Scientific Program

Conference Series LLC Ltd invites all the participants across the globe to attend 6th Global Summit on Artificial Intelligence and Neural Networks Helsinki, Finland.

Day 1 :

Keynote Forum

Vincenzo Piuri

Università degli Studi di Milano, Italy

Keynote: Computational intelligence technologies for ambient intelligence
Neural Networks 2018  International Conference Keynote Speaker Vincenzo Piuri photo

Vincenzo Piuri is a Professor at the University of Milan, Italy and has been Visiting professor at the University of Texas at Austin, USA, and visiting researcher at George Mason University, USA. His research interests are: intelligent systems, signal and image processing, pattern analysis and recognition, machine learning and industrial applications. Original results have been published in 400+ papers. He is a Fellow Member of the IEEE, ACM Distinguished Scientist, and Senior Member of INNS. He has been IEEE Director, IEEE Vice President for Technical Activities (2015), and President of the IEEE Computational Intelligence Society. He is Editorin-Chief of the IEEE Systems Journal (2013-19). For his contributions to the advancement of theory and practice of computational intelligence in measurement systems and industrial applications, he received the IEEE Instrumentation and Measurement Society Technical Award (2002). He is an Honorary Professor at Obuda University (Hungary), Guangdong University of Petrochemical Technology (China), Muroran Institute of Technology (Japan), and Amity University (India).


Adaptability and advanced services for ambient intelligence require an intelligent technological support for understanding the current needs and the desires of users in the interactions with the environment for their daily use, as well as for understanding the current status of the environment also in complex situations. This infrastructure constitutes an essential base for smart living. Computational intelligence can provide additional flexible techniques for designing and implementing monitoring and control systems, which can be configured from behavioral examples or by mimicking approximate reasoning processes to achieve adaptable systems. This session will analyze the opportunities offered by computational intelligence to support the realization of adaptable operations and intelligent services for smart living in an ambient intelligent infrastructure.

Keynote Forum

Erwin E Sniedzins

Mount Knowledge Inc., Canada

Keynote: Automatic reduction of global and personal data overload

Time : 10:20-11:00

Neural Networks 2018  International Conference Keynote Speaker Erwin E Sniedzins photo

Erwin E Sniedzins is the President of Mount Knowledge Inc., Toronto, Canada. He has patented the Knowledge Generator™ (KG), which is an artificial intelligence application that takes any digitized textual content and automatically creates a MicroSelf-Reinforcement Learning and Personalize Gamification of this content into lessons, exercises and tests with scores and marks in dynamic real-time. He is the author and has published 12 books. He is also a Professor at Hebei University, Canada.


Educators, students, employers and employees are inundated with big data; they are seeking relief. AI provides the bridge between big data and personalized data using Natural Language Processing (NLP) and Genetic Algorithm Neural Networks (GANN). Artificial Intelligence is the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making and translation between languages. AI is transforming humanity’s cerebral evolution as a replacement of repetitive habitual motions and thoughts. In its evolutionary process humans developed their primary biological interfaces to interpret the data that they were receiving through their five senses, seeing, hearing, smelling, touching and tasting. In 1991 the World Wide Web (www.) was born and sensory assimilation of data felt the first angst of a new medium. 26 years later, more than 3.4 Exabyte of data is generated every day. This is comparable to a stack of CDs - from Earth to the Moon and back-each day. This onslaught of data is causing people a great deal of anxiety, stress and frustration. To overcome the pressure of knowledge acquisition, people should learn to handle big data and turn it into their personalized data.

Keynote Forum

Paolo Rocchi

University Luiss Guido Carli, Italy

Keynote: Intelligence’s origin and theoretical modeling

Time : 11:15-11:55

Neural Networks 2018  International Conference Keynote Speaker Paolo Rocchi photo

Paolo Rocchi has received a Degree in Physics from the Sapienza University of Rome in 1969 and was associated to the Institute of Physics as an Assistant Lecturer. The following year he joined IBM as a Docent and Researcher. He has carried out research and is still active in various fields of computing including software evolution, computer security, education, information theory, fundamentals of computer science, artificial intelligence and software engineering. He has written over one hundred and thirty works, including a dozen books. Upon retirement in 2010 he was recognized as an Emeritus Docent at IBM for his achievements in basic and applied research. He is also an Adjunct Professor at University LUISS Guido Carli. He is a Founder Member of the Artificial Intelligence Italian Association and a member of various scientific societies. He has received recognition even beyond the scientific community in the mass media.


Artificial Intelligence (AI) is usually defined as the science and engineering of making intelligent machines. AI experts do not confine themselves to practice and bring into question the very nature of intelligence. To win this intellectual and scientific challenge, AI experts should be backed by a solid theoretical base in particular Theoretical Computer Science (TCS) should furnish the notions necessary to explore the advanced properties of machines. Unfortunately this support does not seem to be adequate to the scopes. TCS illustrates every aspect of the computer system by means of formal theories although these theories are narrow, disjoined and abstract. How can AI experts answer profound questions about intelligence when the views of the computer and the brain prove to be fragmentary and insufficient? As an assumption how a unifying scientific theory begins with a simple concept and details all the phenomena occurring in the field through an inferential process. Step by step the theory justifies technical achievements and natural events. For example, mechanics is a unified body of knowledge that introduces the concept of speed. Then experts derive the notion of acceleration from it, in turn the notion of force, work, energy and so forth. A set of interconnected conclusions illustrates the entire domain and disentangles any conundrum through deductive reasoning. The structure of a theoretical construction in engineering and science has nothing to do with philosophy. Frame which kept forward, begins with the formal definition of the elementary piece of information which as assumed distinguishable and meaningful.