Inauguration of “Alps” Research Infrastructure - Scientific Symposium

ETH Zurich Campus Hönggerberg, HCI G3
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We are excited to invite you to the inauguration of “Alps” research infrastructure at the Swiss National Supercomputing Centre (CSCS). This event will kick off with a scientific symposium at ETH Zurich focused on “Transforming the Future with Scientific Computing, Big Data & Machine Learning.”

ETH Zurich Campus Hönggerberg, HCI G3
Wolfgang-Pauli-Strasse 27
Zurich, Switzerland

We look forward to welcoming you in Zurich!

The symposium will open with a welcome address by Prof. Christian Wolfrum, Vice President of Research at ETH Zurich, followed by an introduction to “Alps” by CSCS Director Prof. Thomas Schulthess  and Prof. Torsten Hoefler, Chief Architect for Machine Learning at CSCS. Esteemed experts including Prof. Mary-Anne Hartley, Prof. Jean-Paul Kneib, Prof. Nicola Spaldin, Prof. Tanja Stadler and Dr. Peter Bauer will discuss the symposium theme with moderation by Prof. Claus Beisbart, a physicist and philosopher from the University of Bern.

A lunch will be offered during the symposium (registration required)


  • 9:30 – 10:00 Registration

  • 10:00 – 11:40 Morning Session
    • Welcome
      • Dr Joost VandeVondele (Deputy Director for Science, CSCS)
      • Prof. Christian Wolfrum (Vice President for Research, ETH Zurich)
    • Introducing Alps, Prof. Thomas Schulthess (CSCS Director) & Prof. Torsten Hoefler (ETH Zurich & CSCS)
    • Implementable Generative AI for Clinical Practice, Prof. Mary Anne Hartley (Yale Institute for Global Health & EPFL)
    • Next-Generation Radio Interferometry Computing, Prof. Jean-Paul Kneib (Laboratory of Astrophysics, EPFL)
  • 11:40 – 12:30 Lunch Break

  • 12:30 – 14:30 Afternoon Session
    • Supercomputers, materials, and the future of human civilization, Prof. Nicola Spaldin (Department of Materials, ETH Zurich)
    • Understanding pathogen spread through big data, Prof. Tanja Stadler (Department of Biosystems Science and Engineering, ETH Zurich)
    • The new age of weather and climate computing, Dr Peter Bauer (retired as a director from ECMWF, guest scientist Max-Planck-Institute for Meteorology)
    • Panel discussion; Moderator: Prof. Claus Beisbart


  • Abstracts

    Implementable Generative AI for Clinical Practice

    Prof. Mary Anne Hartley (Yale Institute for Global Health & EPFL)


    Decision-making in clinical practice can be life- saving... and, when done poorly, life-threatening. Integrating generative AI systems into these volatile high-stakes environments requires a “learning system” that fosters evidence-based trust and adoption through co-design and continuous alignment. In this talk, I will introduce Meditron (our suite of medical foundation models), and its learning system, MOOVE (Massive Online Open Validation and Evaluation) which aligns and ben- chmarks LLMs to real-world clinical standards.

    Short Biography

    Prof. Mary-Anne Hartley (“Annie”, MD, Ph.D. MPH), leads the Laboratory for intelligent Global Health and Humanitarian Response Technologies (LiGHT) based jointly at Yale School of Medicine, EPFL School of Computer Science, and CMU-Africa School of Engineering in Rwanda. Her team works with NGOs and humanitarian response organizations like the WHO, Doctors Without Borders, and the International Committee of the Red Cross to develop implementable AI-powered technologies to improve healthcare in resource-limited settings and under-represented populations. In her free time, Annie is a passionate lover-of-street-dogs and medical doctor and continues to work clinically in a volunteer capacity in her home country of South Africa.


    Next-Generation Radio Interferometry Computing

    Prof. Jean-Paul Kneib (Laboratory of Astrophysics, EPFL)


    The increase of computing power over the last two decades has enabled new fundamental science projects. One such major research infrastructure is the Square Kilometer Array Observatory (SKAO), which will use radio interferometry techniques with hundreds of antennas to map the Universe at radio wavelengths from 50 MHz to ~25 GHz.

    I will present work done in the PASC project, including the GPU implementation of standard synthesis, non-uniform FFT synthesis for the Bluebild Imaging ++ (BIPP) software, and extensive validation and benchmarking against state-of-the-art imaging software. Finally, I will show applications using data from the MWA and MeerKat telescopes, SKAO precursor experiments.

    Short Biography

    Prof. Jean-Paul Kneib holds a Master in space technologies and a Ph.D. in Astrophysics. He has worked as a support astronomer at the European Space Observatory in Chile and conducted research in Cambridge, Toulouse, Caltech, and Marseille before joining EPFL in 2012 with an ERC advanced grant. Since 2016, Kneib has been the Director of the EPFL Laboratory of Astrophysics. Renowned for his work on gravitational lensing and 3D mapping of the Universe via redshift surveys, he was the principal investigator of the SDSS-IV/eBOSS project from 2011 to 2018 and led the construction of the fiber positioner robotic system for the SDSS-V project. Currently, he is working on miniaturizing these robots for future cosmological projects and is now the Swiss Science Delegate at the SKAO Council.


    Supercomputers, Materials, and the Future of Human Civilization

    Prof. Nicola Spaldin (Department of Materials, ETH Zurich)


    From the Stone Age to the Bronze Age to the Iron Age, every major advance in human civilization has been driven by a development in Materials. I will discuss how, as we approach the end of today’s Silicon Age, new materials are essential for addressing many of our most urgent societal problems, and high performance computing is invaluable for designing the materials that will facilitate the transition to a new energy-efficient, climate-friendly Age.

    Short Biography

    Nicola Spaldin is the Professor of Materials Theory at ETH Zurich. She is best known for her development of the class of materials known as multiferroics, which combine simultaneous ferromagnetism and ferroelectricity, for which she received the Swiss Science Prize Marcel Benoist and the L’Oréal-UNESCO For Women in Science award. She is a passionate science educator, and coordinated the revision of her Department's BSc Curriculum in Materials Science. Spaldin has twice received the ETH Golden Owl Award for Teaching Excellence. When not trying to make a room-temperature superconductor, she can be found playing her clarinet, or skiing or climbing in the Alps.


    Understanding Pathogen Spread Through Big Data

    Prof. Tanja Stadler (Department of Biosystems Science and Engineering, ETH Zurich)


    Latest sequencing technologies have generated millions of SARS-CoV-2 sequences during the pandemic, a trend that continues with large amounts of sequencing data from various pathogens obtained from patients and the environment.

    We developed novel database structures facilitating global access and sharing of these big datasets. Our rapid querying features enable real-time exploration of pathogen spread. Additionally, we added a GPT-4-powered chat function for natural language data exploration, including Swiss German. Developing this prototype into a persistent tool will facilitate data exploration for public health officials and the public worldwide.

    Short Biography

    Tanja Stadler is a Full Professor at the Department of Biosystems Science and Engineering at ETH Zürich in Basel, and Vice-Chair of the Department. She is the president of the Swiss Science Advisory Panel COVID-19 and a member of the German National Academy of Sciences Leopoldina. Stadler’s research addresses core questions in life sciences from an evolutionary perspective, focusing on macroevolution, epidemiology, developmental biology, and immunology. Her work involves developing statistical phylodynamic tools to estimate evolutionary and population dynamics from genomic data and leading consortia to produce such data.


    The New Age of Weather and Climate Computing

    Dr. Peter Bauer (retired as a director from ECMWF, guest scientist Max-Planck-Institute for Meteorology)


    High-performance computing has been instrumental for advancing weather and climate prediction since the 1950s. The last decade focused on adapting complex codes to new processor architectures and approaching exascale systems. Recently, the need for comprehensive information systems to address climate change adaptation has expanded the scope of cost-effective weather and climate computing. New high-performance computing concepts and ‘machine learning everywhere’ will drive the next decade, transforming traditional computing and data approaches.

    Short Biography

    Dr. Peter Bauer obtained is PhD in meteorology from the University of Hamburg in 1992. He led a satellite remote sensing group at the German Aerospace Centre and held fellowships at NOAA, NASA, and IPSL before joining ECMWF in 2000. At ECMWF, he led the Satellite Data Assimilation Section and Model Development Division and deputised for the Research Department Director. He founded and coordinated the Scalability Programme preparing the prediction system for future computing and data handling architectures. At ECMWF, he coordinated the ExtremeEarth flagship proposal to the European Commission that fed into the Destination Earth programme in 2021. After retiringas a director from ECMWF in 2023, he joined the Max-Planck-Institute for Meteorology in Germany as a guest scientist.

  • Registration

    Registration is required for all participants.

    Registration fee: free

    Deadline for registration: Friday, August 30, 2024

  • Event Venue

    The conference will be held at the ETH Hönggerberg Campus.

    ETH Hönggerberg Campus
    HCI G3
    Wolfgang-Pauli-Strasse 27
    Zurich, Switzerland

    The ETH Hönggerberg Campus is located in the north of the city and is easily accessible by public transport.

    From the main station (Zürich HB)

    You need a valid ticket for zone 110 (city of Zurich).

    • Tram no. 11 from "Bahnhofquai/HB" to stop "Bucheggplatz", change to bus no. 69 to stop "ETH Hönggerberg".