Crina Grosan

 

Title: Machine Learning and Optimisation for Real-World Problems

CV:
Crina Grosan is a Senior Lecturer in the Department of Computer Science at Brunel University. Prior to joining Brunel, She was an academic staff member at Babes-Bolyai University Cluj-Napoca, one of the top universities in Romania. Her research interests span the areas of machine learning, optimisation, and multi-relational graphs. They include both theoretical and algorithmic development as well as applications for particular classes of problems such as classification, clustering, prediction, estimation, decision-making, pattern finding, data mining, very large systems of nonlinear equations and large-scale optimisation.

 

 

Duygu Icen

Title: Big Data Concept for Statisticians


 

Fatih Cemrek

Title: Structural Breaks in Time Series Analysis and An Application

CV:
Fatih Çemrek was born in Konya in 1977. He graduated from Arts and Science Faculty of Osmangazi University in 1998. From this time to 2001, he attended Master’s program in Institutes of Science of Osmangazi University and graduated from PhD program of Institutes of Science of Eskişehir Osmangazi University in 2006. To date from 1999, he is working as a faculty member of Applied Statistics in Arts and Science Faculty of Eskişehir Osmangazi University. He is interested in studies of Time Series Analysis, Econometric Time Series Analysis, Multivariate Statistical Analysis, and Applied Statistics.  He became an assistant professor in 2008 and became an associate professor in 2015. He is married and has one girl and one boy.

 

Mu-Yen Chen

Title: Applying Deep Learning to Forecast the Results of Sports Events

CV:
Dr Chen is a Professor of Information Management at National Taichung University of Science and Technology, Taiwan. He received his PhD from Information Management from National Chiao-Tung University in Taiwan. His current research interests include artificial intelligence, soft computing, bio-inspired computing, data mining, deep learning, context-awareness, machine learning, and financial engineering, with more than 100 publications in these areas. He has co-edited 12 special issues in International Journals (e.g. Computers in Human Behavior, Applied Soft Computing, Soft Computing, Information Fusion, Neurocomputing, Journal of Medical and Biological Engineering, The Electronic Library, Library High Tech). He has served as Editor in Chief and Associate Editor of international journals [e.g. International Journal of Big Data and Analytics in Healthcare, IEEE Access, Journal of Information Processing Systems, International Journal of Social and Humanistic Computing] while he is an editorial board member on several SCI journals.

 

Tahir Ekin

Title: Statistical Methods for Health Care Fraud

CV:
Tahir Ekin is the Brandon Dee Roberts Associate Professor of Quantitative Methods in McCoy College of Business, Texas State University. His areas of expertise include statistical applications in medical fraud assessment and simulation-based stochastic optimization. His previous work experience includes a stint as a statistician at Integrated Management Services (IMS), working on health care fraud detection. He has a forthcoming book on the use of statistical methods for health care fraud assessment as part of the ASA/CRC Series on Statistical Reasoning in Science and Society. His scholar work on health care fraud has been published in a variety of academic journals including International Statistical Review, The American Statistician and Applied Stochastic Models in Business and Industry. His work has been presented in various conferences sponsored by ISI, ISBIS, ISBA and INFORMS; and has been the recipient of Texas State University 2018 Presidential Distinction Award in Scholar Activities, and ASA/NISS y-Bis 2016 Best Paper Award among others. He has developed and taught courses in the areas of business statistics, optimization, data mining and analytics. Dr Ekin also currently serves as ISBIS Vice President of responsible of Y-Bis.