M. Abdullah Canbaz, Ph.D. — AI in Complex Systems

About

Engineering AI for complex systems & society

Dr. M. Abdullah Canbaz is an Assistant Professor in the Department of Information Sciences & Technology and Cybersecurity at the College of Emergency Preparedness, Homeland Security & Cybersecurity (CEHC), University at Albany, SUNY, where he directs the AI in Complex Systems Laboratory. He is an IEEE Senior Member and an inaugural AI & Society Research Fellow.

His research engineers artificial intelligence and machine learning for real-world complex systems — spanning large language models & LegalTech, AI for mental & behavioral health, cybersecurity & cyber deception, crisis response & public safety, and the network science of complex systems. A through-line of his work is grounding modern AI in graph structure, network topology, and responsible, bias-aware design.

He earned his Ph.D. in Computer Science & Engineering from the University of Nevada, Reno (2018; Best Dissertation Award), an M.S. from Indiana University–Purdue University Indianapolis, and a B.S. in Computer Engineering from Fatih University, Istanbul. He previously held faculty appointments at Indiana University Kokomo and UNR.

Research

Areas of focus

The lab builds AI systems that are grounded, trustworthy, and useful in high-stakes settings — connecting machine learning with graphs, networks, and the people these systems serve.

LLMs & LegalTech

Privacy-preserving legal AI, hallucination & citation benchmarks, semantic knowledge graphs, and retrieval-augmented generation for trustworthy legal reasoning.

AI for Mental & Behavioral Health

Human–AI collaboration for empathetic chatbots, graph-based early-warning copilots from therapy narratives, and psychological first-aid assistants.

Cybersecurity & Cyber Deception

LLM-powered honeypots, multi-agent cyber deception, federated learning under adversarial poisoning, and resilient satellite-edge data centers.

Crisis Response & Public Safety

LLM platforms for emergency management, satellite imagery for disaster recovery, and real-time AI for active-threat and firearm detection.

Network Science & Complex Systems

Internet topology mining, co-authorship & advisory networks, quantum network science, and system-dynamics modeling of bias evolution.

Responsible AI & Society

Network-based frameworks for mapping and mitigating AI bias, heuristics in AI decision-making, and AI governance for societal impact.

Publications

Selected & recent work

Peer-reviewed journals, conference proceedings, and book chapters. Filter by type or search by keyword, author, or venue.

No publications match your search.

Legend: Authors in bold indicate Dr. Canbaz. Student co-authors are noted in the full CV (Ph.D. †, undergraduate *). A complete, citable list is also available on request.

Grant Funding

In the classroom & the lab

Courses at University at Albany

Previously taught Data Structures, Data Mining, Computer Networks, Analysis of Algorithms, and Programming I/II at Indiana University Kokomo and the University of Nevada, Reno.

Course Materials

AI in Complex Systems Lab

Ph.D. Researchers

Hakan T. Otal

Malicious traffic detection & synthesis

Tugce Unlu

Information assurance in agentic AI

Mehmet Mikail Demir

AI governance & LegalTech

Mahsa Goodarzi

Bias evolution in recommender systems

Rawan Al Makinah

AI for behavioral health

R. Venkatarakrishnan

Legal knowledge graphs

Master's & Undergraduate

Mariela Santos-Reyes

AI in music generation

JJ Gallucci

AI in 3D world & game generation

Christoph J. Schwartz

Game network fingerprinting

Betul Tok

Bias detection in recommenders

Contact

Get in touch

Open to research collaborations, Ph.D. inquiries, consulting, and speaking. The fastest way to reach me is by email.

Email

mcanbaz@albany.edu

Phone

+1 (518) 442-5258

Office

ETEC, Room 260M · 1220 Washington Avenue · Albany, NY 12226

Department

Information Sciences & Technology · CEHC · University at Albany, SUNY

Profiles

Faculty Page · GitHub

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M. Abdullah Canbaz