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

Nature-inspired Metaheuristics in Unsupervised Learning
(date and time will be provided soon...)

Szymon Lukasik Abstract.
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.

Important Dates

Abstract submission:
07 June 2021
23 June 2021

Notification of acceptance:
20 July 2021
31 July 2021

Late paper submission:
28 July 2021
05 August 2021

Notification of Late paper acceptance:
29 July 2021
10 August 2021

Camera ready paper:
28 July 2021
08 August 2021

Early registration:
07 July 2021 - 07 August 2021
19 July 2021 - 19 August 2021

Sponsored by
IEEE Ukraine Section I&M / CI Joint Societies Chapter
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Research Institute for Intelligent Computer Systems
West Ukrainian National University
Faculty of Electrical and Computer Engineering
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Cracow University of Technology
IEEE Ukraine Section
IEEE Ukraine Section
IEEE Poland Section
IEEE Poland Section
MDPI Sensors
MDPI Sensors
River Publishers
River Publishers