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Shaping the Future of AI for Research at SU: A Faculty-Wide Dialogue

→ Europe/Stockholm
FD5 (AlbaNova Main Building)

FD5

AlbaNova Main Building

Roslagstullsbacken 21, floor 5
Jens Jasche (Stockholm University)
Registration
Participants
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    • Afternoon Workshop on AI for Science: Afternoon AI Workshop
      • 1
        Welcome & Introduction
      • 2
        Speed Talks
        • a) TBD
          Speaker: Prof. Arne Elofsson (Department of biochemistry and biophysics (DBB))
        • b) TBD
          Speaker: Prof. Fernando Jaramillo (Department of Physical Geography)
        • c) TBD
          Speaker: Dr Allison Hsiang (Department of Geological Sciences)
        • d) TBD
          Speaker: Prof. Chun-Biu Li (Department of Mathematics)
      • 14:30
        Break (with beverages)
      • 3
        Explore & Exchange: Thematic Breakouts

        These parallel breakout discussions will focus on how AI intersects with key scientific research tasks, such as hypothesis generation, modeling, data analysis, lab automation, and training. The aim is to identify common needs, challenges, and opportunities across disciplines. Outcomes from these discussions will help shape the direction and priorities of a future Faculty-wide AI Center for Science.

        • a) Scientific Reasoning and Hypothesis Generation with AI

          How can AI support the creative and analytical stages of discovery?
          (e.g., LLMs, semantic tools, literature mining)

        • b) AI for Experimental Design and Laboratory Automation

          How is AI changing how we plan, conduct, and interpret experiments?
          (automation, scheduling, robotics)

        • c) AI-Enhanced Modeling and Simulation

          Can AI augment or even replace traditional simulations?
          (surrogate modeling, emulators, simulation-based inference)

        • d) Data Acquisition, Processing, and Analysis

          How do we best use AI across the data pipeline?
          (from collection to analysis, with focus on infrastructure and reproducibility)

        • e) Teaching, Training, and Skills Development in Scientific AI

          How can the center support the development of AI fluency among researchers, students, and staff?

      • 15:35
        Break
      • 4
        Breakout Summary & Roadmap Planning
      • 5
        Structured Networking
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