Copyright. International Conference on Knowledge, Innovation and Enterprise 2015

knowledge-informed  technology and business innovations & creativityTM

21-24 June GermanY
2nd E. Paul Torrance International
Roundtable on
Creative Thinking  
21 June
How To Leverage New Insights
4th European Symposium on
Big Data, Deep learning & Advanced Predictive Analytics
23-24 June
Berlin 2016
















Guest Speakers & KIE Channels (Down Below)




One-Stop-Shop KIE Channels

KEYNOTER: Professor Frank Habermann, Berlin School of Economics and Law, Germany


Frank Habermann (PhD) is a Professor at the Berlin School of Economics and Law in Germany. He is the co-founder of “Over the Fence”, an interdisciplinary community that aims to develop innovative tools for designing, managing and leading projects (http://overthefence.com.de). In this context, Habermann introduced the “Project Canvas”, a widely-used open-source tool to visually define meaningful projects. Habermann holds a PhD from the University of the Saarland in Germany. As a researcher and lecturer, he worked for the German Institute of Artificial Intelligence, and the Michael Smurfit Business School in Dublin, Ireland. For IMC, Europe’s biggest provider in Learning Management, he headed the consulting unit and was responsible for the firm’s international business. In 2009, Frank co-founded Becota (http://www.becota.com), a Berlin-based consultancy. Since 2010, Frank Habermann holds a professorship for Business Administration at the Berlin School of Economics and Law (http://www.hwr-berlin.de).


Presentation: How slow thinking can accelerate interdisciplinary projects


In his best-selling book “Thinking, Fast and Slow”, Nobel Prize in Economics winner David Kahneman outlined the dichotomy between two modes of thought and cognitive biases related to them. Frank Habermann applies this thesis to project management. Based on five years qualitative empirical research, he delineates people’s tendencies to conduct particular modes of thinking in certain project situations. The emphasis of the keynote presentation is on interdisciplinary teams which want to start a common project. Habermann demonstrates typical human biases and communication failures in the project initiation phase that are based on fast and intuitive thinking. By means of practical exercises, audience can self-test their modes of thinking and identify possible blind spots. At the end of the presentation, a tool for slow thinking is introduced. This “Project Canvas” can help interdisciplinary teams to develop a true common understanding about their future project and thus accelerate their future work. The “Project Canvas” is open-source and can be downloaded for free at overthefence.com.de.


KEYNOTERS: Chris Wilson and Michael Brown, the University of Derby, United Kingdom


Based at the University of Derby in the UK, Chris Wilson and Michael Brown have over 40 years combined experience of music in higher education, and have worked together for many years developing, presenting, and publishing research into creativity. Marked by interdisciplinarity and a focus on the exploration of boundaries between concepts, disciplines, and practices, they have published work in subjects as diverse as creative anthropology, business, project management, education, and the arts.


Presentation: The Future of Creativity


This presentation explores a number of questions: What is the future for creativity? How will we need to be creative in the coming decades? How will personal, social, and organizational creativity operate in a future of Artificial Intelligence, networked data and information? How might our perspective of creativity evolve and develop? Beginning with perhaps the most important question; how do we distinguish between natural and artificial creativity--between human, animal, and machine creation? Read More ……….….   

Chris Wilson

Michael Brown

KEYNOTER: Dr Dom Heger, CEO DHTechnologies/Data Nubes, Texas, USA


Presentation: The Impact of Deep Learning & Quantum Computing on Big Data


One of the goals and objectives of machine learning is that the networks should be teachable. It is rather trivial at a small scale to demonstrate how to feed a series of input examples and expected outputs into a model and to execute a training process to produce more accurate predictions over time. The main problem is how to do the same thing at a large scale while operating on complex problems such as speech or image recognition related projects. In 2012, Hinton et al. published a paper outlining different ways of accelerating that learning process. With most machine learning projects, the main challenge is in identifying the features in the raw input data set. Deep learning aims at removing that manual step by relying on the training process to discover the most useful patterns across the input examples. While the current Big Data ecosystem is considered as being very powerful by today’s standards, to actually increase the computing power of these systems to address the ever-growing Big Data project requirements, it is necessary to add additional transistors into each cluster node. Read More .......

KEYNOTER: Dr Alain Biem, vice president of Analytics and chief scientist of advanced solutions delivery at Opera Solutions  


Presentation: Management of The Analytic Lifecycle for Big Data


The Analytic Lifecycle involves building, deploying, and maintaining a variety of analytic models, on a variety of computing platforms, for a variety of tasks. The Management of the Analytic Lifecycle for Big Data, at rest or in motion, is a challenging endeavor requiring the delicate utilization and leveraging of various Big Data platforms and software assets, as data evolve.   In this presentation, we describe the management of Big Data Analytics lifecycle as an essential part of the data lifecycle and as a pre-requisite in all Big Data viable solutions. We will use the IBM Big Data Platform, which is a stack of software assets, to illustrate specific solutions to issues related analytic lifecycle management.  


Prof Nabil El Kadhi, Deputy Vice-Chancellor for Academic Affairs,  UoB, Oman.


Presentation: Information Systems: A Shift from Structured Data to Smart Cities, with Increasing Artificial Intelligence Capabilities …Read more …

KEYNOTER: Prof Ling Shao, Chair in Computer Vision and Head of the Computer Vision and Artificial Intelligence Group, Department of Computer Science and Digital Technologies  at Northumbria University, UK


Presentation: Discriminative Feature Learning and Image/Video Categorisation for Visual Big Data Categorisation for Visual Big Data Read more …