Kanazawa, Japan | 3-5 April 2017

9th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2017)

Special Session Organizers

Prof. Andrzej W. Przybyszewski
University of Massachusetts Medical School,
Worcester, MA, USA
Polish-Japanese Academy of Information Technology
Warsaw, Poland
E-mail: przy@pjwstk.edu.pl; andrzej.przybyszewski@umassmed.edu

Dr. Tomasz Rutkowski
The University of Tokyo, Japan
Tokyo, Japan
E-mail: tomek@p.u-tokyo.ac.jp

Objectives and topics

Since Descartes who saw the body as a machine that gave the brain a special type of air imbued with vital force, understanding brain functions is a challenging task. Thanks to technological progress and advanced recording methods, there is a huge progress in experiments that enlighten certain aspects of the brain functions. However, we still are at the beginning of understanding deep brain computations and related learning algorithms. There are many intelligent algorithms, which simulate certain functions of the brain such as multilayer neural networks that can learn and classify objects but their intelligence is still very limited. Therefore, the aim of the InABRAIN 2017 Special Session at the 9th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2017) is to present different methods of brain activity recording and testing by means of the intelligent algorithms in order to decipher intelligence of the brain. Our session will offer an opportunity for participants from different labs or clinics to present their research directions and to compare their discoveries. The scope of the InABRAIN 2017 includes, but is not limited to the following topics:

Machine learning and data mining methods in brain research
Machine learning algorithms in objects recognition and their neurological meanings
Data mining methods to assist in brain surgery (e.g. Deep Brain Stimulation in Parkinson’s diseases)
Machine learning in motor symptom progressions in neurodegenerative diseases
Data mining in brain imaging: CT, MRI, and fMRI
Estimation of different therapies efficiencies by means of data mining
Computer-assisted diagnosis and treatment
Machine learning in brain mapping
Data Mining - Rough Sets Theory as a tool to study emotional brain
Brain plasticity and machine learning algorithms
Social brain and multi-agent systems
Learning algorithms describing plastic brain changes in social interactions
Interactive, intelligent descriptors of voice and music features
Diagnostic data mining emotions classification in music and voice
Shallow- and deep-learning methods in neurotechnology
BCI/BMI and neurofeedback approaches in pharma industry
Brain correlates of creativity and neuroaesthetics

Important dates

Submission of papers: 1 October 2016
Notification of acceptance: 1 November 2016
Camera-ready papers: 15 November 2016
Registration & payment: 15 December 2016
Conference date: 3-5 April 2017

Program Committee (to be invited)

Zbigniew Struzik, RIKEN Brain Science Institute, Japan
Zbigniew Ras, University of North Carolina at Charlotte, USA
Konrad Ciecierski, Warsaw University of Technology, Poland
Piotr Habela, Polish-Japanese Academy of Information Technology, Warsaw, Poland
Peter Novak, Brigham and Women’s Hospital, Boston, USA
Wieslaw Nowinski, Cardinal Stefan Wyszynski University, Warsaw, Poland
Andrei Barborica, Research & Compliance and Engineering, FHC, Inc., Bowdoin, ME, USA
Alicja Wieczorkowska, Polish-Japanese Academy of Information Technology, Warsaw, Poland
Majaz Moonis, Dept. Neurology, UMass Medical School, Worcester, MA, USA
Krzysztof Marasek, Polish-Japanese Academy of Information Technology, Warsaw, Poland
Mark Kon, Department of Mathematics, Boston University, Boston, USA
Rafal Zdunek, Wroclaw University of Science and Technology, Poland
Lech Polkowski, Polish-Japanese Academy of Information Technology, Warsaw, Poland
Andrzej Skowron, Institute of Mathematics, Warsaw University, Poland
Ryszard Gubrynowicz Polish-Japanese Academy of Information Technology, Warsaw, Poland
Takeshi Okada, The University of Tokyo, Japan
Dominik, Slezak, Institute of Mathematics, Warsaw University, Poland
Radoslaw Nielek, Polish-Japanese Academy of Information Technology, Warsaw, Poland

Submission

All contributions should be original and not published elsewhere or intended to be published during the review period. Authors are invited to submit their papers electronically in pdf format, through EasyChair. All the special sessions are centralized as tracks in the same conference management system as the regular papers. Therefore, to submit a paper please activate the following link and select the track: inABRAIN 2017: Special Session on Intelligent Algorithms and Brain Functions.

https://aciids.pwr.edu.pl/2017/

Authors are invited to submit original previously unpublished research papers written in English, of up to 10 pages, strictly following the LNCS/LNAI format guidelines. Authors can download the Latex (recommended) or Word templates available at Springer's web site. Submissions not following the format guidelines will be rejected without review. To ensure high quality, all papers will be thoroughly reviewed by the EAML 2017 Program Committee. All accepted papers must be presented by one of the authors who must register for the conference and pay the fee. The conference proceedings will be published by Springer in the prestigious series LNCS/LNAI (indexed by ISI CPCI-S, included in ISI Web of Science, EI, ACM Digital Library, dblp, Google Scholar, Scopus, etc.)

Attachments

Contact

Andrzej Przybyszewski (Andrzej.Przybyszewski@umassmed.edu, przy@pjwstk.edu.pl)