Research Interests:

Machine Learning, Data Mining, Algorithm, Cybersecurity, Software Engineering, and High Performance Computing (HPC). I have specific interests in design and development of Machine Learning and Data Mining algorithm toward transformational research on Big Data analytics and translate that to viable software/application. My methodological, computational, and collaborative works address spatiotemporal Big Data problems and challenges through adaptive computing with efficient-, predictive-, and meta-analytics. I am also interested in high performance Cloud Computing and cybersecurity surveillance research.

Selected Publications:

• Begum, F., Sharker, M. H., Sherman, S. L., Tseng, G. C., & Feingold, E. Regionally Smoothed Meta‐Analysis Methods for GWAS Datasets. Genetic epidemiology, 40(2), 154-160 (2016).
• Bhushan, A., Sharker, M. H., & Karimi, H. A. Incremental Principal Component Analysis Based Outlier Detection Methods for Spatiotemporal Data Streams. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2(4), 67 (2015).
• Sharker, M. and Karimi, H. A. Computing Least Air Pollution Exposure Routes. International Journal of Geographical information Science. Vol. 28, No. 2, pp. 343-362 (2014).
• Sharker, M., Karimi, H. and Zgibor, J. Health-Optimal Routing In Pedestrian Navigation Services. ACM SIGSPATIAL HealthGIS'12. Redondo Beach, CA, November 6 (2012). [Best Paper Award].
• Sharker, Monir H., Karimi, Hassan A. Algorithm for Energy-Efficient and Automatic Configuration of Pedestrian Navigation Services: Smartphones on Clouds. 1st International Conference on Smart Grids and Green IT Systems (SMARTGREENS 2012). Porto, Portugal, April 18-20 (2012).
• Karimi, H. A., Sharker, M. H., and Roongpiboonsopit, D. Geocoding recommender: an algorithm to recommend optimal online geocoding services for applications. Transactions in GIS, Vol. 15, No. 6, pp. 869-886 (2011).