Doctor of Philosophy in Ontological Engineering

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Doctor of Philosophy in Ontological Engineering

The Doctor of Philosophy in Ontological Engineering is a research-intensive program dedicated to the study of formal knowledge structures, AI-driven ontologies, and advanced computational reasoning. This program is designed for scholars and researchers seeking to develop cutting-edge intelligent reasoning and data structuring systems through semantic web technologies, AI-based knowledge graphs, and machine learning-driven ontology development.

About the Program

The Ph.D. in Ontological Engineering provides an advanced framework for investigating and constructing sophisticated knowledge representation models that power artificial intelligence, automation, and data-driven decision-making. Students will explore the intersection of ontology, computational logic, and AI-driven data architecture to design scalable and efficient intelligent systems. Through rigorous coursework, independent research, and applied projects, students will engage in the development of AI-based knowledge graphs, ontological modeling techniques, and semantic reasoning frameworks. This program emphasizes the integration of formal ontology with machine learning, enabling graduates to contribute to the advancement of intelligent automation, natural language processing, and structured data systems.

Key Areas of Study

  • **Formal Knowledge Structures and Computational Logic
  • **AI-Driven Ontologies and Semantic Web Technologies
  • **Machine Learning for Ontological Modeling
  • **Knowledge Graphs and Automated Reasoning Systems

Career Pathways

Graduates of the Ph.D. in Ontological Engineering are well-prepared for careers in knowledge engineering, AI-driven data architecture, computational logic, and advanced ontological modeling. They will be equipped for leadership roles in AI research, enterprise knowledge management, intelligent systems development, and cutting-edge technological innovation.

Core Curriculum & Research Structure

Doctoral Degree Requirements:

Total Credits Required: 75 credits

Core Major Courses: 39 credits

Doctoral Research Seminars: 9 credits

Research & Dissertation: 27 credits

Falll Semester 1

ONE 801 – Advanced Ontological Engineering & Knowledge Representation (3 credits)

ONE 802 – Formal Semantics & Logical Structures in AI (3 credits)

ONE 803 – Knowledge Graphs, Semantic Networks & Reasoning (3 credits)

ONE 804 – Ontology-Based Decision Systems & AI Learning (3 credits)

Doctoral Research Seminar I: AI-Driven Ontology Research (3 credits)

Spring Semester 2

ONE 805 – Computational Ontology in Robotics & Automation (3 credits)

ONE 806 – AI Ethics & Ontology-Driven Decision Support Systems (3 credits)

ONE 807 – Knowledge Representation for AI & Machine Learning (3 credits)

ONE 808 – Large-Scale Ontology Evolution & AI Optimization (3 credits)

Doctoral Research Seminar II: Proposal Development & Review (3 credits)

Falll Semester 3

ONE 901 – Intelligent Agents & Ontology-Based AI Models (3 credits)

ONE 902 – Ontology-Based Neural Networks & Cognitive AI (3 credits)

ONE 903 – The Future of Ontological Engineering in AI & Industry (3 credits)

Independent Research in AI & Ontological Engineering (3 credits)

Doctoral Research Seminar III: Advanced Dissertation Research (3 credits)

Spring Semester 4

ONE 904 – AI Reasoning Systems & Ontological Inference (3 credits)

ONE 905 – Advanced Logical Frameworks for Knowledge Representation (3 credits)

Comprehensive Doctoral Examination (Non-Credit)

Doctoral Dissertation Proposal Defense (Non-Credit)

Falll Semester 5

ONE 990 – Doctoral Dissertation Research (9 credits)

ONE 991 – Experimental AI & Ontology-Based Cognitive Systems (3 credits)

Spring Semester 6

ONE 992 – Dissertation Completion & Pre-Defense Review (9 credits)

ONE 993 – Final Dissertation Defense & Publication (3 credits)