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Zina Ben Miled

Dr. Zina Ben Miled

Indiana University Purdue University Indianapolis

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Zina Ben Miled, Ph.D. (associate professor, Dept. of Electrical and Computer Engineering): Her research interests include machine learning, complex system modeling and large-scale service-oriented software architectures. She developed and designed machine learning models to support drug discovery, and more recently to predict medication adherence, understand the geographical distribution of the incidence of chronic diseases and to predict the onset of dementia. Other application areas include the estimation of daily and monthly water demands for utilities, the modeling of fuel consumption in heavy duty vehicles and the prediction of distribution delays in supply chain networks. These applications motivated the novel design and adaptation of machine learning techniques, including differential learning neural networks, transfer learning and clustering methodologies. She is a senior member of IEEE, the recipient of the Indiana Women in High Tech Award and the National Science Foundation Career Award.

Research Keywords & Expertise

Complex Systems
Information System
Knowledge Discovery
machine learning
High Performance Compu...

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Information System

Short Biography

Zina Ben Miled, Ph.D. (associate professor, Dept. of Electrical and Computer Engineering): Her research interests include machine learning, complex system modeling and large-scale service-oriented software architectures. She developed and designed machine learning models to support drug discovery, and more recently to predict medication adherence, understand the geographical distribution of the incidence of chronic diseases and to predict the onset of dementia. Other application areas include the estimation of daily and monthly water demands for utilities, the modeling of fuel consumption in heavy duty vehicles and the prediction of distribution delays in supply chain networks. These applications motivated the novel design and adaptation of machine learning techniques, including differential learning neural networks, transfer learning and clustering methodologies. She is a senior member of IEEE, the recipient of the Indiana Women in High Tech Award and the National Science Foundation Career Award.