Machine Learning & AI
At the forefront of technological innovation, Machine Learning involves crafting algorithms for autonomous learning, while AI simulates human intelligence. Integrating multi-agent systems and game theory enhances decision-making in complex environments, finding applications in finance, cybersecurity, and resource management.
Privacy-protected AI Methods for Restricted Surveillance of Mobile Communications
Duan Lingjie (2023)
Dynamic Crowdsourcing Mechanisms for Decarbonising Urban Passenger Transportation and Package Delivery
Duan Lingjie (2023)
Fast Learning And Channel Hopping For Anti-Jamming Defense
Duan Lingjie (2023)
GPU-Accelerated Algorithms for Multi-Sensor Data Association for Multi-Target Tracking.
Nagi Rakesh (2023)
Hybrid AI/ML-Optimization Approaches to Cloud Native Workflow Scheduling,” IBM-Illinois Discovery Accelerator Institute
Nagi Rakesh (2023)
Mitigating the Harm of Fentanyl through Holistic Demand/Supply-Chain Interventions and Equitable Resource Allocations,” National Science Foundation (USA)
Nagi Rakesh (2023)
Building Proposal Development Evaluation with Artificial Intelligence
Varvitsiotis Antonios (2022)
Towards Co-clustering in Big Data: An optimization perspective
Lin Meixia (2022)
Computer Science Approaches to Quantum Computing for Finance
Varvitsiotis Antonios (2022)
To Motivate Human-in-the-loop Learning of Complex Traffic Networks
Duan Lingjie (2022)