Recommendation Systems, LLMs, and Information Retrieval: We invite you to attend lectures by Professor Juan Manuel Fernández Luna (University of Granada)

Next week, FIT BUT will welcome another prominent international expert whose lectures focus on the latest IT trends. We would like to invite you to attend the presentations by Spanish researcher Juan Manuel Fernández Luna, a professor at the University of Granada. Professor Luna has long been engaged in research in the areas of information retrieval, recommendation systems, personalization, learning to rank, and other methods of intelligent access to information and machine learning. In his work, he combines the theoretical foundations of information retrieval with practical applications in recommendation systems and explainable artificial intelligence.

Luna earned his Ph.D. in 2001 at the University of Granada, an institution founded in the 16th century and now ranked among the world’s top universities. Luna’s doctoral research focused on designing information retrieval models based on Bayesian networks. Today, he serves as a professor at the local Department of Computer Science and Artificial Intelligence (Departamento de Ciencias de la Computación e Inteligencia Artificial) and boasts, for example, numerous publications in prestigious academic journals and membership on their editorial boards.

Juan Manuel Fernández Luna will deliver two lectures at FIT VUT:

• LLM-Powered Conversational Explainable Recommender Systems
• • Thursday, April 16, 2026 at 10:00 AM, Room D105
  • As part of the MTIa course
  • The lecture will focus on the development of conversational explainable recommender systems using large language models (L-CERS) and will trace their transition from traditional “black-box” algorithms to interactive generative assistants. The technical transition from the standard Retrieval-Augmented Generation (RAG) approach to the innovative “LLM Wiki” paradigm will be discussed, where models pre-compile raw data into structured, interconnected knowledge bases for better reasoning. Through an analysis of the role of dialogue control, grounded explainability, and compiled knowledge, the lecture explores how these systems function as transparent systems, while also highlighting key challenges such as inference latency and trust-based evaluation.

• Information Retrieval Foundations and Advanced Topics
• • Thursday, April 16, 2026 at 2:00 PM, Room G202
  • As part of the PIS course
  • The lecture will offer a comprehensive overview of the field of Information Retrieval, mapping its evolution from the traditional foundations of librarianship to today’s intelligent generative systems. The lecturer will discuss the transition from Classical Information Retrieval (IR), in which systems relied on statistical keyword matching to rank documents, to Modern Information Retrieval (IR), in which search engines recognize the underlying intent of the user’s query. The lecture also includes an analysis of the basic components of the search pipeline—indexing, result ranking, and evaluation—and highlights the architectural changes that have enabled computers to move beyond merely providing “lists” (retrieval pipeline)—indexing, result ranking, and evaluation—and an emphasis on the architectural changes that have enabled computers to move from merely providing “lists of links” to providing direct, synthesized answers through the development of deep learning. By linking historical search models with the latest developments in Retrieval-Augmented Generation (RAG) technology, the lecture offers a comprehensive view of how information systems have evolved to handle the vast complexity of unstructured data in the current digital age.

Both lectures will thus offer insights into modern trends in computer science: the convergence of information retrieval, recommendation systems, conversational interfaces, and large language models. The event is intended for students, academics, and anyone interested in current developments in artificial intelligence, information systems, and data science. You are cordially invited.