Polykarpos Meladianos

Prior to joining MBZUAI, Professor Meladianos led the development of real-world AI systems, including LLM-based chatbots, retrieval-augmented generation pipelines, and fraud detection tools. His current work focuses on agentic architectures, scalable knowledge infrastructures, and real-time AI assistants. Professor Meladianos is an AI/NLP Engineer with deep industry experience in applied machine learning and natural language processing, having led chatbot and RAG system development using internal LLMs; implemented feedback learning and fine-tuning; and built a multimodal knowledge graph powering RAG. He developed real-time bonus calculation systems and fraud detection using Spark streaming for large-scale ML, created deep learning entity extraction systems for real-time maritime/shipping insights and worked on large-scale text mining, meeting summarization, and deep learning for summarization.

• Ph.D. in Computer Science, Athens University of Economics and Business
• Data Science Master-M2 from École Polytechnique
• Bachelor of Science + M1 in Electrical and Computer Engineering from The Aristotle University of Thessaloniki

• Graph classification with 2D CNNs, ICANN 2019
• Kernel Graph Convolutional Neural Networks, ICANN 2018
• An optimization approach for sub-event detection and summarization in Twitter, ECIR 2018
• Unsupervised abstractive meeting summarization, ACL 2018
• A Degeneracy Framework for Graph Similarity, IJCAI 2018
• Word embeddings from large-scale Greek web content, arXiv 2018
• K-clique-graphs for dense subgraph discovery, ECML/PKDD 2017
• Matching node embeddings for graph similarity, AAAI 2017
• Real-time keyword extraction from conversations, EACL 2017
• Classifying graphs as images with CNNs, arXiv 2017
• Combining graph degeneracy and submodularity for extractive summarization, 2017