Pleased2MeetU: Black Swan Lux

Lux Future Lab » Pleased2MeetU: Black Swan Lux

Thursday 11 February 2016, lux future lab hosted its second “pleased-to-meet-you” breakfast.
This welcome session aimed at introduce newcomers to lfl community, fellow members and partners.

 

Meet Black Swan Lux

Emilia Tantar – co-founder, Chief Operating Officer
Alexandru-Adrian Tantar- co-founder, Vice President Research, Development, Innovation
Hannes De Wachter – co-founder, CEO
Thomas Engel – co-founder, Advisory Board

Who we are

Black Swan Lux is a high-tech spin-off of the University of Luxembourg active in the area of anomaly detection. With more than 10 years of academic research in the field of optimization and predictive analytics, our team has a strong background in the business development of high-tech research spin-offs.

What we do

We develop context-aware anomaly detection applications for people in high-risk situations, such as elderly people living independently and rescue workers. Our SafeLive solutions enable anomaly detection based on real-time continuous biometric sensor data from wearable devices.

What we think

The growth of the Ambient Assisted Living(AAL) market expected across Europe brings with it a need for dedicated assistance tools. The market will be driven by elderly people unwilling to go to the hospital and shortages in nursing home beds. SafeLive is built on the user’s needs, using their input, and embeds real-time context-aware analytics for off-the-shelf wearable devices. We provide a unique mix of anomaly detection and contextual understanding.

Where we’re headed

Black Swan LUX is intended as an R&D company, with the first goal being anomaly detection in real-time on wearable devices in order to support an independent and safer life for the elderly living at home. Together with our partners, we build high-quality, tailored solutions for supporting active ageing in the ambient assisted living context. We embrace anti-fragility and build upon newly occuring challenges. We aim to position ourselves as competitors in the area of anomaly detection.

Emilia, Thomas, Alex and Hannes, pleased to meet you!


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