The AI in Complex Systems Lab
The AI in Complex Systems Laboratory, led by Dr. Canbaz, is at the forefront of advancing artificial intelligence within complex systems and networks.
Lab Mission and Focus
Research Hub
A convergence point for experts in AI, network science, and complex systems.
Specialized Algorithms
Developing AI algorithms and models for analyzing complex networks in various fields.
Innovative Solutions
Tackling intricate challenges and opportunities in AI integration.
About the Director
Dr. M. Abdullah Canbaz, the director of the AI in Complex Systems Lab, is a leading expert in the fields of complex networks, graph data science, and multi-layer data representation and analytics. His research focuses on developing foundational models and algorithms for AI integration at the tactical edge.
For more details please visit[ drcanbaz.com ]
Strategic Projects

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Complex Networks, Internet of Things, Wearables, and Data
Harnessing the interconnectedness of the Internet of Things, Wearables, and the transformative power of Big Data.

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Measurement Studies
Creating novel assessment metrics and monitoring frameworks to quantify the impact of AI integration in complex domains.

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Data Curation
Developing multi-modal data conversion algorithms to harmonize and integrate diverse data sources for advanced analytics.

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Process/Quality Monitoring
Deploying AI-driven quality monitoring systems to optimize production workflows, as demonstrated in the Bayer Pharma partnership.

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Digital Twinning
Combining data entanglement techniques with AI to enable highly accurate digital twins for complex systems and networks.
Strategic Projects
Advancing Legal Intelligence
Transforming the approach to immigration law using AI-powered semantic knowledge graphs.
The AI-Bias Control Framework
Integrating control theory into AI design to address the critical issue of bias in AI systems.
LLM-Assisted Crisis Management
Developing advanced language model platforms to improve emergency response during crises.
Real-World Impact

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Interdisciplinary Collaboration
Fostering interdisciplinary collaborations to address real-world problems and societal challenges.

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Talent Development
Nurturing talent in AI research and contributing to the development of AI-driven solutions for complex systems and networks.

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Efficiency Enhancement
Making our interconnected world smarter and more efficient through innovative AI-driven solutions.
Student Engagement

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Doctoral Candidates
Engaged in advanced research, enriching the lab's cutting-edge projects.

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Undergraduate Students
Enriching their academic studies and laying a foundation for future pursuits.
Team
  • Director, M. Abdullah Canbaz, Ph.D.
  • Postdoc, Emrah Tanyildizi, Ph.D.
  • Ph.D. Student, Radhakrishnan VenkataKrishnan
  • Ph.D. Student, Mahsa Goodarzi
  • Ph.D. Student, Thilanka Munasinghe
  • Ph.D. Student, Hakan Otal
  • Ph.D. Student, Rawan Al Makinah
  • Ph.D. Student, Muhammad Saidur Rahman
  • Undergraduate Student, Betul Tok
  • Undergraduate Student, Kenny Huang
  • Undergraduate Student, Katherine Cajamarca
Knowledge Exchange
Research Agenda
Driving forward the lab's ambitious research agenda.
Lifelong Learning
Fostering a rich learning environment for students and professionals.
Team Collaboration
Promoting a culture of collaboration and knowledge exchange.
Previous Years Achievements

Papers

[PRESENTED] IEEE Conference of Artificial Intelligence 2023, San Francisco, US [PRESENTED] International Conference on Complex Networks and Applications 2023, Riviera, France [ACCEPTED] ACM Web Conference 2024, Singapore [ACCEPTED] IEEE World Forum on Public Safety Technologies 2024, Washington D.C. [ACCEPTED] Intelligent Systems Conference 2024, Amsterdam, Netherlands [PENDING] 3 Papers at IEEE Conference of Artificial Intelligence 2024, Singapore Grants Optical CRISPR Nano-diagnostics Against Common Salmonella Serotypes Using Mobile-App Driven Image Analysis and Data Transmission, United States Department of Agriculture, $611,000.00

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