Data Analytics and Artificial Intelligence

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Artificial Intelligence (AI) is an ability to design smart machines or to develop self-learning software applications that imitate the traits of the human mind like reasoning, problem-solving, planning, optimal decision making, sensory perceptions etc. The capacity of artificial intelligent approaches to outperform human actions in terms of knowledge discovery gained the attention of business and research communities all over the world and this field of study witnessed rapid progress in the past two decades. The Operations Research wing of the Industrial Engineering faculty are able to bring to bear their predisposition towards data and data science in getting on the forefront of this burgeoning field. With four members of the faculty currently developing and applying Operations Research and optimization tools there is a readiness to contribute significantly to the Data Analytics and AI cluster.

Current ISE Focus

Current ISE faculty focus is on developing advanced analytical and data mining models that can be used to transform large-scale datasets into actionable insights and decision-making intelligence in real time. Specifically, some members of the ISE faculty are involved in the areas of Data-driven analytics and Modeling, and Optimization, Sensor-based Process Monitoring and Control, Network Theory and Information Science, and Machine Learning and Artificial Intelligent Optimization. Currently, there’s only one faculty member with AI and ML research expertise (Dr. Chen), and three others with a background that would support this ISE Cluster of Data Analytics and AI.

Opportunities for Interdisciplinary Collaboration:

Joining the ISE Department this fall is Dr. Chen who has already explored the use of AI in healthcare. An awareness of how AI-powered solutions can transform health care, with opportunities including disease diagnosis and monitoring, clinical workflow augmentation, and hospital optimization represents a tremendous opportunity for interdisciplinary collaboration. Dr. Chen and Dr. Moghaddass can serve as a strong anchor for Data Analytics & AI cluster. Such opportunities extend to the development of insights into the various AI-based techniques impacting and improving upon traditional health care structures, including natural language processing, data analytics, and machine learning.

CoE Thrust Supported: Data Science

Graduate Courses Offered: IEN 716 Introduction to Applied Data Analytics

Number of Ph.D. Students and Research Personnel: 15       

Faculty Participants

Coordinator: Ramin Moghaddass

ISE Members: Cheng-Bang Chen

Other Department & School Participants: TBA