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DTSTAMP:20260421T090512Z
LOCATION:Bldg. 6 - Room 102
DTSTART;TZID=Europe/Stockholm:20260629T160000
DTEND;TZID=Europe/Stockholm:20260629T180000
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:IDEAS4HPC proposes a minisymposium on bias, fairness, and tran
 sparency in high performance computing (HPC), addressing ethical and socie
 tal challenges that arise as large-scale computational methods increasingl
 y influence scientific discovery, engineering, and public decision-making.
  The session brings together speakers at the intersection of HPC, data, et
 hics, and domain science, highlighting how diversity of perspectives and i
 nterdisciplinary collaboration can improve the robustness, reproducibility
 , and societal impact of computational research. The first presentation of
 fers an early-career perspective through a hands-on case study on AI-drive
 n digital twins for drought early warning in the Alps, illustrating how HP
 C-enabled AI can support equitable, climate-relevant decision-making and e
 nvironmental resilience. The second contribution examines the design of fa
 ir, carbon-aware, and socially responsible scheduling mechanisms for large
 -scale HPC infrastructures, drawing on operational experience from the CER
 N Worldwide LHC Computing Grid and the SKA Science Regional Centre Network
 . The third presentation explores human-centered approaches to fairness an
 d transparency in AI-powered HPC workflows, focusing on human–AI collabora
 tion, explainable AI, and data visualization to enable bias detection, mod
 el understanding, and informed human decision-making. The fourth presentat
 ion addresses breaking disciplinary silos through federated, FAIR, and fai
 r approaches to Digital Twins, for domains ranging from health up to socia
 l sciences.\n\nBreaking the disciplinary silos: federated, FAIR, and fair 
 approaches for Virtual Human Twins in health and care\n\nFollowing the Eur
 opean Commission (EC) definition, a Virtual Human Twin (VHT) is a digital 
 representation of human health or disease across multiple anatomical scale
 s, from cells to organ systems. Built from computational models and hetero
 geneous data, VHTs aim to simulate and predict physiological ...\n\n\nLies
 bet Geris (KU Leuven, VPH society)\n---------------------\nFrom Scalable W
 orkflows to Trustworthy AI: Fairness, Bias, and Reproducibility on HPC\n\n
 My work at CERN openlab focused on evaluating open-source AI workflows for
  scientific digital twins on HPC systems using the interTwin/itwinai stack
 . While studying distributed training across JUWELS Booster and Vega, I fo
 und that issues that look purely technical, such as data partitioning, per
 form...\n\n\nAnjali Khantaal (CERN, MBZUAI)\n---------------------\nProACT
 : Fair and Carbon-Aware Scheduling for Responsible HPC\n\nHPC infrastructu
 res face increasing pressure to reduce emissions while continuing to suppo
 rt diverse and growing scientific workloads. Initiatives by major cloud pr
 oviders such as Google, Microsoft, and Amazon demonstrate that delaying or
  relocating flexible workloads can significantly reduce emissi...\n\n\nDen
 isa-Andreea Constantinescu (EPFL) and Steven Senator (Los Alamos National 
 Laboratory)\n\nDomain: Climate, Weather, and Earth Sciences, Engineering, 
 Life Sciences, Computational Methods and Applied Mathematics\n\nSession Ch
 airs: Maria Grazia Giuffreda (ETH Zurich / CSCS), Florina Ciorba (Universi
 ty of Basel), Marie-Christine Sawley (ICES Foundation), and Maria Girone (
 CERN)
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