Academician Nikolai Denkov - Prime Minister of the Republic of Bulgaria
Iliana Ivanova - European Commissioner for Innovation, Research, Culture, Education and Youth
Prof. Galin Tzokov - Minister of Education and Science
Milena Stoycheva - Minister of Innovation and Growth
Alexander Yolovski - Minister of e-Government

Moderator: Montserrat Daban, the President of the European Bioregions Council (CEBR)
Prof. Victoria Sarafian, MD, PhD, DSc - Research Institute at Medical University of Plovdiv
Yana Georgieva, Medical University-Sofia, member of the management board of the Strategic research and innovation programme
Maria Nakova - EDIH in construction, Cleantech Bulgaria
Maria Pournari - COO EDIH Health Hub, Larisa

Moderator: Kristina Eskenazi - AI Cluster Bulgaria, Health & Life Sciences Cluster
Speakers:
Sylvia Ilieva, PhD - Director of “Big Data for Smart Society” Institute (GATE), Project Veles
Prof. Iliya Iliev - Perimed
Kiril Kirilov - Оperational manager at Discoverer
Apostolos Dimitriadis - BD & In Manager, FORTH, Institute of Computer Science

Svetlana Boyanova, Chairperson of Institute for Agrostrategies and Innovations and Chairperson of AgroHub.BG
Mariyana Hamanova – Executive Director of Cleantech Bulgaria and NCP for Cluster 6: Food, Bioeconomy, Natural Resources, Agriculture and Environment

Moderator: Assoc. Professor Dimitar Nikolov - Chair of the Managing Board of The Cluster of Microelectronics and Industrial Electronics Systems (CMIES), TU Sofia
Speakers:
Todor Mladenov - Chief Executive Officer&Board Member · Sofia Tech Park JSC
Svetoslav Mollov, Head of Technology Transfer and Commercialization at Quasar Competence Center
Prof. Dr Eng. Georgi Todorov - Technical University Sofia
Prof. Todor Ganchev - Head of the Artificial Intelligence Laboratory at the Technical University of Varna
Kiril Kirilov - Оperational manager at Discoverer

Albena Kuyumdzhieva, Petya Najdenova-Andreeva, Kiril Borisov, Viktoria Petrova

Predictive maintenance is critical for industries relying on machinery and equipment to avoid unplanned downtime and reduce operational costs. Google Cloud offers a range of AI and machine learning tools, such as BigQuery ML and AutoML, that can be applied to predict equipment failures and schedule maintenance proactively. This theme explores the application of Google tools to develop and deploy AI-driven predictive maintenance systems in industrial settings.

In today's competitive business landscape, providing personalised experiences to customers is essential for retention and growth. Google offers a suite of AI tools, including TensorFlow and Google Cloud AI, which can be harnessed to create sophisticated recommendation engines, chatbots, and predictive analytics models. This theme focuses on using Google's AI capabilities to develop advanced personalisation solutions that enhance customer engagement, drive sales, and improve overall satisfaction.

Natural Language Processing (NLP) is a valuable tool for businesses looking to gain insights from text data, such as customer reviews, social media content, and support tickets. Google Cloud's NLP tools, including Cloud Natural Language and BERT-based models, can be used to perform sentiment analysis and content optimisation. This theme explores the application of NLP techniques to extract actionable insights from textual data and improve content strategies.

Image recognition and analysis can provide businesses with valuable insights, from automating quality control in manufacturing to enhancing user experiences in e-commerce. Google AutoML Vision simplifies the development of custom image recognition models. This theme focuses on creating and deploying high-accuracy image recognition systems for various business applications.