Assoc. Prof. Szymon Lukasik
Faculty of Physics and Applied Computer Science, AGH University of Science and Technology
Systems Research Institute, Polish Academy of Sciences, Poland
Recent decades have been characterized by an unprecedented burst of new - potentially useful - data being generated in various fields of science and engineering. The toolbox of contemporary data science – though broad and reinforced by unconventional methods of artificial intelligence – does not contain algorithms that cope well with the challenges of so-called Big Data. The aim of this talk is to provide examples of techniques based on nature-inspired algorithms designed to solve large-scale unsupervised learning tasks. Besides presenting procedures uncovering unknown patterns in data set without preexisting labels we will also discuss variations of typical unsupervised data exploration, which stem from tackling real-world data science problems. Finally, the vivid landscape of nature-inspired metaheuristics will be also characterized, with the discussion on major trends and critical outlook on some individual algorithms.
Szymon Lukasik is an associate professor at at the AGH University of Science and Technology in Kraków and the Systems Research Institute of the Polish Academy of Sciences. PhD and habilitation in the field of data analysis and computational intelligence. A graduate of the Top 500 Innovators program at the Haas School of Business at the University of California, Berkeley, visiting scientist at UNINOVA (Portugal), National Laboratory of Pattern Recognition (China) and University of Technology Sydney (Australia). Author of over 60 publications in the field of data science and artificial intelligence methods. Invariably fascinated by the world of data and extracting valuable information. His main area of research interests cover nature inspired metaheuristics and unsupervised learning.
07 May 2021
07 June 2021
Notification of acceptance:
07 July 2021
Camera ready paper:
28 July 2021
07 July 2021 - 07 August 2021