16th Machine Learning in Healthcare meetup - BIH endorsed


Details
We are excited to invite you to our next meetup!
After the successful 1st AI community awards we are back with a true ML in Healthcare edition at our regular place in the BIH. We are very grateful for another year of support!
This time we'll welcome Franziska Boenisch, PhD student at Fraunhofer AISEC. Franziska will cover a highly interesting topic, which is very important for healthcare.
Have you ever wondered whether your healthcare model can be attacked? This is exactly the topic Franziska will talk about!
Title :
The Long and Winding Road of Secure and Private Machine Learning - Or: Stop people from cloning your models before their models start cloning you!
Abstract:
Nowadays, machine learning (ML) is used everywhere, including in sectors that deal with extremely sensitive data, like health or finance. And while most companies do not deploy a single line of code anymore without being tested somehow, ML models are often let out into the wild without being checked or secured. In my talk, I will guide you through the long road of possible threats and attacks that your ML models might be experiencing out there, and give an overview what countermeasures might be worth considering.
We will meet - as usually - in the “Atrium” conference room of the BIH, 5th floor of the Spreepalais, Anna-Louisa-Karsch-Straße 2, 10178 Berlin. Please enter the lobby, find the elevator group at Aufgang A and get out on the 5th floor. The entrance to the meeting room is labeled.
There will of course again be the classic "Pizza and Beer"!
Be aware that sometimes only one of the 4 elevators works!
The venue and food/drinks are again provided by the BIH and the BHI accelerator!
Doors will be open at 6:40 pm, we will begin at 7 pm sharp.
Introduction 7 pm: Introduction by the hosts.
Talk and Q&A 7:05 pm: Franziska Boenisch
Get together 8:00 pm: time for networking, talking, eating even more Pizza, having fun
End 9:30 pm.


16th Machine Learning in Healthcare meetup - BIH endorsed