Projects:
- MediNet: A Complexity Science-Based AI Knowledge Graph for Medicine Pricing, Supply Chain Optimization, and Intelligent Recommendations
Developing an AI-powered knowledge graph integrating complexity science, network science, and game theory to create a self-regulating pharmaceutical market. The system ensures fair pricing, detects cartelization, provides recommendations, and improves accessibility.
Status: Conceptualization and Prototype Development
- The Haunted Graph: A Network Science and Knowledge Graph-Based AI Framework for Gaming
Unlike traditional AI games with fixed behaviors, we are creating a self-evolving AI that dynamically adapts to player actions. This unique approach enables real-time narrative shifts, unpredictable enemy strategies, and an ever-changing horror experience, making each playthrough truly unique.
Status: Conceptualization and Prototype Development
- BloodNodes: AI-Driven Blood Donation Optimization Using Network Science & Knowledge Graphs
Developing a blood donation network to optimize donor-recipient matching, blood supply logistics, and emergency response coordination. The system employs real-time graph analytics and AI-driven decision-making to enhance blood availability forecasting, reduce wastage, and ensure faster, data-driven distribution across healthcare networks.
Status: Conceptualization and Prototype Development
Furthermore, pleas add the following information under this link: https://csfsd.uet.edu.pk/
Information:
Projects:
- NetGuardPro: A Complexity-Driven Cyber Threat Intelligence Framework Using Network Science
Developing a graph-based cybersecurity framework integrating network science, complexity theory, and AI to model corporate networks and predict cyber threats. Developing a multi-layered knowledge graph and an interactive security application for real-time threat alerts, forensic analysis, and network visualization, with applications in enterprise, finance, and critical infrastructure security.
Status: Conceptualization and Prototype Development