The 19th International Conference on Artificial Intelligence and Soft Computing

October 12-14, 2020

Contact - ICAISC 2020 Organizing Committee

General Chairman
Leszek Rutkowski Leszek Rutkowski email: leszek.rutkowski.a_t.pcz.pl
Databases and Internet Submission
Marcin Korytkowski Marcin Korytkowski email: marcin.korytkowski.a_t.pcz.pl
Finance Chair
Marcin Gabryel Marcin Gabryel email: marcin.gabryel.a_t.pcz.pl

Organizing Committee Office

Institute of Computational Intelligence Częstochowa University of Technology
al. Armii Krajowej 36 42-200 Częstochowa, Poland
Tel: +48 (34) 3250546 Fax: +48 (34) 3250546 E-mail: icaisc@pcz.pl ICAISC 2020 Web page: http://icaisc.eu

International Liaison

Prof. Jacek M. Żurada Dept. of Electr. and Comp. Engineering
University of Louisville, Louisville, KY 40292, USA
Tel: (502) 852-6314 Fax: (502) 852-3940 E-mail: jacek.zurada@louisville.edu URL: http://ci.uofl.edu/zurada

Invited Talks

Włodzisław Duch "Neurocognitive Technologies and Computational Intelligence for Human Augmentation"

Włodzisław Duch
Włodzisław Duch "Neurocognitive Technologies and Computational Intelligence for Human Augmentation" Department of Informatics, and NeuroCognitive Laboratory
Center for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Poland
Google: W. Duch, CV: http://www.is.umk.pl/~duch/cv/cv.html

Artificial Intelligence has great impact on every aspect of technology, including neurotechnologies used for human augmentation. In recent years progress in methods of brain activity measurement, analysis of neuroimaging and electrophysiological data, and understanding of brain processes, opens new areas for transdisciplinary applications. Identifying patterns of EEG/MEG, ECoG or fMRI signals that serve as "fingerprints" of high subnetwork activity allows for many applications: linking brain activity with thoughts, intentions, emotions and other mental states, objective diagnostic methods in neuropsychiatry, reliable brain-computer interfaces (BCI), optimization of brain processes through neurofeedback, therapeutic interventions using neuromodulation, neurorehabilitation based on direct brain stimulation combined with behavioral procedures. Some commercial applications for treating epilepsy, major depression and other mental problems are already on the market.
Although I will focus on technical aspects of brain fingerprinting it is worth to reflect how neurocognitive technologies will enable human-computer interaction, and in an unprecedented way will change the very nature of people, their social interactions and coupling with physical environment.

Tom Gedeon "Predicting human internal states from physiological signals"

Tom Gedeon
Tom Gedeon "Predicting human internal states from physiological signals" Research School of Computer Science, Australian National University

Tom Gedeon is Chair Professor of Computer Science at the Australian National University. He is formerly Deputy Dean and Head of Computer Science at ANU. His BSc and PhD are from the University of Western Australia, and Grad Dip Management from UNSW. He is twice a former President of the Asia-Pacific Neural Network Assembly, and former President of the Computing Research and Education Association of Australasia. He is currently a member of the Australian Research Council's College of Experts. He is an associate editor of the IEEE Transactions on Fuzzy Systems, and the INNS/Elsevier journal Neural Networks.
Tom's research focuses on bio-inspired computing (mainly neural, deep learning, fuzzy and evolutionary) and human centred computing (mainly eye gaze, wearable physiological signals, fNIRS, thermal, EEG) to construct truly responsive computer systems (biometrics and affective computing) and humanly useful information resources (hierarchical and time series knowledge), industrial (mining, defence) and social good (medical, educational) applications.


Human beings reflect their internal states in many ways in their physiological signals, from skin conductivity, heart rate, pupil dilation, brain signals and behavioural measures. Many of these can be collected unobtrusively. The kinds of internal states we have investigated include stress, depression, emotion veracity, and doubt. We have shown in a number of such areas that physiological signals recorded from a human observer can be used to predict the ground truth in the observed data better than the same human beings themselves can do. That is, by the use of appropriately cross-validated machine learning training, we can access implicit knowledge within the human participants, which is not available to their consciousness.

Jarek Gryz "Algorithms and Politics"

Jarek Gryz
Jarek Gryz "Algorithms and Politics" Department of Electrical Engineering and Computer Science
York University, Toronto, Canada, http://www.cs.yorku.ca/~jarek/

In the last few years, interpretability of classification models has become a very active area of research. Both ACM and IEEE initiated new interdisciplinary conferences where fairness, accountability and transparency of "black-box" algorithms is the main topic. Suddenly, computer programs are being evaluated from moral and political point of view.

In this talk, I will discuss a couple of recent controversies in this area. First, I will talk briefly about a supposed racial bias in a COMPAS system, widely used in US courts. Second, I will discuss the concept of algorithm interpretability in a more specific legal context. In 2018 EU introduced General Data Protection Regulation with a Right to Explanation for people subjected to automated decision making. The Regulation itself is very brief on what such a right might imply. I will attempt to explain what the Right to Explanation may involve. I then will argue that this right would be very difficult to implement due to technical challenges. I also maintain that the Right to Explanation may not be needed and sometimes may even be harmful.

Bartosz Krawczyk "Learning from imbalanced and difficult data"

Bartek Krawczyk
Bartosz Krawczyk "Learning from imbalanced and difficult data" Department of Computer Science, Virginia Commonwealth University, Richmond VA, USA

Bartosz Krawczyk is an assistant professor in the Department of Computer Science, Virginia Commonwealth University, Richmond VA, USA, where he heads the Machine Learning and Stream Mining Lab. He obtained his M.Sc. and Ph.D. degrees from Wroclaw University of Science and Technology, Poland, in 2012 and 2015 respectively. Dr. Krawczyk's current research interests include machine learning, data streams, ensemble learning, class imbalance, and explainable artificial intelligence. He has authored more than 60 journal papers and over 100 contributions to conferences. Dr. Krawczyk has coauthored the book Learning from Imbalanced Data Sets (Springer 2018). He was a recipient of numerous prestigious awards for his scientific achievements such as IEEE Richard Merwin Scholarship, IEEE Outstanding Leadership Award, and Amazon Machine Learning Award among others. He served as a Guest Editor for four journal special issues and as a Chair for fifteen special session and workshops. Dr. Krawczyk is a member of the Program Committee for conferences such as AAAI, IJCAI and IJCNN. He is the member of the editorial board for Applied Soft Computing (Elsevier).


Learning from imbalanced data is considered one of the vital challenges in contemporary machine learning. Despite more than three decades of research, the problem of handling skewed distributions is still as important as ever, with new challenges emerging on regular basis. This talk will give an overview of the imbalanced learning domain, focusing on contemporary challenging scenarios and recent developments. Special attention will be given to data-level difficulties and understanding minority classes, multi-class imbalanced problems, and data streams with dynamically evolving classes. The talk will discuss various resampling methods, low-dimensional embeddings, algorithm-level modifications, and ensemble learning approaches that were recently proposed to efficiently handle such challenging scenarios.

The next, 20th ICAISC will take place in Zakopane in June 20-24, 2021.
Committee on Informatics of the Polish Academy of Sciences

Program Committee

General chairman

Leszek Rutkowski Leszek Rutkowski

Area Chairs

Fuzzy Systems
Witold Pedrycz Witold Pedrycz
Evolutionary Algorithms
Zbigniew Michalewicz Zbigniew Michalewicz
Neural Networks
Jinde Cao Jinde Cao

Computer Vision
Dacheng Tao Dacheng Tao
Machine Learning
Nikhil R. Pal Nikhil R. Pal
Artificial Intelligence with Applications
Janusz Kacprzyk Janusz Kacprzyk

International Liaison

Jacek M. Żurada Jacek M. Żurada

International Program Committee

  • Hojjat Adeli - USA
  • Cesare Alippi - Italy
  • Shun-ichi Amari - Japan
  • Rafal A. Angryk - USA
  • Robert Babuska - Netherlands
  • James C. Bezdek - Australia
  • Piero P. Bonissone - USA
  • Bernadette Bouchon-Meunier - France
  • Jinde Cao - China
  • Juan Luis Castro - Spain
  • Yen-Wei Chen - Japan
  • Andrzej Cichocki - Japan
  • Krzysztof Cios - USA
  • Ian Cloete - Germany
  • Oscar Cordón - Spain
  • Bernard De Baets - Belgium
  • Włodzisław Duch - Poland
  • Meng Joo Er - Singapore
  • Pablo Estevez - Chile
  • David B. Fogel - USA
  • Tom Gedeon - Australia
  • Erol Gelenbe - United Kingdom
  • Jerzy W. Grzymala-Busse - USA
  • Hani Hagras - UK
  • Saman Halgamuge - Australia
  • Yoichi Hayashi - Japan
  • Tim Hendtlass - Australia
  • Francisco Herrera - Spain
  • Kaoru Hirota - Japan
  • Tingwen Huang - USA
  • Hisao Ishibuchi - Japan
  • Mo Jamshidi - USA
  • Robert John - UK
  • Janusz Kacprzyk - Poland
  • Nikola Kasabov - New Zealand
  • Okyay Kaynak - Turkey
  • Vojislav Kecman - USA
  • James M. Keller - USA
  • Etienne Kerre - Belgium
  • Frank Klawonn - Germany
  • Robert Kozma - USA
  • László Kóczy - Hungary
  • Józef Korbicz - Poland
  • Rudolf Kruse - German
  • Adam Krzyzak - Canada
  • Věra Kůrková - Czech Republic
  • Soo-Young Lee - Korea
  • Simon M. Lucas - UK
  • Luis Magdalena - Spain
  • Jerry M. Mendel - USA
  • Radko Mesiar - Slovakia
  • Zbigniew Michalewicz - Australia
  • Javier Montero - Spain
  • Eduard Montseny - Spain
  • Kazumi Nakamatsu - Japan
  • Detlef D. Nauck - Germany
  • Ngoc Thanh Nguyen - Poland
  • Erkki Oja - Finland
  • Nikhil R. Pal - India
  • Witold Pedrycz - Canada
  • Leonid Perlovsky - USA
  • Marios M. Polycarpou - Cyprus
  • Danil Prokhorov - USA
  • Vincenzo Piuri - Italy
  • Sarunas Raudys - Lithuania
  • Olga Rebrova - Russia
  • Vladimir Red’ko - Russia
  • Raúl Rojas - Germany
  • Imre J. Rudas - Hungary
  • Norihide Sano - Japan
  • Rudy Setiono - Singapore
  • Jennie Si - USA
  • Peter Sincak - Slovakia
  • Andrzej Skowron - Poland
  • Roman Słowiński - Poland
  • Pilar Sobrevilla - Spain
  • Janusz Starzyk - USA
  • Jerzy Stefanowski - Poland
  • Vitomir Štruc - Slovenia
  • Ron Sun - USA
  • Johan Suykens - Belgium
  • Ryszard Tadeusiewicz - Poland
  • Hideyuki Takagi - Japan
  • Dacheng Tao - Australia
  • Vicenç Torra - Spain
  • Burhan Turksen - Canada
  • Shiro Usui - Japan
  • Deliang Wang - USA
  • Jun Wang - Hong Kong
  • Lipo Wang - Singapore
  • Paul Werbos - USA
  • Bernard Widrow - USA
  • Kay C. Wiese - Canada
  • Bogdan M. Wilamowski - USA
  • Donald C. Wunsch - USA
  • Ronald R. Yager - USA
  • Xin-She Yang - United Kingdom
  • Gary Yen - USA
  • Sławomir Zadrożny - Poland
  • Jacek Zurada - USA