Konstantinos Fokianos is affiliated with the University of Cyprus in Cyprus and has made numerous contributions in the areas of mathematics and computer science, focusing extensively on statistics and probability as well as artificial intelligence. Their research spans a range of topics including statistical methods and inference, complex systems and time series analysis, financial risk and volatility modeling, Bayesian methods and mixture models, statistical methods and Bayesian inference, time series analysis and forecasting, and COVID-19 epidemiological studies.
Fokianos has published in various venues, with a notable presence in arXiv (Cornell University) where they have contributed eight publications. Additional publication venues include the Journal of Time Series Analysis, the Journal of the Royal Statistical Society Series A (Statistics in Society), the Journal of the American Statistical Association, and the Journal of Multivariate Analysis.
Recent papers associated with Fokianos include:
Frequent co-authors collaborating with Fokianos include Mirko Armillotta, Georgios K. Nikolopoulos, Roland Fried, Maria Ganopoulou, and Lefteris Angelis. These collaborations have resulted in multiple joint publications, particularly with Armillotta.
The main scientific domains of Fokianos' work reflect a blend of rigorous mathematical theory and applied computational techniques, especially within the scope of statistical modeling and time series forecasting. Their research outputs contribute to advancing understanding in quantitative methods applicable to complex data structures and dynamics observed in economics, finance, and epidemiological contexts.
Benjamin Kedem;Konstantinos Fokianos
Unknown
Sofia Wichert;Konstantinos Fokianos;Korbinian Strimmer
Benjamin Kedem;Konstantinos Fokianos
Konstantinos Fokianos;Dag Tjøstheim
Tobias Liboschik;Konstantinos Fokianos;Roland Fried
Vasiliki Christou;Konstantinos Fokianos
Konstantinos Fokianos;Roland Fried
Konstantinos Fokianos;Benjamin Kedem
Konstantinos Fokianos
Konstantinos Fokianos;Benjamin Kedem;Jing Qin;David A Short
Paul Doukhan;Konstantinos Fokianos;Dag Tjøstheim
Richard A. Davis;Konstantinos Fokianos;Scott H. Holan;Harry Joe
Konstantinos Fokianos;Dag Tjøstheim
Konstantinos Fokianos
Konstantinos Fokianos;Roland Fried
Konstantinos Fokianos;Benjamin Kedem
Konstantinos Fokianos;Benjamin Kedem
Konstantinos Fokianos
Konstantinos Fokianos
Konstantinos Fokianos;Bård Støve;Dag Bjarne Tjøstheim;Paul Doukhan
Konstantinos Fokianos
If you think any of the details on this page are incorrect, let us know.
Pursuing a degree in Mathematics opens up a variety of related educational and career opportunities, particularly in data-driven and business-focused fields. For those interested in leveraging their mathematical skills in technology and analytics, exploring the data analytics masters programs can be a strategic choice. These programs focus on interpreting complex data, a skill highly valued across industries.
For students looking to blend quantitative expertise with business acumen, an MBA can be a valuable option. Understanding the easiest mba specialization helps prospective students select programs that match their career goals with manageable admission requirements. Additionally, considering an easy online mba can offer flexibility and accessibility for working professionals aiming to enhance their leadership skills.
For those aspiring to enter higher-level academic or organizational roles, a Doctor of Business Administration (DBA) may be suitable. Researching the cheapest online dba options ensures a quality education without excessive financial burden, supporting career advancement with a focus on applied research and business strategy.
Nankai University
Soochow University
Sabiotec
Michigan State University
University of Manchester
University of Zurich
University of Copenhagen
Tokyo Institute of Technology
Oregon Health & Science University
United Way
Ben-Gurion University of the Negev
University of Cambridge
Southern Federal University
Vanderbilt University Medical Center
University of Copenhagen
Ludwig-Maximilians-Universität München