance evaluation; business analytics
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Special Issue Information
Dear Colleagues,
The Journal of Mathematics is publishing a Special Issue under the above title to honor Prof. Sally McClean in the occasion of her semi-retirement and in recognition of her important contributions in research.
Sally Ida McClean was born in Belfast and took her first degree, an M.A. in mathematics, from the University of Oxford in 1970. She earned an M.Sc. in Mathematical Statistics and Operations Research from Cardiff University in 1972, and completed her Ph.D. in 1976 at the Ulster University at Coleraine. Her contribution to mathematical modeling in health care planning is huge, and, in particular, her studies for improving the wellbeing of the elderly is greatly respected amongst her peers. She is currently Professor of Mathematics at Ulster University. Her main research interests are in Stochastic Modelling and Optimization for Healthcare Planning and Computer Science, and, more specifically, in Databases, Internet of Things, Sensor Technology, and Telecommunications. She has published more than 300 papers on the subjects, with an impressive record of citations. Prof. McClean is a recipient of Ulster University's Senior Distinguished Research Fellowship.
Stochastic processes are probably the most important tool in many areas of science, such as biology, operational research, social sciences, stochastic finance, and others. Important characteristics in these areas evolve with time in a more or less a random way, and since stochastic processes are mainly sequences or families of random variables, in which their index represents time, they are the natural tool to use. The theory and applications of stochastic processes emerged in the genesis of one of the richest one, that is, the Brownian motion. That was rather unexpected since Brownian motion is a beautiful object which is at the same time a martingale, a Gaussian process, a diffusion, a Levy process, a Markov process, etc.; concepts that were discovered quite latter in the evolution of time. We cordially invite researchers and colleagues to submit their papers following the journal’s guidelines and the topics of interest listed below.
Prof. Dr. Panagiotis-Christos Vassiliou
Prof. Dr. Andreas C. Georgiou
Guest Editors
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Keywords
- anomaly detection and Markov processes
- applications of artificial intelligence in medical diagnosis processes
- business processes and Markov chains
- conditional phase-type distributions
- discrete q-distributions
- epidemic models
- hidden Markov chains and applications
- inference in Markov, semi-Markov and diffusion processes
- machine learning lingo for a stochastic environment
- Markov and semi-Markov chains and processes,
- Markov chains in computing science
- Markov decision processes and Markov processes in reinforcement learning
- Markov models and applications in biology, epidemiology and healthcare
- Markov models and efficiency evaluation
- Markov Populations
- Markov renewal processes
- Markovian Arrival Processes (MAP)
- martingales
- mathematical finance
- matrix analysis
- migration process in credit risk
- modeling and applications in supervised and unsupervised machine learning
- nonhomogeneous Markov and semi-Markov systems
- optimization techniques and efficiency evaluation
- perturbation and sensitivity analysis in Markov processes
- phase type survival trees
- point process
- process mining techniques
- queuing networks and Markov chains
- random walks
- reversible Markov chains
- stochastic analysis
- stochastic biological models
- stochastic environments
- stochastic processes in finance and social sciences
- stochastic stability and asymptotic analysis
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