School of Electrical Engineering and Computer Science
|Educations||Research Interests||Publications||Presentations||Academic Experiences||Curriculum Vitae (PDF)|
My research interests lie mainly in the following areas:
E. Nazerfard and D. Cook, Using Bayesian Networks for Daily Activity Prediction, AAAI Workshop on Plan, Activity and Intention Recognition (PAIR), Technical Report, 2013.
E. Nazerfard and D. Cook, Bayesian Networks Structure Learning for Activity Prediction in Smart Homes, Proceedings of the International Conference on Intelligent Environments (IE), pp. 50-56, 2012.
E. Nazerfard, P. Rashidi, and D. Cook, Using Association Rule Mining to Discover Temporal Relations of Daily Activities, Proceedings of the International Conference on Smart Homes and Health Telematics (ICOST), pp. 49-56, 2011.
E. Nazerfard, P. Rashidi, and D. Cook, Discovering Temporal Features and Relations of Activity Patterns, Proceedings of the ICDM Workshop on Data Mining for Service, pp. 1069-1075, 2010.
E. Nazerfard, B. Das, L. Holder, and D. Cook, Conditional Random Fields for Activity Recognition in Smart Environments, Proceedings of the ACM International Conference on Health Informatics (SIGHIT), pp. 282-286, 2010.
E. Nazerfard, V. Hakami, and S. Bagheri, Evolutionary GMDH-based Identification of Building Blocks for Binary-Coded Systems, Proceedings of the IEEE International Conference on Information Communication Technologies: from Theory to Application (ICTTA), pp. 1900-1904, 2006.
E. Nazerfard and S. Bagheri, RGEA: A novel Evolutionary Algorithm based on GMDH Neural Networks and Rule Extractions, Proceedings of the International CSI Conference (CSICC), pp. 520-527, 2006.
The followings are my selected recent (well, almost!) presentations:
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Last update: April 2013