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Computational and Data Sciences
- Large-scale mixed-integer linear, nonlinear and bilevel programming
- Deep learning, machine learning, and predictive analytics
- Quantum computing for optimization and machine learning
- Learning-based and model-based control and automation
- Data-driven decision making under uncertainty
- Grey-box digital twins and hybrid analytics
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Process, Energy and Environmental Systems Engineering (PEESE)
- Decarbonization, carbon-neutrality, and sustainable design of energy systems
- Life cycle energy, environmental, and economic systems analytics
- Material informatics and computer-aided molecular design
- Digital agriculture, smart energy and circular economy
- Industrial big data analytics and Internet of things
- Supply chain optimization and smart logistics
See Collaborating for Sustainability featuring our research in artificial intelligence, energy systems, circular economy, sensors, and quantum computing.
Recent stories (past two years) by Cornell Chronicle on our research:
- Sep 2021: Quantum computing and AI for smart power systems
- Sep 2021: Future plastics waste chemical recycling systems
- Jun 2021: Recycling of photovoltaic solar cells for sustainability
- Apr 2021: Sustainable campus energy systems
- Dec 2020: New York State’s 100% renewable energy transition planning
- Oct 2020: AI and machine learning for capturing and converting microplastics
- Jul 2020: Sustainability of tandem perovskite solar cells
- Apr 2020: COVID-19 Dashboard for New York State
- Jul 2019: AI for smart irrigation systems in agricultural water management
- Jun 2019: Carbon-neutral energy systems using Cornell campus as a living laboratory
- Feb 2019: Artificial intelligence (AI) for smart building energy control
Additional details about our research on AI for Smart Control and Automation, Quantum Computing, and Sustainable PV Energy Materials, as well as various journal covers, are in the News section. There is also a feature story on Energy Systems Engineering.