• HELMHOLTZ AI</br>VIRTUAL </br>CONFERENCE</br> 2021 HELMHOLTZ AI</br>VIRTUAL </br>CONFERENCE</br> 2021

    HELMHOLTZ AI
    VIRTUAL
    CONFERENCE
    2021

That was the

Helmholtz AI virtual conference 2021

14-15 April 2021

In a data-based future, it will be key to democratise access to AI to maximise research impact.

We showed you how. 

You joined us to meet method and domain specialists with a shared interest in AI, learn more about the Helmholtz AI initiatives, discuss use cases in applied AI/ML and expand your network.
 

 

© Beate Kopp DESIGN.KONZEPT // www.visual-recording.com

 


 

PROGRAMME

14-15 April 2021 (CEST - Munich time)

TIME 14 APRIL 2021 15 APRIL 2021
15:00 Opening remarks: Fabian Theis PhD elevator pitch competition
15:10 Helmholtz AI in 2021: Fabian Theis
15:35

Use cases + discussion

  • Niki Kilbertus & Christina BukasHMGU - Health
  • David Greenberg. Hereon - Earth & Environment
  • Patrick StillerHZDR - Matter
 

Use cases + discussion

  • Stefan KesselheimFZJ - Information
  • Charlotte Debus. KIT - Energy
  • Rudolph Triebel & Lichao Mou. DLR - Aeronautics, Space and Transport
 
16:50 Break Break
17:00

Keynote lecture: Bernt Schiele

  • The Bright and Dark Sides of Computer Vision and Machine Learning —
    Challenges and Opportunities for Robustness and Security
 

Keynote lecture: Mihaela van der Schaar

  • Why medicine is creating exciting new frontiers for machine learning
 
17:45 Cocktail party / Speed networking Poster session / Networking lounge
18:45 End of day 1 End of day 2

 

 


 

Keynote speakers

Bernt Schiele

Bernt Schiele

Max Planck Director at MPI for Informatics & Professor at Saarland University

Bernt Schiele

Bernt Schiele

Bernt Schiele has been Max Planck Director at MPI for Informatics and Professor at Saarland University since 2010.

He studied computer science at the University of Karlsruhe, Germany. He worked on his master thesis in the field of robotics in Grenoble, France, where he also obtained the "diplome d'etudes approfondies d'informatique". In 1994 he worked in the field of multi-modal human-computer interfaces at Carnegie Mellon University, Pittsburgh, PA, USA in the group of Alex Waibel. In 1997 he obtained his PhD from INP Grenoble, France under the supervision of Prof. James L. Crowley in the field of computer vision. The title of his thesis was "Object Recognition using Multidimensional Receptive Field Histograms". Between 1997 and 2000 he was postdoctoral associate and Visiting Assistant Professor with the group of Prof. Alex Pentland at the Media Laboratory of the Massachusetts Institute of Technology, Cambridge, MA, USA. From 1999 until 2004 he was Assistant Professor at the Swiss Federal Institute of Technology in Zurich (ETH Zurich). Between 2004 and 2010 he was Full Professor at the computer science department of TU Darmstadt.

Image source: Max Planck Institute for Informatics

Mihaela van der Schaar

Mihaela van der Schaar

John Humphrey Plummer Professor of Machine Learning, AI and Medicine, University of Cambridge

Mihaela van der Schaar

Mihaela van der Schaar

Mihaela van der Schaar is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge, a Fellow at The Alan Turing Institute in London, and a Chancellor’s Professor at UCLA.

Mihaela was elected IEEE Fellow in 2009. She has received numerous awards, including the Oon Prize on Preventative Medicine from the University of Cambridge (2018), a National Science Foundation CAREER Award (2004), 3 IBM Faculty Awards, the IBM Exploratory Stream Analytics Innovation Award, the Philips Make a Difference Award and several best paper awards, including the IEEE Darlington Award.

Mihaela’s work has also led to 35 USA patents (many widely cited and adopted in standards) and 45+ contributions to international standards for which she received 3 International ISO (International Organization for Standardization) Awards.

In 2019, she was identified by National Endowment for Science, Technology and the Arts as the most-cited female AI researcher in the UK. She was also elected as a 2019 “Star in Computer Networking and Communications” by N²Women. Her research expertise spans signal and image processing, communication networks, network science, multimedia, game theory, distributed systems, machine learning and AI.

Mihaela’s research focus is on machine learning, AI and operations research for healthcare and medicine.

In addition to leading the van der Schaar Lab, Mihaela is founder and director of the Cambridge Centre for AI in Medicine (CCAIM).

Use case speakers


 

PhD elevator pitch competition

We were looking for the coolest data science PhD students!

Candidates submitted an up to three-minute video explaining their PhD project and got the chance to present their scientific topic live at the Helmholtz AI virtual conference!

The PhD students with the coolest pitch were selected by our jury for the final round and were invited to the live competition on 15 April 2021.

 

Winner:

1. Place: "Sign Language Recognition using 3D Convolutional Neural Networks",
Noha Sarhan, University of Hamburg (UHH).

2. Place: "Tropical Cyclone Forecasting – Can machine learning leverage state-of-the-art weather models?",
Michael Maier Gerber, Karlsruhe Institute of Technology (KIT).

3. Place: "Effects of Noisy Labels on Deep Neural Networks for Semantic Segmentation",
Sami Hamdan, Forschungszentrum Jülich (FZJ).


 

Virtual poster session

Great scientists shared their latest research highlights with us!

The poster session at the Helmholtz AI virtual conference 2021 was a synchronous virtual session where authors and attendees could interact in real time.

They used the opportunity to share their AI and ML research by submitting an abstract and uploading a scientific poster.


Winner:

1. Place: Marc Horlacher, Lambert Moyon, Yue Hu, Ernesto Elorduy Vergara, Svitlana Oleshko, Annalisa Marsico: "Computational Mapping of the Human SARS-CoV-2 Protein-RNA Interactome",
Helmholtz Zentrum München, Ludwig-Maximilians-Universität, Boehringer Ingelheim Pharma GmbH.

2. Place: Tobias Bernecker, Jakob Weiß, Daniel Rückert, Shadi Albarqouni: "FedNorm: Federated Learning with Modality-Based Normalization",
Helmholtz Zentrum München, Technical University of Munich, Universitätsklinikum Freiburg, Klinikum rechts der Isar.

3. Place: Frederic Bock, Sören Keller, Norbert Huber, Benjamin Klusemann: "Hybrid Modelling via Analytical Model Predictions Corrected with Machine Learning towards High-Fidelity Simulation Solutions",
Helmholtz-Zentrum hereon.


 

Organisers

Partners