Topic

Data Science

idalab seminar #17: Interactive data visualisation – Can new empirical approaches in macroeconomic research reveal the true nature of our financial systems?

The Global Financial Crisis of 2007-2008 did not only cause the biggest loss in output post World War II, its far-reaching ripple effects also revealed that interdependencies between individual players in financial systems were much higher than previously assumed. This led policy makers to push the reset button for much of macroeconomic research. The analysis of financial systems and the development of empirical approaches became top of the agenda. One of these new empirical approaches was interactive data visualisation.

How to unlock valuable personal data for analysis: shedding light on the byzantine world of privacy-enhancing technology

At the heart of privacy preserving data analysis lies a fundamental paradox: privacy preservation aims to hide, while data analysis aims to reveal. The two concepts may seem completely irreconcilable at first, but – using the right approach – they need not be. To help you find this right approach for your specific use case, I discuss both the potential and the limitations of different solution concepts, ranging from de-identification to encryption.

idalab seminar #16: How to unlock valuable personal data for analysis – Shedding light on the byzantine world of privacy-enhancing technology

At the heart of privacy preserving data analysis lies a fundamental paradox: privacy preservation aims to hide, while data analysis aims to reveal. The two concepts may seem completely irreconcilable at first, but – using the right approach – they need not be. Our Data Strategist Lisa Martin spent two months researching this topic extensively, conducting interviews with industry experts and Startups alike. In this talk, Lisa will share her insights and we invite you to join us in discussing one of the most pressing issues of the 21st century: data privacy.

Cutting through the laptop installation jungle: How our MacBook setup repository helps our Data Scientists to organise their tools in only half a day

For me, one of the most frustrating parts of learning to program in earnest was that I always had some tooling problem before I could start. When I found a cool Python package and was eager to wrap my head around how it could help me to solve a problem, for instance, I often lacked the right version of Python to just install the package version I wanted and dive right in.

idalab seminar #14: Academia to Industry: Looking back on a decade of machine learning

Machine Learning is one of that areas that has seen a rapid transformation from a purely academic topic to becoming a driving technology in the industry these days. Mikio has seen both sides of the coin and will share his experience. What is the difference between academic research and bringing a ML driven product live? What does it take to productionize ML? And finally, how close are we to true AI?

Hassle-free travelling: idalab teams up with DB Systel, DFKI and Door2Door for research project SIM3S

Using public transport can be a challenge. In case of disruptions, loudspeaker announcements are the critical source of information – but they can be hard to understand, even for native speakers. English translations aren’t always provided, except in bigger cities. Matters get even worse for handicapped or elderly people, because information about accessibility on the alternative routes is usually not available at all.

idalab seminar #13: Exploring Chemical Space with Deep Learning

What if we could build batteries for electric cars that would take us further than a full tank of gasoline? If we could grow affordable, tasty and nutritious meat in the laboratory instead of occupying one third of the land on our planet with animal farming? What if we could easily identify promising targets in the human body for new cancer drugs?

Die Sehnsucht nach Transparenz ist eine Sehnsucht nach Begründung. Warum Algorithmen lernen sollten, eine Geschichte zu erzählen.

Basis aller heutigen Künstlichen Intelligenz sind bekanntlich Algorithmen. Diese sind in den letzten Jahren in zunehmendem Ausmaß in den Fokus der öffentlichen Wahrnehmung gerückt. Dabei schwankt der Grad an thematischer Souveränität und Güte der einzelnen Wortmeldungen aus Presse, Politik und Gesellschaft teils erheblich.