Welcome to the NEMO group at Arizona State University

Our research lies at the intersection of artificial intelligence, operations research, optimization, and engineering, aiming to develop mathematical models and computational algorithms for intelligent decision-making in large-scale cyber-physical systems. We study how to design AI and engineering systems that are efficient, sustainable, resilient, and trustworthy under uncertainty, with applications spanning AI infrastructure, cloud and edge computing, electric power systems, transportation electrification, healthcare, and smart cities.

Our work combines optimization, machine learning, game theory, economics, control, quantum computing, and secure computation to solve challenging problems involving uncertainty, distributed decision-making, and strategic interactions. A major focus of our recent research is sustainable AI infrastructure, including optimization for large language model (LLM) training and inference, distributed GPU systems, and the interaction between AI data centers and the electric power grid.

Current Research Areas

• Sustainable AI infrastructure and LLM optimization

• Quantum machine learning and optimization

• AI–power grid interaction and electricity markets

• Cloud, edge, and distributed AI systems

• Decision-making under uncertainty and robust optimization

• Multi-agent systems, market design, and mechanism design

• Federated learning and privacy-preserving AI

• Fair resource allocation and trustworthy AI

• EV charging infrastructure and smart energy systems