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Predictive Analytics for Responsible Data Science

Date: Monday, 6th February 2017
Time: 03:30 PM
Location: CIC Ideation Studio, Building 22, Blackfriars Campus

On Monday 6 February from 3.30 – 5pm, we welcomed guest speaker Mykola Pechenizkiy who talked about Predictive Analytics for Responsible Data Science. This talk showcased current state-of-the-art tools for predictive analytics and emphasised that further research is needed to gain a deeper understanding of what it means for predictive analytics to be ethics-aware.


Application-driven research in predictive analytics contributes to the massive automation of the data-driven decision making and decision support. Recent successes and further commoditization of deep learning make this process even faster. Data mining researchers and data scientists often have a (false) believe that data mining techniques have no bad intents. In this talk I will revisit several popular applications in banking, intelligent transportation, personalized medicine and education to highlight why the general public, domain experts and policy makers have good reasons to consider off-the-shelf predictive analytics as a thread. I will present my subjective view on the current state-of-the-art and further research needed for gaining a deeper understanding of what it means for predictive analytics to be ethics-aware, transparent and accountable.

mpMykola Pechenizkiy Biography

Mykola is Full Professor, Chair Data Mining at the Department of Computer Science, Eindhoven University of Technology (TU/e), the Netherlands and Adjunct Professor in Data Mining for Industrial Applications at the University of Jyvaskyla, Finland. His expertise and research interests are in predictive analytics and knowledge discovery from evolving data, and in their application to real-world problems in industry, commerce, medicine and education. He develops generic frameworks and effective approaches for designing adaptive, context-aware predictive analytics systems. He has actively collaborated on this with industry. He has co-authored over 100 peer-reviewed publications and co-organized several workshops, conferences, special issues, and tutorials in these areas. He has co-edited the first Handbook of Educational Data Mining; serves as the President of IEDMS, the International Educational Data Mining Society. As a panelist and an invited speaker he has been advocating for the responsible data science and ethics-aware predictive analytics research at several events, including the FATML@ICML 2015 and NSF IRB Privacy and Big Data workshops and the EDM 2015 conference.

Click here for more information on Mykola Pechenizkiy.