Our research focuses on developing and employing new tools and techniques in artificial intelligence, operations research, optimization, and game theory to address various challenging and exciting engineering problems in emerging areas such as cloud/edge computing, network virtualization, sustainable computing, crowdsourcing, intelligent transportation, smart healthcare/grids/cities, renewable energy integration, and online marketplaces.
Current research directions:
Decision-making under uncertainty (robust, stochastic, online optimization and learning)
Quantum-assisted optimization and learning
Multi-agent resource allocation, fair allocation, fairness-aware algorithms
Market design, market-based mechanisms, dynamic pricing, and network economics
Privacy-preserving distributed optimization and learning
Electric vehicle charging network design and operations
Cloud/edge computing