Using AI to Create More Precise and Personalized Drug Delivery Solutions
With two NIH Awards totaling $2.8 million, Daniel Reker of Duke BME will design machine learning models to improve the development of more effective drug delivery tools.
Data Science, Advanced Computing & Intelligent Systems
Duke Engineering researchers are developing and deploying the power of computing to design autonomous systems, improve communications, glean useful insights from masses of data, detect disease and improve health, and enhance security in our world and cyberspace.
Major Centers and Initiatives
AI and Machine Learning
- AI/Machine Learning Group—Department of Electrical & Computer Engineering
- Computation & AI Group—Thomas Lord Department of Mechanical Engineering & Materials Science
- NSF AI Institute for Edge Computing Leveraging Next-Generation Networks (Athena)
Big Data & Data Analytics
Quantum Computing
- Duke Quantum Center
- Quantum Computing Group
- Error-corrected Universal Reconfigurable Ion-trap Quantum Archetype (Euriqa)
- Spectator Qubit Multidisciplinary University Research Initiative (MURI)
- Software-Tailored Architecture for Quantum (STAQ)
Computer Systems & Architecture
- NSF AI Institute for Edge Computing Leveraging Next-Generation Networks (Athena)
- Center for Alternative Sustainable and Intelligent Computing (ASIC)
Information Processing
- Autonomous Systems Group
- Duke Robotics
- Applied Computational Ion Spectrometry Center (CAMMS-ES)
- X-Ray Diffraction Scanner
Computational Design
- Computational Design Groups:
- Center for Autonomous Materials Design
- Computational Modeling of Biological Systems Group
- Aerodynamics & Aeroelasticity Group
- Sensing & Imaging Group
- GUIde Consortium for Aeroelasticity
Trustworthy Computing
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