Confirmed Speakers
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Bart Baesens
Associate Professor
Department of Decision Sciences and Information Management
KU Leuven, Belgium
"Social Networks Analytics using GOTCHA: Theory and Applications"
A common assumption in analytical applications is that customer behavior is independent and identically distributed, often referred to as the IDD assumption. However, in many real-life settings this assumption is simply not valid! Social network effects between customers, both implicit and explicit, create collective correlational behavior which needs to be appropriately analyzed and modeled. In this talk, we start by outlining the architecture of a social network learning environment, consisting of a local model (e.g. a logistic regression model), a relational learner (e.g. a relational neighbor classifier), and a collective inferencing procedure (e.g. Google PageRank).
We then introduce our recently developed GOTCHA method for social network analytics and illustrate the application thereof in various real-life settings such as churn prediction, credit scoring and fraud detection. It will be empirically shown how GOTCHA allows to efficiently model social network effects, hereby generating both additional lift and profit compared to, e.g., a flat logistic regression model. Throughout the presentation, the speaker will extensively report on his recent research insights.
See more about Prof. Baesens here
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Usama Fayyad, Ph.D
CEO Open Insights / www.open-insights.com
He reactivated Open Insights, after leaving Barclays in London. He is also Interim CTO for Stella.AI a Mountain View, CA VC-Funded startup in AI for recruitment. He is acting as Chief Operations & Technology Officer for MTN’s new division: MTN2.0 aiming to extend Africa’s largest telco into new revenue streams beyond Voice & Data.
See more about Mr. Fayyad here
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Peter Flach
Professor of Artificial Intelligence
Intelligent Systems Laboratory, Department of Computer Science
University of Bristol, UK
See more about Prof. Flach here
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Francisco Herrera
Head of Research Group SCI2S
Soft Computing and Intelligent Information Systems
Universidad de Granada, Spain
"A tour on Imbalanced big data classification and applications"
Big Data applications are emerging during the last years, and researchers from many disciplines are aware of the high advantages related to the knowledge extraction from this type of problem.
The topic of imbalanced classification has gathered a wide attention of researchers during the last several years. It occurs when the classes represented in a problem show a skewed distribution, i.e., there is a minority (or positive) class, and a majority (or negative) one. This case study may be due to rarity of occurrence of a given concept, or even because of some restrictions during the gathering of data for a particular class. In this sense, class imbalance is ubiquitous and prevalent in several applications. The emergence of Big Data brings new problems and challenges for the class imbalance problem.
In this lecture we focus on learning from imbalanced data problems in the context of Big Data, especially when faced with the challenge of Volume. We will analyze the strengths and weaknesses of various MapReduce-based algorithms that address imbalanced data. We will present the current approaches presenting real cases of study and applications, and some research challenges.
See more about Prof. Herrera here
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J. R. Reagan
Vice Dean
Endicott College of International Studies
Woosong University, South Korea
"Designing Security for Next Industrial Revolution"
Around the world, industries are experiencing a digital transformation that is accelerated by exponentially growing technologies and data. The networking of ’internet of things, services, data and people’ will fundamentally change the future of individual companies, as well as transform market dynamics across a whole range of industries. This talk how to design for security in this new environment and the impact data, analytics & technology will have in shaping it.
See more about Prof. Reagan here
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Further speakers will be confirmed.
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