2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary

International Joint Conference on Neural Networks - IJCNN 2019

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14-19 July 2019, InterContinental Budapest Hotel, HUNGARY.    www.ijcnn.org

On behalf of the IJCNN Organizing Committee, it is our great pleasure to invite you to the International Joint Conference on Neural Networks (IJCNN 2019). The conference is organized by the International Neural Network Society (INNS) in cooperation with the IEEE Computational Intelligence Society (IEEE-CIS), and is the premier international meeting for researchers and other professionals in neural networks and related areas. It will feature invited plenary talks by world-renowned speakers in the areas of neural network theory and applications, computational neuroscience, robotics, and distributed intelligence.

Important dates:

  • Paper submissions: December 15, 2018 (Submit your paper)
  • Paper Acceptance Notifications: January 30, 2019
  • Conference Dates: July 14-19, 2019

Call for Papers:

  • Paper submissions: December 15, 2018
  • Our Paper Submissions guidelines site includes a link for uploading papers, plus brief instructions for paper formatting and submission. More detail is available in the Authors' Guide for young researchers and those unfamiliar with the IEEE Paper submission system and IJCNN conference requirements.

Lists of the approved Tutorials, Competitions, Workshops, Panels

Confirmed Plenary Speakers:
Lee Giles is the David Reese Professor at the College of Information Sciences and Technology at the Pennsylvania State University, University Park, PA. He is also graduate college Professor of Computer Science and Engineering, courtesy Professor of Supply Chain and Information Systems, and Director of the Intelligent Systems Research Laboratory. He recently became a Teaching and Learning Technology Fellow and the Interim Associate Dean of Research for IST Isabelle Guyon obtained a engineering diploma from the Ecole Superieure de Physique et Chimie Industrielles de Paris, Paris, in 1985, and a Ph.D. degree in Physical Sciences from the Universite Pierre et Marie Curie, Paris, in 1988. She joined AT&T Bell Labs Research , Homdel, NJ, in January 1989. In January 1996, she left AT&T to try her luck with a startup company, CyberGold, which she left in April of the same year to start her own consulting company, ClopiNet. Recently, she also served as Vice President of a bioinformatics startup called BIOwulf.
Nicola Kasabov is the Director of the Knowledge Engineering and Discovery Research Centre (KEDRI) and Personal Chair of Knowledge Engineering in the School of Engineering, Computing and Mathematical Sciences at AUT. His main interests are in the areas of: computational intelligence, neuro-computing, bioinformatics, neuroinformatics, speech and image processing, novel methods for data mining and knowledge discovery. Vera Kurkova received Ph.D. in mathematics from the Charles University, Prague, and DrSc. (Prof.) in theoretical computer science from the Czech Academy of Sciences. She is a senior scientist in the Department of Machine Learning, Institute of Computer Science, Czech Academy of Sciences. In 2002-2009 she was the Head of the Department of Theoretical Computer Science.
Adam Miklosi is a Hungarian ethologist, expert on dog cognition and behavior. He is a full professor and the head of the Ethology Department at the Eötvös Loránd University in Budapest, Hungary. In 2016 he was elected as a corresponding member of the Hungarian Academy of Sciences. He is the co-founder and leader of the Family Dog Project, which aims to study human-dog interaction from an ethological perspective. In 2014 he published the 2nd edition of an academic volume entitled Dog Behaviour, Evolution, and Cognition by Oxford University Press. Errki Oja is a Finnish computer scientist and Aalto Distinguished Professor in the Department of Information and Computer Science at Aalto University School of Science. He is recognized for developing Oja's rule, which is a model of how neurons in the brain or in artificial neural networks learn over time. He is a Fellow of the International Association for Pattern Recognition and the IEEE, and a member of the Finnish Academy of Sciences. He served as chairman of the European Neural Network Society between 2000 and 2005, and as the chairman of the Academy of Finland’s Research Council for Natural Sciences and Engineering between 2007 and 2012.
Danil Prokhorov received his Diploma in Robotics with Honors from the St. Petersburg State University of Aerospace Instrumentation, Russia, in 1992. He then worked in the St. Petersburg Institute for Informatics and Automation. After receiving Ph.D. in 1997, he joined the staff of Ford Scientific Research Laboratory, Dearborn, Michigan. While at Ford he was engaged in application-driven studies of intelligent technologies, developing new and improving existing machine learning/computational intelligence algorithms and applying them to problems in system modeling, control, diagnostics and optimization. Since 2011 he has been in charge of future mobility research department of Toyota NA. Wolf Singer studied Medicine in Munich and Paris, obtained his MD from the Ludwig Maximilian University in Munich, and his PhD from the Technical University in Munich. He is Director em. at the Max Planck Institute for Brain Research in Frankfurt, Founding Director both of the Frankfurt Institute for Advanced Studies (FIAS) and of the Ernst Strüngmann Institute for Neuroscience (ESI) and Director of the Ernst Strüngmann Forum.
Ichiro Tsuda holds the position of Professor at Chubu University Academy of Emerging Sciences, Professor Emeritus of Hokkaido University, and Visiting Professor at Osaka University, Tamagawa University and at many other universities. He has been Associate Member of Science Council of Japan since 2014. He received a degree of Doctor of Science (DSc) from Kyoto University in 1982. He has published widely in the field of chaotic dynamical systems and complex systems, and also in the field of cognitive neurodynamics.

Call for Sponsor and Exhibits:

  • IJCNN2019 is a great opportunity to promote your brand and to show off your neural network success stories as well as leading edge products to a world wide audience of people and organization in neural networks research and development. Please contact the Chair : Bill Howell, Sponsors & Exhibits Chair, Alberta, Canada

Topics and Areas include, but not limited to

  • Neural Networks Theory
  • Deep Learning
  • Deep Neuro Fuzzy Systems
  • Computational Neuroscience
  • Cognitive Models
  • Brain-Machine Interfaces
  • Embodied Robotics
  • Evolving Neural Networks
  • Neurodynamics
  • Neuroinformatics
  • Neuroengineering
  • Connectomics
  • Neural Networks and Big Data
  • Pattern Recognition

  • Machine Learning
  • Collective Intelligence
  • Hybrid Systems
  • Self-aware Systems
  • Data Mining
  • Sensor Networks
  • Hardware, Memristors
  • Agent-based Systems
  • Machine Perception
  • Bioinformatics
  • Artificial Life
  • Neural Network Applications
  • Social Media
  • Philosophical Issues

IJCNN 2019 General Co-Chairs :

Chrisina Jayne
INNS Director
Head of Engineering-Computing-Mathematics
Oxford Brooks University, UK
Zoltán Somogyvári
Wigner Institute
Hungarian Academy of Sciences
Budapest, Hungary
Péter Érdi
Honorary General Co-Chair
INNS VP Membership
Kalamazoo College
Michigan, USA

Sponsoring Organizations:

Platinum Platinum Silver (mailto) Bronze (mailto) Bronze (mailto)

Young researchers, and experienced researchers who are not familiar with the IJCNN processes and IEEE [paper submissions, formatting, copyrights, plagiarism checks], may find the Authors' Guide to be of some help.

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