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DTSTART;TZID=Europe/Stockholm:20260629T160000
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UID:submissions.pasc-conference.org_PASC26_sess119@linklings.com
SUMMARY:MS2D - Breaking the HPC Silos: Towards Fairness for Tackling Bias 
 in Algorithms and Data
DESCRIPTION:Organizer(s): Maria Grazia Giuffreda (ETH Zurich / CSCS), Flor
 ina M. Ciorba (University of Basel), Marie-Christine Sawley (ICES Foundati
 on), and Maria Girone (CERN)\n\nIDEAS4HPC proposes a minisymposium on bias
 , fairness, and transparency in high performance computing (HPC), addressi
 ng ethical and societal challenges that arise as large-scale computational
  methods increasingly influence scientific discovery, engineering, and pub
 lic decision-making. The session brings together speakers at the intersect
 ion of HPC, data, ethics, and domain science, highlighting how diversity o
 f perspectives and interdisciplinary collaboration can improve the robustn
 ess, reproducibility, and societal impact of computational research. The f
 irst presentation offers an early-career perspective through a hands-on ca
 se study on AI-driven digital twins for drought early warning in the Alps,
  illustrating how HPC-enabled AI can support equitable, climate-relevant d
 ecision-making and environmental resilience. The second contribution exami
 nes the design of fair, carbon-aware, and socially responsible scheduling 
 mechanisms for large-scale HPC infrastructures, drawing on operational exp
 erience from the CERN Worldwide LHC Computing Grid and the SKA Science Reg
 ional Centre Network. The third presentation explores human-centered appro
 aches to fairness and transparency in AI-powered HPC workflows, focusing o
 n human–AI collaboration, explainable AI, and data visualization to enable
  bias detection, model understanding, and informed human decision-making. 
 The fourth presentation addresses breaking disciplinary silos through fede
 rated, FAIR, and fair approaches to Digital Twins, for domains ranging fro
 m health up to social sciences.\n\nProACT: Fair and Carbon-Aware Schedulin
 g for Responsible HPC\n\nHPC infrastructures face increasing pressure to r
 educe emissions while continuing to support diverse and growing scientific
  workloads. Initiatives by major cloud providers such as Google, Microsoft
 , and Amazon demonstrate that delaying or relocating flexible workloads ca
 n significantly reduce emissi...\n\n\nDenisa-Andreea Constantinescu (EPFL)
  and Steven Senator (Los Alamos National Laboratory)\n--------------------
 -\nHumans, Machines, and the Space Between: Engineering Effective Human-AI
  Partnerships\n\nIntelligence augmentation through mixed-initiative system
 s promises to combine AI's computational efficiency with human contextual 
 expertise. In this talk, I will explore a framework for bridging human and
  artificial intelligence through three core pillars: interpretability, fee
 dback, and augmentati...\n\n\nMennatallah El-Assady (ETH Zurich)\n--------
 -------------\nFrom Scalable Workflows to Trustworthy AI: Fairness, Bias, 
 and Reproducibility on HPC\n\nMy work at CERN openlab focused on evaluatin
 g open-source AI workflows for scientific digital twins on HPC systems usi
 ng the interTwin/itwinai stack. While studying distributed training across
  JUWELS Booster and Vega, I found that issues that look purely technical, 
 such as data partitioning, perform...\n\n\nAnjali Khantaal (CERN, MBZUAI)\
 n---------------------\nBreaking the Disciplinary Silos: Federated, FAIR, 
 and Fair Approaches for Virtual Human Twins in Health and Care\n\nFollowin
 g the European Commission (EC) definition, a Virtual Human Twin (VHT) is a
  digital representation of human health or disease across multiple anatomi
 cal scales, from cells to organ systems. Built from computational models a
 nd heterogeneous data, VHTs aim to simulate and predict physiological ...\
 n\n\nLiesbet Geris (KU Leuven, VPH society)\n\nDomain: Climate, Weather, a
 nd Earth Sciences, Engineering, Life Sciences, Computational Methods and A
 pplied Mathematics\n\nSession Chairs: Maria Grazia Giuffreda (ETH Zurich /
  CSCS) and Florina Ciorba (University of Basel)
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