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19th Machine Learning in Healthcare meetup - sponsored by QUEST

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Vince
19th Machine Learning in Healthcare meetup - sponsored by QUEST

Details

We are delighted to invite you to our next meetup!

This time we'll welcome a very renowned speaker, Sebastian Lapuschkin, the head of explainable AI at the Fraunhofer Heinrich Hertz Institute.

Sebastian received his Ph.D. degree with distinction from the Berlin Institute of Technology in 2018 for his pioneering contributions to the field of Explainable Artificial Intelligence (XAI) and interpretable machine learning.
From 2007 to 2013 he studied computer science (B. Sc. and M. Sc.) at the Berlin Institute of Technology, with a focus on software engineering and machine learning.
Currently, he is the Head of the Explainable Artificial Intelligence at Fraunhofer Heinrich Hertz Institute (HHI) in Berlin.
He is the recipient of multiple awards, including the Hugo-Geiger-Prize for outstanding doctoral achievement and the 2020 Pattern Recognition Best Paper Award, and is listed among the 2% most impactful researchers of 2021 according to Stanford University.
His work is focused on pushing the boundaries of XAI, e.g, for achieving human-understandable explanations, or towards the utilization of interpretable feedback for the improvement of machine learning systems and data.
Further research interests include efficient machine learning and data analysis, data and algorithm visualization.

His talk titled "Model-Assisted Data Analysis via xAI" will be about best practices and the latest trends in explainable AI.

The emerging field of eXplainable Artificial Intelligence (XAI) aims to bring transparency to today’s powerful but opaque deep learning models. However, the vast majority of current approaches to XAI only provide partial insights via heatmaps in the input space of the AI and leave the burden of interpreting the model’s reasoning -- with all its degrees of freedom -- to the user.
This talk will cover how established techniques from XAI can be used to successfully understand, debug and improve machine learning models, data and pipelines (at hand of select examples borrowed from he medical domain).
Furthermore, an outlook on how recent developments in XAI may lead to more human interpretable explanations leading to novel analyses will be provided.

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.
We will of course provide the classic "Pizza and Beer"!

Please, if your RSVP-ed but realize that you can´t join please make sure to make your spot available for someone else!

Be aware that sometimes only one of the 4 elevators works!

The venue and food/drinks are kindly provided by the QUEST Center

Doors will be open at 6:30 pm, we will begin at 7 pm sharp.

7 pm: Introduction by the hosts.

7:05 pm: talk Sebastian

8 pm: time for networking, talking, eating even more Pizza, having fun

End 9:30 pm.

COVID-19-Sicherheitsmaßnahmen

Event findet in einem Gebäude statt
Please refrain from attending when you are sick. Sick people will be asked to leave.
Der Event-Veranstalter schreibt für dieses Event die oben genannten Sicherheitsmaßnahmen vor. Meetup ist nicht für die Einhaltung der Maßnahmen verantwortlich und überprüft nicht, ob die Maßnahmen befolgt werden.
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Machine Learning in Healthcare Berlin
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Berlin Institute of Health (BIH)
Anna-Louisa-Karsch-Straße 2, 10178 · Berlin