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The Research Impact Initiative represents a significant investment in faculty and Ph.D. students in the form of direct support for research in areas of importance for Qatar’s industry. This enterprise represents an exciting new era in which our ability to conduct groundbreaking research is part of a long-term vision with sustainable funding, and it ensures that faculty have the resources and remit to maintain a leading role in advancing technical knowledge for Qatar and the region.

Ph.D. students from Texas A&M will work with an outstanding engineering faculty member who will coordinate research activities of other faculty and supervise teams of Ph.D. and undergraduate students. And this is an important attribute of this initiative — it will generate new knowledge while also increasing human capacity in Qatar by fostering a new generation of scholar-researchers among our engineering students.

  • Chemical Engineering Program — will respond to Qatar’s efforts to mitigate the environmental impact of hydrocarbons through new technologies to reduce emissions while working to accelerate the transition of Qatar’s energy industry to meet the demands of a low- or zero-carbon world.
  • Electrical and Computer Engineering Program — will respond to Qatar’s goals for sustainable energy, advanced health care and robust national security through research and advancement of emerging technologies such as artificial intelligence, machine learning and data analytics.
  • Mechanical Engineering Program — will respond to Qatar’s economic-diversification ambitions to become a global center for smart and sustainable manufacturing. This research will address a range of topics such as advanced materials, additive and hybrid manufacturing, artificial intelligence, energy-efficient technologies, and data-driven modeling and optimization.
  • Petroleum Engineering Program — will respond to Qatar’s aims for global energy leadership by applying data science to maximize the value of Qatar’s upstream and midstream energy sectors. This research will leverage big data and machine learning technologies to improve production efficiency and carbon capture.

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