Research

Research Topics

1. KRR for Trustworthy AI, e.g., 

   • Description Logic and Explanation for Ontology and Knowledge Graph applications

     • Similarity-based Reasoning

   • Argumentation and Explanation for Practical Reasoning

     • Analogical Argumentation

   • Human-friendly Explanation Formalisms

   • Implementation of XAI system, e.g., Virtual Knowledge Graph

2. Integration of KRR and ML for Trustworthy AI, e.g., 

   • Knowledge Graph Embedding (i.e. Knowledge Graph meets ML)

   • Ontology Embedding (i.e. Ontology meets ML)

   • Neural-symbolic Learning (i.e. Symbolic Reasoning meets ML)

   • Argument Mining (i.e. Argumentation meets ML)

   • Fairness, Accountability, and Transparency (FAccT)

   • Knowledge-aware Machine Learning

   • Learning Equivalent Whitebox for Explanation Finding

3. Any topics that use either KRR or ML for building AI systems that humans can trust are also welcome! 

For further details, please visit the following pages:

• Homepage (Teeradaj Racharak)

• Google Scholar (Teeradaj Racharak)

• Received Fundings (Teeradaj Racharak)

• ReaLearns's Projects

• ReaLearn's Publication Records