Keynote Title: AI for Data Science in Industry

Keynote Speaker: Péter Ihász

Péter Ihász is an experienced researcher and developer with a working history in the fields of Applied and Computational Linguistics. During his studies at Ritsumeikan University and the Hungarian Academy of Sciences, Peter conducted research with a particular focus on Neural Language Modeling and Deep Language Generation. Currently he works at Deutsche Telekom IT Solutions Hungary, managing technical and architectural aspects of AI development.

Keynote Abstract:

Owing to recent technological advancements, the interest in and demand for artificial intelligence (AI) methods in data science have grown dramatically. The market has been flooded with AI gadgets targeting individual consumers. For instance, algorithms have been developed to generate realistic images and video streams (deep fake algorithms), automatically produce witty responses to user prompts (chatbots), and even predict one’s genetic heritage based on selfies (image classifiers). At the same time, there is a vast spectrum of AI applications meant for industrial use and, specifically, for the optimization of business strategies and processes. Time-series predictors forecasting the number of incoming calls to call-centers, reinforcement learning algorithms optimizing production lines, and search engines enabling quick and effective browsing on company homepages are just a few examples of such applications. The broad introduction of AI systems in the industry typically necessitates incremental developments with continual improvements and operational maintenance. The system lifecycle therefore includes additional activities besides predictive data modeling, such as data store management, data ingestion, deployment automation, etc. This talk is to provide the conference participants with insights on the lifecycles of industrial AI products by discussing several supervised and unsupervised use-cases. It will also elaborate on the DevOps and MLOps culture in a context of the AGILE framework – a set of developmental and operational practices aimed at shortening the system development time and providing for continuous delivery with high software quality.

Keynote Title:
Developing soft skills of a technology entrepreneur: understanding your customer through your value proposition

Keynote Speaker: Irina Pavlova

Irina Pavlova is an Associate Professor at Innovation Management Department of Tomsk State University of Control Systems and Radioelectronics and an Associate Professor at School of Engineering Entrepreneurship of National Research Tomsk Polytechnic University (Tomsk, Russia). She has a scientific degree of Cand. Sci. in Economics. Her area of specialization is innovation management, innovation systems, entrepreneurial universities, triple helix model, regional dimension of innovation, innovation statistics, innovation and technology policies.

Keynote Abstract:

For technology entrepreneurs, understanding your potential customer is a critical skill today. Your unique selling proposition, more commonly referred to as a USP, manifests that your offering is better than those of your competitors’. The underlying value proposition included in the USP differentiates your products and makes them to stand out at the market. What are the values of your customers that you are addressing to? During this workshop we will learn how to formulate functional, social and emotional values to fit into your value proposition. Since the value proposition is the centerpiece of the business modelling, good business models communicate the value messages to the customer in the most efficient way. The workshop will help you to explore how a value proposition should quickly answer the most immediate question when the potential customers encounter your brand. This question is “What makes you different from the rivals?” Also, we will learn what affects the value proposition messages in different societal, cultural and industrial

Keynote Title: Artificial Intelligence Technology in Education

Keynote Speaker: Ivan Krechetov

Ivan Krechetov is the head of the Laboratory of e-Learning Tools and Systems (LISMO) in TUSUR University. Today, the lab provides support for the university's e-learning systems and develops e-courses, simulators, and virtual labs. Since 2010, he has been engaged in research of adaptive learning. He has developed new algorithms, models, and software that allow universities to implement adaptive learning in LMS systems and develop adaptive electronic courses. The results are now used in some of the largest universities in the country. Current activities focus on the field of learning management based on artificial intelligence and data analysis technologies.

Keynote Abstract:

Artificial Intelligence technology is actively being introduced into various fields of activity. In education, these technologies are not yet as widely used as in business, but there are already well-known practices that use the power of AI. These include adaptive learning technology, a concept designed to improve the quality of education through a personalized approach and in-depth analysis of the learner's behavior. The presentation discusses TUSUR's experience in implementing adaptive learning in the educational process, methods, models and approaches underlying this technology.