Iffat is a Lecturer in Big Data Analytics. Her main research interests involve artificial intelligence, pattern recognition, optimization, algorithm design, and cyber security. In particularIy am interested in developing intelligent algorithms for applications in food security and medicine.
Iffat’s main area of expertise include:
- Neurocomputing
- Evolutionary Computing and Multiobjective Programming
- Signal Processing
- Computational Statistics
PhD in Computing Science (Stirling University, 2010)
MSc in Information Technology –with distinction for project (Stirling University, 2006)
MSc in Information Systems Management (Stirling University, 2005)
MS in Marketing—First Class (Bangladesh Agricultural University, 2002)
BSc in Agricultural Economics—First Class Honors (Bangladesh Agricultural University, 2000).
Courses Dr Gheyas teaches on:
- MSc in Business Intelligence
- BSc in Computer Science
- BSc in Business Information Technology
This includes:
# CMP7079 (PG) Data Mining, MSc in Business Intelligence (Module Leader), School of Computing and Digital Technology, Birmingham City University.
# CMP7082 (PG) Data Analysis, MSc in Business Intelligence (Module Leader), School of Computing and Digital Technology, Birmingham City University.
Diana Haider,PhD project, May 2015– present,Big Data Analytics for Supporting Risk Mitigation Decisions
Journal Publications
- Baldwin, A., Gheyas, I., Ioannidis, C., Pym, D., and Williams, J. Contagion in Cybersecurity Attacks. Accepted for publication: Journal of the Operational Research Society, 2016.
- Gheyas, I., and Abdallah, A.E. Detection and Prediction of Insider Threats to Cyber Security: A Systematic Literature Review and Meta-Analysis. Accepted for publication: Big Data Analytics, 2016 (Invited Paper).
- Gheyas, I.A., and Smith, L.S. (2011). A Novel Neural Network Ensemble Architecture for Time Series Forecasting. Neurocomputing, 74(18), pp. 3855-3864 (Cited by 32).
- Gheyas, I.A., and Smith, L.S. (2010). Feature Subset Selection in Large Dimensionality Domains. Pattern Recognition, 43(1), pp. 5-13 (Cited by 251: One of the most cited articles published since 2010, extracted from Scopus).
- Gheyas, I.A., and Smith, L.S. (2010). A Neural Network-based Framework for the Reconstruction of Incomplete Data Sets. Neurocomputing, 73(16-18), pp. 3039-3065 (Cited by 31).
Book Chapters
Gheyas, I.A., & Smith, L.S. (2009). ‘Reconstruction of Cross-sectional Missing Data using Neural Networks’. In Dominic Palmer-Brown et al (Eds.), Engineering Applications of Neural Networks, Communications in Computer and Information Science (CCIS), vol. 43, Springer Berlin Heidelberg, pp. 28-34.
International Refereed Conference Papers
- Ioannidis, C., Pym, D., Williams, J., and Gheyas, I. (2014). Resilience in Information Stewardship. In: 13th Annual Workshop on the Economics of Information Security (WEIS 2014), Penn State University, 23-24, June Pennsylvania (Cited by 2).
- Baldwin, A., Gheyas, I., Ioannidis, C., Pym, D., & Williams, J. (2012). Contagion in Cybersecurity Attacks. In: 11th Annual Workshop on the Economics of Information Security, Berlin, Germany, 25/06/12-26/06/12 (Cited by 2).
- Gheyas, I.A., and Smith, L.S. (2009). A Neural Network Approach to Time Series Forecasting. Paper published in Proceedings of the World Congress on Engineering 2009, vol. II, WCE 2009, July 1-3, London, UK (Cited by 40).
- Gheyas, I.A., and Smith, L.S. (2009). A Novel Nonparametric Multiple Imputation Algorithm for Estimating Missing Data. Paper published in the Proceedings of World Congress on Engineering, 2009 Vol. II, WCE 2009, July 1-3, London, UK (cited by 2).
Presentations
- Gheyas, I.A., & Williams, J.M. (2013). Forecasting Short-Term Stock Price Movements using Evolutionary Algorithms and Neural Networks. Paper presented at the 20th Forecasting Financial Market 2013, Hannover, Germany.
- Gheyas, I. A. (2012). Dynamic Modelling of Cyber Attacks. Invited Presentation. School of Natural & Computing Sciences at the University of Aberdeen.
- Gheyas, I. A., & Smith, L.S. (2009). ‘Reconstruction of Cross-sectional Missing Data using Neural Networks’. Paper presented at the 11th International Conference on Engineering Applications of Neural Networks, EANN 2009, London, UK, August 27-29, 2009.
- Gheyas, I. A., & Smith, L.S. (2009). A neural network approach to time series forecasting. Paper presented at the World Congress on Engineering 2009, vol. II, WCE 2009, July 1-3, London, UK.
- Gheyas, I. A., & Smith, L.S. (2009). A novel nonparametric Multiple Imputation Algorithm for Estimating Missing Data. Paper presented at the World Congress on Engineering 2009 Vol. II, WCE 2009, July 1-3, London, UK.
Theses and Technical Reports
- Gheyas, I.A., Hallas, B., & Williams, J. (2011). Cloud Computing and SME’s in UK. A CSE project report, November 2011.
- Gheyas, I. A. (2009).Novel Computationally Intelligent Machine Learning Algorithm for Data Mining and Knowledge Discovery. PhD thesis, University of Stirling.
- Gheyas, I. A. (2005). A Decision Support Tool for Disease Diagnosis. MSc thesis, University of Stirling.
- Gheyas, I. A. (2004). Managing Information Systems in the University Libraries: A case study of the Stirling University Library. MSc thesis, University of Stirling.
- Gheyas, I.A., & Sabur, S.A. (2003). Household Consumption Pattern and Buying Behaviour for Fish in Area of Mymensingh, Bangladesh. Bangladesh Journal of Fisheries, 7(2), 185-196.
- Gheyas, I.A., & Sabur, S.A. (2002). Effects of Various Stimuli on Consumer Behaviour for Food Commodities in an Area of Mymensingh District, Bangladesh. Bangladesh Journal of Agricultural Economics. 26(2), 63-84.
- Gheyas, I. A. (2002).A Study on Consumer Behaviour towards Food Commodities of the residents of Agrivarsity and Adjoining Areas Under Mymensingh Sadar Upazila. M.S. thesis, Bangladesh Agricultural University.
Editorial Board Member
The Big Data Analytics Journal (http://bdataanalytics.biomedcentral.com/)
ISSN: 2058-6345
Conference Committees
Member of the Technical Program Committee for 2015 IEEE Symposium on Computational Intelligence in Healthcare and e-health.